The future of PanDA in ATLAS distributed computing

NASA Astrophysics Data System (ADS)

De, K.; Klimentov, A.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Schovancova, J.; Vaniachine, A.; Wenaus, T.

2015-12-01

Experiments at the Large Hadron Collider (LHC) face unprecedented computing challenges. Heterogeneous resources are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, while data processing requires more than a few billion hours of computing usage per year. The PanDA (Production and Distributed Analysis) system was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. In the process, the old batch job paradigm of locally managed computing in HEP was discarded in favour of a far more automated, flexible and scalable model. The success of PanDA in ATLAS is leading to widespread adoption and testing by other experiments. PanDA is the first exascale workload management system in HEP, already operating at more than a million computing jobs per day, and processing over an exabyte of data in 2013. There are many new challenges that PanDA will face in the near future, in addition to new challenges of scale, heterogeneity and increasing user base. PanDA will need to handle rapidly changing computing infrastructure, will require factorization of code for easier deployment, will need to incorporate additional information sources including network metrics in decision making, be able to control network circuits, handle dynamically sized workload processing, provide improved visualization, and face many other challenges. In this talk we will focus on the new features, planned or recently implemented, that are relevant to the next decade of distributed computing workload management using PanDA.

ATLAS Distributed Computing Experience and Performance During the LHC Run-2

NASA Astrophysics Data System (ADS)

Filipčič, A.; ATLAS Collaboration

2017-10-01

ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of the new model was demonstrated through the delivery of analysis datasets to users just one week after data taking, by completing the calibration loop, Tier-0 processing and train production steps promptly. The great flexibility of the new system also makes it possible to execute part of the Tier-0 processing on the grid when Tier-0 resources experience a backlog during high data-taking periods. The introduction of the data lifetime model, where each dataset is assigned a finite lifetime (with extensions possible for frequently accessed data), was made possible by Rucio. Thanks to this the storage crises experienced in Run-1 have not reappeared during Run-2. In addition, the distinction between Tier-1 and Tier-2 disk storage, now largely artificial given the quality of Tier-2 resources and their networking, has been removed through the introduction of dynamic ATLAS clouds that group the storage endpoint nucleus and its close-by execution satellite sites. All stable ATLAS sites are now able to store unique or primary copies of the datasets. ATLAS Distributed Computing is further evolving to speed up request processing by introducing network awareness, using machine learning and optimisation of the latencies during the execution of the full chain of tasks. The Event Service, a new workflow and job execution engine, is designed around check-pointing at the level of event processing to use opportunistic resources more efficiently. ATLAS has been extensively exploring possibilities of using computing resources extending beyond conventional grid sites in the WLCG fabric to deliver as many computing cycles as possible and thereby enhance the significance of the Monte-Carlo samples to deliver better physics results. The exploitation of opportunistic resources was at an early stage throughout 2015, at the level of 10% of the total ATLAS computing power, but in the next few years it is expected to deliver much more. In addition, demonstrating the ability to use an opportunistic resource can lead to securing ATLAS allocations on the facility, hence the importance of this work goes beyond merely the initial CPU cycles gained. In this paper, we give an overview and compare the performance, development effort, flexibility and robustness of the various approaches.

PD2P: PanDA Dynamic Data Placement for ATLAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maeno, T.; De, K.; Panitkin, S.

2012-12-13

The PanDA (Production and Distributed Analysis) system plays a key role in the ATLAS distributed computing infrastructure. PanDA is the ATLAS workload management system for processing all Monte-Carlo (MC) simulation and data reprocessing jobs in addition to user and group analysis jobs. The PanDA Dynamic Data Placement (PD2P) system has been developed to cope with difficulties of data placement for ATLAS. We will describe the design of the new system, its performance during the past year of data taking, dramatic improvements it has brought about in the efficient use of storage and processing resources, and plans for the future.

Computing shifts to monitor ATLAS distributed computing infrastructure and operations

NASA Astrophysics Data System (ADS)

Adam, C.; Barberis, D.; Crépé-Renaudin, S.; De, K.; Fassi, F.; Stradling, A.; Svatos, M.; Vartapetian, A.; Wolters, H.

2017-10-01

The ATLAS Distributed Computing (ADC) group established a new Computing Run Coordinator (CRC) shift at the start of LHC Run 2 in 2015. The main goal was to rely on a person with a good overview of the ADC activities to ease the ADC experts’ workload. The CRC shifter keeps track of ADC tasks related to their fields of expertise and responsibility. At the same time, the shifter maintains a global view of the day-to-day operations of the ADC system. During Run 1, this task was accomplished by a person of the expert team called the ADC Manager on Duty (AMOD), a position that was removed during the shutdown period due to the reduced number and availability of ADC experts foreseen for Run 2. The CRC position was proposed to cover some of the AMODs former functions, while allowing more people involved in computing to participate. In this way, CRC shifters help with the training of future ADC experts. The CRC shifters coordinate daily ADC shift operations, including tracking open issues, reporting, and representing ADC in relevant meetings. The CRC also facilitates communication between the ADC experts team and the other ADC shifters. These include the Distributed Analysis Support Team (DAST), which is the first point of contact for addressing all distributed analysis questions, and the ATLAS Distributed Computing Shifters (ADCoS), which check and report problems in central services, sites, Tier-0 export, data transfers and production tasks. Finally, the CRC looks at the level of ADC activities on a weekly or monthly timescale to ensure that ADC resources are used efficiently.

PanDA: Exascale Federation of Resources for the ATLAS Experiment at the LHC

NASA Astrophysics Data System (ADS)

Barreiro Megino, Fernando; Caballero Bejar, Jose; De, Kaushik; Hover, John; Klimentov, Alexei; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Padolski, Siarhei; Panitkin, Sergey; Petrosyan, Artem; Wenaus, Torre

2016-02-01

After a scheduled maintenance and upgrade period, the world's largest and most powerful machine - the Large Hadron Collider(LHC) - is about to enter its second run at unprecedented energies. In order to exploit the scientific potential of the machine, the experiments at the LHC face computational challenges with enormous data volumes that need to be analysed by thousand of physics users and compared to simulated data. Given diverse funding constraints, the computational resources for the LHC have been deployed in a worldwide mesh of data centres, connected to each other through Grid technologies. The PanDA (Production and Distributed Analysis) system was developed in 2005 for the ATLAS experiment on top of this heterogeneous infrastructure to seamlessly integrate the computational resources and give the users the feeling of a unique system. Since its origins, PanDA has evolved together with upcoming computing paradigms in and outside HEP, such as changes in the networking model, Cloud Computing and HPC. It is currently running steadily up to 200 thousand simultaneous cores (limited by the available resources for ATLAS), up to two million aggregated jobs per day and processes over an exabyte of data per year. The success of PanDA in ATLAS is triggering the widespread adoption and testing by other experiments. In this contribution we will give an overview of the PanDA components and focus on the new features and upcoming challenges that are relevant to the next decade of distributed computing workload management using PanDA.

A multipurpose computing center with distributed resources

NASA Astrophysics Data System (ADS)

Chudoba, J.; Adam, M.; Adamová, D.; Kouba, T.; Mikula, A.; Říkal, V.; Švec, J.; Uhlířová, J.; Vokáč, P.; Svatoš, M.

2017-10-01

The Computing Center of the Institute of Physics (CC IoP) of the Czech Academy of Sciences serves a broad spectrum of users with various computing needs. It runs WLCG Tier-2 center for the ALICE and the ATLAS experiments; the same group of services is used by astroparticle physics projects the Pierre Auger Observatory (PAO) and the Cherenkov Telescope Array (CTA). OSG stack is installed for the NOvA experiment. Other groups of users use directly local batch system. Storage capacity is distributed to several locations. DPM servers used by the ATLAS and the PAO are all in the same server room, but several xrootd servers for the ALICE experiment are operated in the Nuclear Physics Institute in Řež, about 10 km away. The storage capacity for the ATLAS and the PAO is extended by resources of the CESNET - the Czech National Grid Initiative representative. Those resources are in Plzen and Jihlava, more than 100 km away from the CC IoP. Both distant sites use a hierarchical storage solution based on disks and tapes. They installed one common dCache instance, which is published in the CC IoP BDII. ATLAS users can use these resources using the standard ATLAS tools in the same way as the local storage without noticing this geographical distribution. Computing clusters LUNA and EXMAG dedicated to users mostly from the Solid State Physics departments offer resources for parallel computing. They are part of the Czech NGI infrastructure MetaCentrum with distributed batch system based on torque with a custom scheduler. Clusters are installed remotely by the MetaCentrum team and a local contact helps only when needed. Users from IoP have exclusive access only to a part of these two clusters and take advantage of higher priorities on the rest (1500 cores in total), which can also be used by any user of the MetaCentrum. IoP researchers can also use distant resources located in several towns of the Czech Republic with a capacity of more than 12000 cores in total.

Automating usability of ATLAS Distributed Computing resources

NASA Astrophysics Data System (ADS)

Tupputi, S. A.; Di Girolamo, A.; Kouba, T.; Schovancová, J.; Atlas Collaboration

2014-06-01

The automation of ATLAS Distributed Computing (ADC) operations is essential to reduce manpower costs and allow performance-enhancing actions, which improve the reliability of the system. In this perspective a crucial case is the automatic handling of outages of ATLAS computing sites storage resources, which are continuously exploited at the edge of their capabilities. It is challenging to adopt unambiguous decision criteria for storage resources of non-homogeneous types, sizes and roles. The recently developed Storage Area Automatic Blacklisting (SAAB) tool has provided a suitable solution, by employing an inference algorithm which processes history of storage monitoring tests outcome. SAAB accomplishes both the tasks of providing global monitoring as well as automatic operations on single sites. The implementation of the SAAB tool has been the first step in a comprehensive review of the storage areas monitoring and central management at all levels. Such review has involved the reordering and optimization of SAM tests deployment and the inclusion of SAAB results in the ATLAS Site Status Board with both dedicated metrics and views. The resulting structure allows monitoring the storage resources status with fine time-granularity and automatic actions to be taken in foreseen cases, like automatic outage handling and notifications to sites. Hence, the human actions are restricted to reporting and following up problems, where and when needed. In this work we show SAAB working principles and features. We present also the decrease of human interactions achieved within the ATLAS Computing Operation team. The automation results in a prompt reaction to failures, which leads to the optimization of resource exploitation.

Development, deployment and operations of ATLAS databases

NASA Astrophysics Data System (ADS)

Vaniachine, A. V.; Schmitt, J. G. v. d.

2008-07-01

In preparation for ATLAS data taking, a coordinated shift from development towards operations has occurred in ATLAS database activities. In addition to development and commissioning activities in databases, ATLAS is active in the development and deployment (in collaboration with the WLCG 3D project) of the tools that allow the worldwide distribution and installation of databases and related datasets, as well as the actual operation of this system on ATLAS multi-grid infrastructure. We describe development and commissioning of major ATLAS database applications for online and offline. We present the first scalability test results and ramp-up schedule over the initial LHC years of operations towards the nominal year of ATLAS running, when the database storage volumes are expected to reach 6.1 TB for the Tag DB and 1.0 TB for the Conditions DB. ATLAS database applications require robust operational infrastructure for data replication between online and offline at Tier-0, and for the distribution of the offline data to Tier-1 and Tier-2 computing centers. We describe ATLAS experience with Oracle Streams and other technologies for coordinated replication of databases in the framework of the WLCG 3D services.

Evolution of user analysis on the grid in ATLAS

NASA Astrophysics Data System (ADS)

Dewhurst, A.; Legger, F.; ATLAS Collaboration

2017-10-01

More than one thousand physicists analyse data collected by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN through 150 computing facilities around the world. Efficient distributed analysis requires optimal resource usage and the interplay of several factors: robust grid and software infrastructures, and system capability to adapt to different workloads. The continuous automatic validation of grid sites and the user support provided by a dedicated team of expert shifters have been proven to provide a solid distributed analysis system for ATLAS users. Typical user workflows on the grid, and their associated metrics, are discussed. Measurements of user job performance and typical requirements are also shown.

Improving ATLAS grid site reliability with functional tests using HammerCloud

NASA Astrophysics Data System (ADS)

Elmsheuser, Johannes; Legger, Federica; Medrano Llamas, Ramon; Sciacca, Gianfranco; van der Ster, Dan

2012-12-01

With the exponential growth of LHC (Large Hadron Collider) data in 2011, and more coming in 2012, distributed computing has become the established way to analyse collider data. The ATLAS grid infrastructure includes almost 100 sites worldwide, ranging from large national computing centers to smaller university clusters. These facilities are used for data reconstruction and simulation, which are centrally managed by the ATLAS production system, and for distributed user analysis. To ensure the smooth operation of such a complex system, regular tests of all sites are necessary to validate the site capability of successfully executing user and production jobs. We report on the development, optimization and results of an automated functional testing suite using the HammerCloud framework. Functional tests are short lightweight applications covering typical user analysis and production schemes, which are periodically submitted to all ATLAS grid sites. Results from those tests are collected and used to evaluate site performances. Sites that fail or are unable to run the tests are automatically excluded from the PanDA brokerage system, therefore avoiding user or production jobs to be sent to problematic sites.

Integration of the Chinese HPC Grid in ATLAS Distributed Computing

NASA Astrophysics Data System (ADS)

Filipčič, A.; ATLAS Collaboration

2017-10-01

Fifteen Chinese High-Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC-CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC-CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC-CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte Carlo Simulation in SCEAPI and have been providing CPU power since fall 2015.

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

NASA Astrophysics Data System (ADS)

Klimentov, A.; Buncic, P.; De, K.; Jha, S.; Maeno, T.; Mount, R.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Porter, R. J.; Read, K. F.; Vaniachine, A.; Wells, J. C.; Wenaus, T.

2015-05-01

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(102) sites, O(105) cores, O(108) jobs per year, O(103) users, and ATLAS data volume is O(1017) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled ‘Next Generation Workload Management and Analysis System for Big Data’ (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. We will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.

Documentation for the machine-readable version of the Stellar Spectrophotometric Atlas, 3130 A lambda 10800 A of Gunn and Stryker (1983)

NASA Technical Reports Server (NTRS)

Warren, W. H., Jr.

1984-01-01

The machine-readable version of the Atlas as it is currently being distributed from the Astronomical Data Center is described. The data were obtained with the Oke multichannel scanner on the 5-meter Hale reflector for purposes of synthesizing galaxy spectra, and the digitized Atlas contains normalized spectral energy distributions, computed colors, scan line and continuum indices for 175 selected stars covering the complete ranges of spectral type and luminosity class. The documentation includes a byte-by-byte format description, a table of the indigenous characteristics of the magnetic tape file, and a sample listing of logical records exactly as they are recorded on the tape.

Networks in ATLAS

NASA Astrophysics Data System (ADS)

McKee, Shawn; ATLAS Collaboration

2017-10-01

Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

Advanced technologies for scalable ATLAS conditions database access on the grid

NASA Astrophysics Data System (ADS)

Basset, R.; Canali, L.; Dimitrov, G.; Girone, M.; Hawkings, R.; Nevski, P.; Valassi, A.; Vaniachine, A.; Viegas, F.; Walker, R.; Wong, A.

2010-04-01

During massive data reprocessing operations an ATLAS Conditions Database application must support concurrent access from numerous ATLAS data processing jobs running on the Grid. By simulating realistic work-flow, ATLAS database scalability tests provided feedback for Conditions Db software optimization and allowed precise determination of required distributed database resources. In distributed data processing one must take into account the chaotic nature of Grid computing characterized by peak loads, which can be much higher than average access rates. To validate database performance at peak loads, we tested database scalability at very high concurrent jobs rates. This has been achieved through coordinated database stress tests performed in series of ATLAS reprocessing exercises at the Tier-1 sites. The goal of database stress tests is to detect scalability limits of the hardware deployed at the Tier-1 sites, so that the server overload conditions can be safely avoided in a production environment. Our analysis of server performance under stress tests indicates that Conditions Db data access is limited by the disk I/O throughput. An unacceptable side-effect of the disk I/O saturation is a degradation of the WLCG 3D Services that update Conditions Db data at all ten ATLAS Tier-1 sites using the technology of Oracle Streams. To avoid such bottlenecks we prototyped and tested a novel approach for database peak load avoidance in Grid computing. Our approach is based upon the proven idea of pilot job submission on the Grid: instead of the actual query, an ATLAS utility library sends to the database server a pilot query first.

Job optimization in ATLAS TAG-based distributed analysis

NASA Astrophysics Data System (ADS)

Mambelli, M.; Cranshaw, J.; Gardner, R.; Maeno, T.; Malon, D.; Novak, M.

2010-04-01

The ATLAS experiment is projected to collect over one billion events/year during the first few years of operation. The efficient selection of events for various physics analyses across all appropriate samples presents a significant technical challenge. ATLAS computing infrastructure leverages the Grid to tackle the analysis across large samples by organizing data into a hierarchical structure and exploiting distributed computing to churn through the computations. This includes events at different stages of processing: RAW, ESD (Event Summary Data), AOD (Analysis Object Data), DPD (Derived Physics Data). Event Level Metadata Tags (TAGs) contain information about each event stored using multiple technologies accessible by POOL and various web services. This allows users to apply selection cuts on quantities of interest across the entire sample to compile a subset of events that are appropriate for their analysis. This paper describes new methods for organizing jobs using the TAGs criteria to analyze ATLAS data. It further compares different access patterns to the event data and explores ways to partition the workload for event selection and analysis. Here analysis is defined as a broader set of event processing tasks including event selection and reduction operations ("skimming", "slimming" and "thinning") as well as DPD making. Specifically it compares analysis with direct access to the events (AOD and ESD data) to access mediated by different TAG-based event selections. We then compare different ways of splitting the processing to maximize performance.

ATLAS Eventlndex monitoring system using the Kibana analytics and visualization platform

NASA Astrophysics Data System (ADS)

Barberis, D.; Cárdenas Zárate, S. E.; Favareto, A.; Fernandez Casani, A.; Gallas, E. J.; Garcia Montoro, C.; Gonzalez de la Hoz, S.; Hrivnac, J.; Malon, D.; Prokoshin, F.; Salt, J.; Sanchez, J.; Toebbicke, R.; Yuan, R.; ATLAS Collaboration

2016-10-01

The ATLAS EventIndex is a data catalogue system that stores event-related metadata for all (real and simulated) ATLAS events, on all processing stages. As it consists of different components that depend on other applications (such as distributed storage, and different sources of information) we need to monitor the conditions of many heterogeneous subsystems, to make sure everything is working correctly. This paper describes how we gather information about the EventIndex components and related subsystems: the Producer-Consumer architecture for data collection, health parameters from the servers that run EventIndex components, EventIndex web interface status, and the Hadoop infrastructure that stores EventIndex data. This information is collected, processed, and then displayed using CERN service monitoring software based on the Kibana analytic and visualization package, provided by CERN IT Department. EventIndex monitoring is used both by the EventIndex team and ATLAS Distributed Computing shifts crew.

High-Performance Scalable Information Service for the ATLAS Experiment

NASA Astrophysics Data System (ADS)

Kolos, S.; Boutsioukis, G.; Hauser, R.

2012-12-01

The ATLAS[1] experiment is operated by a highly distributed computing system which is constantly producing a lot of status information which is used to monitor the experiment operational conditions as well as to assess the quality of the physics data being taken. For example the ATLAS High Level Trigger(HLT) algorithms are executed on the online computing farm consisting from about 1500 nodes. Each HLT algorithm is producing few thousands histograms, which have to be integrated over the whole farm and carefully analyzed in order to properly tune the event rejection. In order to handle such non-physics data the Information Service (IS) facility has been developed in the scope of the ATLAS Trigger and Data Acquisition (TDAQ)[2] project. The IS provides a high-performance scalable solution for information exchange in distributed environment. In the course of an ATLAS data taking session the IS handles about a hundred gigabytes of information which is being constantly updated with the update interval varying from a second to a few tens of seconds. IS provides access to any information item on request as well as distributing notification to all the information subscribers. In the latter case IS subscribers receive information within a few milliseconds after it was updated. IS can handle arbitrary types of information, including histograms produced by the HLT applications, and provides C++, Java and Python API. The Information Service is a unique source of information for the majority of the online monitoring analysis and GUI applications used to control and monitor the ATLAS experiment. Information Service provides streaming functionality allowing efficient replication of all or part of the managed information. This functionality is used to duplicate the subset of the ATLAS monitoring data to the CERN public network with a latency of a few milliseconds, allowing efficient real-time monitoring of the data taking from outside the protected ATLAS network. Each information item in IS has an associated URL which can be used to access that item online via HTTP protocol. This functionality is being used by many online monitoring applications which can run in a WEB browser, providing real-time monitoring information about the ATLAS experiment over the globe. This paper describes the design and implementation of the IS and presents performance results which have been taken in the ATLAS operational environment.

C3PO - A Dynamic Data Placement Agent for ATLAS Distributed Data Management

NASA Astrophysics Data System (ADS)

Beermann, T.; Lassnig, M.; Barisits, M.; Serfon, C.; Garonne, V.; ATLAS Collaboration

2017-10-01

This paper introduces a new dynamic data placement agent for the ATLAS distributed data management system. This agent is designed to pre-place potentially popular data to make it more widely available. It therefore incorporates information from a variety of sources. Those include input datasets and sites workload information from the ATLAS workload management system, network metrics from different sources like FTS and PerfSonar, historical popularity data collected through a tracer mechanism and more. With this data it decides if, when and where to place new replicas that then can be used by the WMS to distribute the workload more evenly over available computing resources and then ultimately reduce job waiting times. This paper gives an overview of the architecture and the final implementation of this new agent. The paper also includes an evaluation of the placement algorithm by comparing the transfer times and the new replica usage.

Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Purdie, Thomas G.

2017-01-01

Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to be used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mean absolute difference in all DVHs for the clinical and predicted dose distribution. The results on average are favorable in comparison to our previous approach (1.91 versus 2.57). Comparing our method with and without atlas-selection further validates that atlas-selection improved dose prediction on average in whole breast (0.64 versus 1.59), prostate (2.13 versus 4.07), and rectum (1.46 versus 3.29) while it is less important in breast cavity (0.79 versus 0.92) and lung (1.33 versus 1.27) for which there is high conformity and minimal dose shaping. In CNS brain, atlas-selection has the potential to be impactful (3.65 versus 5.09), but selecting the ideal atlas is the most challenging.

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

DOE PAGES

Klimentov, A.; Buncic, P.; De, K.; ...

2015-05-22

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2) sites, O(10 5) cores, O(10 8) jobs per year, O(10 3) users, and ATLAS data volume is O(10 17) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.« less

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klimentov, A.; Buncic, P.; De, K.

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2) sites, O(10 5) cores, O(10 8) jobs per year, O(10 3) users, and ATLAS data volume is O(10 17) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.« less

Dashboard Task Monitor for Managing ATLAS User Analysis on the Grid

NASA Astrophysics Data System (ADS)

Sargsyan, L.; Andreeva, J.; Jha, M.; Karavakis, E.; Kokoszkiewicz, L.; Saiz, P.; Schovancova, J.; Tuckett, D.; Atlas Collaboration

2014-06-01

The organization of the distributed user analysis on the Worldwide LHC Computing Grid (WLCG) infrastructure is one of the most challenging tasks among the computing activities at the Large Hadron Collider. The Experiment Dashboard offers a solution that not only monitors but also manages (kill, resubmit) user tasks and jobs via a web interface. The ATLAS Dashboard Task Monitor provides analysis users with a tool that is independent of the operating system and Grid environment. This contribution describes the functionality of the application and its implementation details, in particular authentication, authorization and audit of the management operations.

MRI-based treatment planning with pseudo CT generated through atlas registration.

PubMed

Uh, Jinsoo; Merchant, Thomas E; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-05-01

To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787-0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%-98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs.

MRI-based treatment planning with pseudo CT generated through atlas registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uh, Jinsoo, E-mail: jinsoo.uh@stjude.org; Merchant, Thomas E.; Hua, Chiaho

2014-05-15

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration ofmore » conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. Conclusions: MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs.« less

MRI-based treatment planning with pseudo CT generated through atlas registration

PubMed Central

Uh, Jinsoo; Merchant, Thomas E.; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-01-01

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. Conclusions: MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs. PMID:24784377

Computational and mathematical methods in brain atlasing.

PubMed

Nowinski, Wieslaw L

2017-12-01

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

The ATLAS Production System Evolution: New Data Processing and Analysis Paradigm for the LHC Run2 and High-Luminosity

NASA Astrophysics Data System (ADS)

Barreiro, F. H.; Borodin, M.; De, K.; Golubkov, D.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Padolski, S.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The second generation of the ATLAS Production System called ProdSys2 is a distributed workload manager that runs daily hundreds of thousands of jobs, from dozens of different ATLAS specific workflows, across more than hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based on many criteria, such as input and output size, memory requirements and CPU consumption, with manageable scheduling policies and by supporting different kind of computational resources, such as GRID, clouds, supercomputers and volunteer-computers. The system dynamically assigns a group of jobs (task) to a group of geographically distributed computing resources. Dynamic assignment and resources utilization is one of the major features of the system, it didn’t exist in the earliest versions of the production system where Grid resources topology was predefined using national or/and geographical pattern. Production System has a sophisticated job fault-recovery mechanism, which efficiently allows to run multi-Terabyte tasks without human intervention. We have implemented “train” model and open-ended production which allow to submit tasks automatically as soon as new set of data is available and to chain physics groups data processing and analysis with central production by the experiment. We present an overview of the ATLAS Production System and its major components features and architecture: task definition, web user interface and monitoring. We describe the important design decisions and lessons learned from an operational experience during the first year of LHC Run2. We also report the performance of the designed system and how various workflows, such as data (re)processing, Monte-Carlo and physics group production, users analysis, are scheduled and executed within one production system on heterogeneous computing resources.

Evolution of the ATLAS Nightly Build System

NASA Astrophysics Data System (ADS)

Undrus, A.

2012-12-01

The ATLAS Nightly Build System is a major component in the ATLAS collaborative software organization, validation, and code approval scheme. For over 10 years of development it has evolved into a factory for automatic release production and grid distribution. The 50 multi-platform branches of ATLAS releases provide vast opportunities for testing new packages, verification of patches to existing software, and migration to new platforms and compilers for ATLAS code that currently contains 2200 packages with 4 million C++ and 1.4 million python scripting lines written by about 1000 developers. Recent development was focused on the integration of ATLAS Nightly Build and Installation systems. The nightly releases are distributed and validated and some are transformed into stable releases used for data processing worldwide. The ATLAS Nightly System is managed by the NICOS control tool on a computing farm with 50 powerful multiprocessor nodes. NICOS provides the fully automated framework for the release builds, testing, and creation of distribution kits. The ATN testing framework of the Nightly System runs unit and integration tests in parallel suites, fully utilizing the resources of multi-core machines, and provides the first results even before compilations complete. The NICOS error detection system is based on several techniques and classifies the compilation and test errors according to their severity. It is periodically tuned to place greater emphasis on certain software defects by highlighting the problems on NICOS web pages and sending automatic e-mail notifications to responsible developers. These and other recent developments will be presented and future plans will be described.

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

De, K; Jha, S; Klimentov, A

2016-01-01

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Managementmore » System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), MIRA supercomputer at Argonne Leadership Computing Facilities (ALCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full production for the ATLAS experiment since September 2015. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.« less

PanDA for ATLAS distributed computing in the next decade

NASA Astrophysics Data System (ADS)

Barreiro Megino, F. H.; De, K.; Klimentov, A.; Maeno, T.; Nilsson, P.; Oleynik, D.; Padolski, S.; Panitkin, S.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The Production and Distributed Analysis (PanDA) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider (LHC) data processing scale. Heterogeneous resources used by the ATLAS experiment are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, dozens of scientific applications are supported, while data processing requires more than a few billion hours of computing usage per year. PanDA performed very well over the last decade including the LHC Run 1 data taking period. However, it was decided to upgrade the whole system concurrently with the LHC’s first long shutdown in order to cope with rapidly changing computing infrastructure. After two years of reengineering efforts, PanDA has embedded capabilities for fully dynamic and flexible workload management. The static batch job paradigm was discarded in favor of a more automated and scalable model. Workloads are dynamically tailored for optimal usage of resources, with the brokerage taking network traffic and forecasts into account. Computing resources are partitioned based on dynamic knowledge of their status and characteristics. The pilot has been re-factored around a plugin structure for easier development and deployment. Bookkeeping is handled with both coarse and fine granularities for efficient utilization of pledged or opportunistic resources. An in-house security mechanism authenticates the pilot and data management services in off-grid environments such as volunteer computing and private local clusters. The PanDA monitor has been extensively optimized for performance and extended with analytics to provide aggregated summaries of the system as well as drill-down to operational details. There are as well many other challenges planned or recently implemented, and adoption by non-LHC experiments such as bioinformatics groups successfully running Paleomix (microbial genome and metagenomes) payload on supercomputers. In this paper we will focus on the new and planned features that are most important to the next decade of distributed computing workload management.

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

NASA Astrophysics Data System (ADS)

Klimentov, A.; De, K.; Jha, S.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Wells, J.; Wenaus, T.

2016-10-01

The.LHC, operating at CERN, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than grid can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility. Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full pro duction for the ATLAS since September 2015. We will present our current accomplishments with running PanDA at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

BNL ATLAS Grid Computing

ScienceCinema

Michael Ernst

2017-12-09

As the sole Tier-1 computing facility for ATLAS in the United States and the largest ATLAS computing center worldwide Brookhaven provides a large portion of the overall computing resources for U.S. collaborators and serves as the central hub for storing,

Atlasmaker: A Grid-based Implementation of the Hyperatlas

NASA Astrophysics Data System (ADS)

Williams, R.; Djorgovski, S. G.; Feldmann, M. T.; Jacob, J.

2004-07-01

The Atlasmaker project is using Grid technology, in combination with NVO interoperability, to create new knowledge resources in astronomy. The product is a multi-faceted, multi-dimensional, scientifically trusted image atlas of the sky, made by federating many different surveys at different wavelengths, times, resolutions, polarizations, etc. The Atlasmaker software does resampling and mosaicking of image collections, and is well-suited to operate with the Hyperatlas standard. Requests can be satisfied via on-demand computations or by accessing a data cache. Computed data is stored in a distributed virtual file system, such as the Storage Resource Broker (SRB). We expect these atlases to be a new and powerful paradigm for knowledge extraction in astronomy, as well as a magnificent way to build educational resources. The system is being incorporated into the data analysis pipeline of the Palomar-Quest synoptic survey, and is being used to generate all-sky atlases from the 2MASS, SDSS, and DPOSS surveys for joint object detection.

ATLAS@Home: Harnessing Volunteer Computing for HEP

NASA Astrophysics Data System (ADS)

Adam-Bourdarios, C.; Cameron, D.; Filipčič, A.; Lancon, E.; Wu, W.; ATLAS Collaboration

2015-12-01

A recent common theme among HEP computing is exploitation of opportunistic resources in order to provide the maximum statistics possible for Monte Carlo simulation. Volunteer computing has been used over the last few years in many other scientific fields and by CERN itself to run simulations of the LHC beams. The ATLAS@Home project was started to allow volunteers to run simulations of collisions in the ATLAS detector. So far many thousands of members of the public have signed up to contribute their spare CPU cycles for ATLAS, and there is potential for volunteer computing to provide a significant fraction of ATLAS computing resources. Here we describe the design of the project, the lessons learned so far and the future plans.

HEP Computing Tools, Grid and Supercomputers for Genome Sequencing Studies

NASA Astrophysics Data System (ADS)

De, K.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Novikov, A.; Poyda, A.; Tertychnyy, I.; Wenaus, T.

2017-10-01

PanDA - Production and Distributed Analysis Workload Management System has been developed to address ATLAS experiment at LHC data processing and analysis challenges. Recently PanDA has been extended to run HEP scientific applications on Leadership Class Facilities and supercomputers. The success of the projects to use PanDA beyond HEP and Grid has drawn attention from other compute intensive sciences such as bioinformatics. Recent advances of Next Generation Genome Sequencing (NGS) technology led to increasing streams of sequencing data that need to be processed, analysed and made available for bioinformaticians worldwide. Analysis of genomes sequencing data using popular software pipeline PALEOMIX can take a month even running it on the powerful computer resource. In this paper we will describe the adaptation the PALEOMIX pipeline to run it on a distributed computing environment powered by PanDA. To run pipeline we split input files into chunks which are run separately on different nodes as separate inputs for PALEOMIX and finally merge output file, it is very similar to what it done by ATLAS to process and to simulate data. We dramatically decreased the total walltime because of jobs (re)submission automation and brokering within PanDA. Using software tools developed initially for HEP and Grid can reduce payload execution time for Mammoths DNA samples from weeks to days.

ATLAS@AWS

NASA Astrophysics Data System (ADS)

Gehrcke, Jan-Philip; Kluth, Stefan; Stonjek, Stefan

2010-04-01

We show how the ATLAS offline software is ported on the Amazon Elastic Compute Cloud (EC2). We prepare an Amazon Machine Image (AMI) on the basis of the standard ATLAS platform Scientific Linux 4 (SL4). Then an instance of the SLC4 AMI is started on EC2 and we install and validate a recent release of the ATLAS offline software distribution kit. The installed software is archived as an image on the Amazon Simple Storage Service (S3) and can be quickly retrieved and connected to new SL4 AMI instances using the Amazon Elastic Block Store (EBS). ATLAS jobs can then configure against the release kit using the ATLAS configuration management tool (cmt) in the standard way. The output of jobs is exported to S3 before the SL4 AMI is terminated. Job status information is transferred to the Amazon SimpleDB service. The whole process of launching instances of our AMI, starting, monitoring and stopping jobs and retrieving job output from S3 is controlled from a client machine using python scripts implementing the Amazon EC2/S3 API via the boto library working together with small scripts embedded in the SL4 AMI. We report our experience with setting up and operating the system using standard ATLAS job transforms.

The ATLAS Eventlndex: data flow and inclusion of other metadata

NASA Astrophysics Data System (ADS)

Barberis, D.; Cárdenas Zárate, S. E.; Favareto, A.; Fernandez Casani, A.; Gallas, E. J.; Garcia Montoro, C.; Gonzalez de la Hoz, S.; Hrivnac, J.; Malon, D.; Prokoshin, F.; Salt, J.; Sanchez, J.; Toebbicke, R.; Yuan, R.; ATLAS Collaboration

2016-10-01

The ATLAS EventIndex is the catalogue of the event-related metadata for the information collected from the ATLAS detector. The basic unit of this information is the event record, containing the event identification parameters, pointers to the files containing this event as well as trigger decision information. The main use case for the EventIndex is event picking, as well as data consistency checks for large production campaigns. The EventIndex employs the Hadoop platform for data storage and handling, as well as a messaging system for the collection of information. The information for the EventIndex is collected both at Tier-0, when the data are first produced, and from the Grid, when various types of derived data are produced. The EventIndex uses various types of auxiliary information from other ATLAS sources for data collection and processing: trigger tables from the condition metadata database (COMA), dataset information from the data catalogue AMI and the Rucio data management system and information on production jobs from the ATLAS production system. The ATLAS production system is also used for the collection of event information from the Grid jobs. EventIndex developments started in 2012 and in the middle of 2015 the system was commissioned and started collecting event metadata, as a part of ATLAS Distributed Computing operations.

Two-stage atlas subset selection in multi-atlas based image segmentation.

PubMed

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.

Volunteer Computing Experience with ATLAS@Home

NASA Astrophysics Data System (ADS)

Adam-Bourdarios, C.; Bianchi, R.; Cameron, D.; Filipčič, A.; Isacchini, G.; Lançon, E.; Wu, W.; ATLAS Collaboration

2017-10-01

ATLAS@Home is a volunteer computing project which allows the public to contribute to computing for the ATLAS experiment through their home or office computers. The project has grown continuously since its creation in mid-2014 and now counts almost 100,000 volunteers. The combined volunteers’ resources make up a sizeable fraction of overall resources for ATLAS simulation. This paper takes stock of the experience gained so far and describes the next steps in the evolution of the project. These improvements include running natively on Linux to ease the deployment on for example university clusters, using multiple cores inside one task to reduce the memory requirements and running different types of workload such as event generation. In addition to technical details the success of ATLAS@Home as an outreach tool is evaluated.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

Development, Validation and Integration of the ATLAS Trigger System Software in Run 2

NASA Astrophysics Data System (ADS)

Keyes, Robert; ATLAS Collaboration

2017-10-01

The trigger system of the ATLAS detector at the LHC is a combination of hardware, firmware, and software, associated to various sub-detectors that must seamlessly cooperate in order to select one collision of interest out of every 40,000 delivered by the LHC every millisecond. These proceedings discuss the challenges, organization and work flow of the ongoing trigger software development, validation, and deployment. The goal of this development is to ensure that the most up-to-date algorithms are used to optimize the performance of the experiment. The goal of the validation is to ensure the reliability and predictability of the software performance. Integration tests are carried out to ensure that the software deployed to the online trigger farm during data-taking run as desired. Trigger software is validated by emulating online conditions using a benchmark run and mimicking the reconstruction that occurs during normal data-taking. This exercise is computationally demanding and thus runs on the ATLAS high performance computing grid with high priority. Performance metrics ranging from low-level memory and CPU requirements, to distributions and efficiencies of high-level physics quantities are visualized and validated by a range of experts. This is a multifaceted critical task that ties together many aspects of the experimental effort and thus directly influences the overall performance of the ATLAS experiment.

SU-F-T-405: Development of a Rapid Cardiac Contouring Tool Using Landmark-Driven Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pelletier, C; Jung, J; Mosher, E

2016-06-15

Purpose: This study aims to develop a tool to rapidly delineate cardiac substructures for use in dosimetry for large-scale clinical trial or epidemiological investigations. The goal is to produce a system that can semi-automatically delineate nine cardiac structures to a reasonable accuracy within a couple of minutes. Methods: The cardiac contouring tool employs a Most Similar Atlas method, where a selection criterion is used to pre-select the most similar model to the patient from a library of pre-defined atlases. Sixty contrast-enhanced cardiac computed tomography angiography (CTA) scans (30 male and 30 female) were manually contoured to serve as the atlasmore » library. For each CTA 12 structures were delineated. Kabsch algorithm was used to compute the optimum rotation and translation matrices between the patient and atlas. Minimum root mean squared distance between the patient and atlas after transformation was used to select the most-similar atlas. An initial study using 10 CTA sets was performed to assess system feasibility. Leave-one patient out method was performed, and fit criteria were calculated to evaluate the fit accuracy compared to manual contours. Results: For the pilot study, mean dice indices of .895 were achieved for the whole heart, .867 for the ventricles, and .802 for the atria. In addition, mean distance was measured via the chord length distribution (CLD) between ground truth and the atlas structures for the four coronary arteries. The mean CLD for all coronary arteries was below 14mm, with the left circumflex artery showing the best agreement (7.08mm). Conclusion: The cardiac contouring tool is able to delineate cardiac structures with reasonable accuracy in less than 90 seconds. Pilot data indicates that the system is able to delineate the whole heart and ventricles within a reasonable accuracy using even a limited library. We are extending the atlas sets to 60 adult males and females in total.« less

Two-stage atlas subset selection in multi-atlas based image segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stagemore » atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.« less

Atlas-derived perfusion correlates of white matter hyperintensities in patients with reduced cardiac output.

PubMed

Jefferson, Angela L; Holland, Christopher M; Tate, David F; Csapo, Istvan; Poppas, Athena; Cohen, Ronald A; Guttmann, Charles R G

2011-01-01

Reduced cardiac output is associated with increased white matter hyperintensities (WMH) and executive dysfunction in older adults, which may be secondary to relations between systemic and cerebral perfusion. This study preliminarily describes the regional distribution of cerebral WMH in the context of a normal cerebral perfusion atlas and aims to determine if these variables are associated with reduced cardiac output. Thirty-two participants (72 ± 8 years old, 38% female) with cardiovascular risk factors or disease underwent structural MRI acquisition at 1.5T using a standard imaging protocol that included FLAIR sequences. WMH distribution was examined in common anatomical space using voxel-based morphometry and as a function of normal cerebral perfusion patterns by overlaying a single photon emission computed tomography (SPECT) atlas. Doppler echocardiogram data was used to dichotomize the participants on the basis of low (n=9) and normal (n=23) cardiac output. Global WMH count and volume did not differ between the low and normal cardiac output groups; however, atlas-derived SPECT perfusion values in regions of hyperintensities were reduced in the low versus normal cardiac output group (p<0.001). Our preliminary data suggest that participants with low cardiac output have WMH in regions of relatively reduced perfusion, while normal cardiac output participants have WMH in regions with relatively higher regional perfusion. This spatial perfusion distribution difference for areas of WMH may occur in the context of reduced systemic perfusion, which subsequently impacts cerebral perfusion and contributes to subclinical or clinical microvascular damage. Copyright © 2009 Elsevier Inc. All rights reserved.

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

PubMed

Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

2014-01-01

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.

TU-AB-BRA-02: An Efficient Atlas-Based Synthetic CT Generation Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, X

2016-06-15

Purpose: A major obstacle for MR-only radiotherapy is the need to generate an accurate synthetic CT (sCT) from MR image(s) of a patient for the purposes of dose calculation and DRR generation. We propose here an accurate and efficient atlas-based sCT generation method, which has a computation speed largely independent of the number of atlases used. Methods: Atlas-based sCT generation requires a set of atlases with co-registered CT and MR images. Unlike existing methods that align each atlas to the new patient independently, we first create an average atlas and pre-align every atlas to the average atlas space. When amore » new patient arrives, we compute only one deformable image registration to align the patient MR image to the average atlas, which indirectly aligns the patient to all pre-aligned atlases. A patch-based non-local weighted fusion is performed in the average atlas space to generate the sCT for the patient, which is then warped back to the original patient space. We further adapt a PatchMatch algorithm that can quickly find top matches between patches of the patient image and all atlas images, which makes the patch fusion step also independent of the number of atlases used. Results: Nineteen brain tumour patients with both CT and T1-weighted MR images are used as testing data and a leave-one-out validation is performed. Each sCT generated is compared against the original CT image of the same patient on a voxel-by-voxel basis. The proposed method produces a mean absolute error (MAE) of 98.6±26.9 HU overall. The accuracy is comparable with a conventional implementation scheme, but the computation time is reduced from over an hour to four minutes. Conclusion: An average atlas space patch fusion approach can produce highly accurate sCT estimations very efficiently. Further validation on dose computation accuracy and using a larger patient cohort is warranted. The author is a full time employee of Elekta, Inc.« less

Research on Spectroscopy, Opacity, and Atmospheres

NASA Technical Reports Server (NTRS)

Kurucz, Robert L.; West, Donald (Technical Monitor)

2001-01-01

With this funding I produced a web site kurucz.harvard.edu that can also be accessed by FTP. it has a 73GB disk that holds all of my atomic and diatomic molecular data, my tables of distribution function opacities, my grids of model atmospheres, colors, fluxes, etc., my programs that are ready for distribution, and most of my recent papers. Atlases and computed spectra will be added as they are completed. New atomic and molecular calculations will be added as they are completed.

Brain transcriptome atlases: a computational perspective.

PubMed

Mahfouz, Ahmed; Huisman, Sjoerd M H; Lelieveldt, Boudewijn P F; Reinders, Marcel J T

2017-05-01

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

Distribution of Prostate Sentinel Nodes: A SPECT-Derived Anatomic Atlas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ganswindt, Ute, E-mail: ute.ganswindt@med.uni-muenchen.d; Schilling, David; Mueller, Arndt-Christian

2011-04-01

Purpose: The randomized Radiation Therapy Oncology Group 94-13 trial revealed that coverage of the pelvic lymph nodes in high-risk prostate cancer confers an advantage (progression-free survival and biochemical failure) in patients with {>=}15% risk of lymph node involvement. To facilitate an improved definition of the adjuvant target volume, precise knowledge regarding the location of the relevant lymph nodes is necessary. Therefore, we generated a three-dimensional sentinel lymph node atlas. Methods and Materials: In 61 patients with high-risk prostate cancer, a three-dimensional visualization of sentinel lymph nodes was performed using a single photon emission computed tomography system after transrectal intraprostatic injectionmore » of 150 to 362 (median 295) mega becquerel (MBq) {sup 99m}Technetium-nanocolloid (1.5-3h after injection) followed by an anatomic functional image fusion. Results: In all, 324 sentinel nodes in 59 of 61 patients (96.7%) were detected, with 0 to 13 nodes per patient (median 5, mean 5.3). The anatomic distribution of the sentinel nodes was as follows: external iliac 34.3%, internal iliac 17.9%, common iliac 12.7%, sacral 8.6%, perirectal 6.2%, left paraaortic 5.3%, right paraaortic 5.3%, seminal vesicle lymphatic plexus 3.1%, deep inguinal 1.5%, superior rectal 1.2%, internal pudendal 1.2%, perivesical 0.9%, inferior rectal 0.9%, retroaortic 0.3%, superficial inguinal 0.3%, and periprostatic 0.3%. Conclusions: The distribution of sentinel nodes as detected by single photon emission computed tomography imaging correlates well with the distribution determined by intraoperative gamma probe detection. A lower detection rate of sentinels in close proximity to the bladder and seminal vesicles is probably caused by the radionuclide accumulation in the bladder. In regard to intensity-modulated radiotherapy techniques, the presented anatomic atlas may allow optimized target volume definitions.« less

Integration of Panda Workload Management System with supercomputers

NASA Astrophysics Data System (ADS)

De, K.; Jha, S.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Nilsson, P.; Novikov, A.; Oleynik, D.; Panitkin, S.; Poyda, A.; Read, K. F.; Ryabinkin, E.; Teslyuk, A.; Velikhov, V.; Wells, J. C.; Wenaus, T.

2016-09-01

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), Supercomputer at the National Research Center "Kurchatov Institute", IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run singlethreaded workloads in parallel on Titan's multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accomplishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility's infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Integration of PanDA workload management system with Titan supercomputer at OLCF

NASA Astrophysics Data System (ADS)

De, K.; Klimentov, A.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Schovancova, J.; Vaniachine, A.; Wenaus, T.

2015-12-01

The PanDA (Production and Distributed Analysis) workload management system (WMS) was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. While PanDA currently distributes jobs to more than 100,000 cores at well over 100 Grid sites, the future LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). The current approach utilizes a modified PanDA pilot framework for job submission to Titan's batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on Titan's multicore worker nodes. It also gives PanDA new capability to collect, in real time, information about unused worker nodes on Titan, which allows precise definition of the size and duration of jobs submitted to Titan according to available free resources. This capability significantly reduces PanDA job wait time while improving Titan's utilization efficiency. This implementation was tested with a variety of Monte-Carlo workloads on Titan and is being tested on several other supercomputing platforms. Notice: This manuscript has been authored, by employees of Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. The publisher by accepting the manuscript for publication acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Data federation strategies for ATLAS using XRootD

NASA Astrophysics Data System (ADS)

Gardner, Robert; Campana, Simone; Duckeck, Guenter; Elmsheuser, Johannes; Hanushevsky, Andrew; Hönig, Friedrich G.; Iven, Jan; Legger, Federica; Vukotic, Ilija; Yang, Wei; Atlas Collaboration

2014-06-01

In the past year the ATLAS Collaboration accelerated its program to federate data storage resources using an architecture based on XRootD with its attendant redirection and storage integration services. The main goal of the federation is an improvement in the data access experience for the end user while allowing more efficient and intelligent use of computing resources. Along with these advances come integration with existing ATLAS production services (PanDA and its pilot services) and data management services (DQ2, and in the next generation, Rucio). Functional testing of the federation has been integrated into the standard ATLAS and WLCG monitoring frameworks and a dedicated set of tools provides high granularity information on its current and historical usage. We use a federation topology designed to search from the site's local storage outward to its region and to globally distributed storage resources. We describe programmatic testing of various federation access modes including direct access over the wide area network and staging of remote data files to local disk. To support job-brokering decisions, a time-dependent cost-of-data-access matrix is made taking into account network performance and key site performance factors. The system's response to production-scale physics analysis workloads, either from individual end-users or ATLAS analysis services, is discussed.

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

PubMed

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

An atlas of monthly mean distributions of GEOSAT sea surface height, SSMI surface wind speed, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1988

NASA Technical Reports Server (NTRS)

Halpern, D.; Zlotnicki, V.; Newman, J.; Brown, O.; Wentz, F.

1991-01-01

Monthly mean global distributions for 1988 are presented with a common color scale and geographical map. Distributions are included for sea surface height variation estimated from GEOSAT; surface wind speed estimated from the Special Sensor Microwave Imager on the Defense Meteorological Satellite Program spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer on NOAA spacecrafts; and the Cartesian components of the 10m height wind vector computed by the European Center for Medium Range Weather Forecasting. Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

A high-resolution atlas of composite Sloan Digital Sky Survey galaxy spectra

NASA Astrophysics Data System (ADS)

Dobos, László; Csabai, István.; Yip, Ching-Wa; Budavári, Tamás.; Wild, Vivienne; Szalay, Alexander S.

2012-02-01

In this work we present an atlas of composite spectra of galaxies based on the data of the Sloan Digital Sky Survey Data Release 7 (SDSS DR7). Galaxies are classified by colour, nuclear activity and star formation activity to calculate average spectra of high signal-to-noise ratio (S/N) and resolution (? at Δλ= 1 Å), using an algorithm that is robust against outliers. Besides composite spectra, we also compute the first five principal components of the distributions in each galaxy class to characterize the nature of variations of individual spectra around the averages. The continua of the composite spectra are fitted with BC03 stellar population synthesis models to extend the wavelength coverage beyond the coverage of the SDSS spectrographs. Common derived parameters of the composites are also calculated: integrated colours in the most popular filter systems, line-strength measurements and continuum absorption indices (including Lick indices). These derived parameters are compared with the distributions of parameters of individual galaxies, and it is shown on many examples that the composites of the atlas cover much of the parameter space spanned by SDSS galaxies. By co-adding thousands of spectra, a total integration time of several months can be reached, which results in extremely low noise composites. The variations in redshift not only allow for extending the spectral coverage bluewards to the original wavelength limit of the SDSS spectrographs, but also make higher spectral resolution achievable. The composite spectrum atlas is available online at .

A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.

PubMed

Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W

2005-01-01

We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.

Applications of advanced data analysis and expert system technologies in the ATLAS Trigger-DAQ Controls framework

NASA Astrophysics Data System (ADS)

Avolio, G.; Corso Radu, A.; Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-12-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment is a very complex distributed computing system, composed of more than 20000 applications running on more than 2000 computers. The TDAQ Controls system has to guarantee the smooth and synchronous operations of all the TDAQ components and has to provide the means to minimize the downtime of the system caused by runtime failures. During data taking runs, streams of information messages sent or published by running applications are the main sources of knowledge about correctness of running operations. The huge flow of operational monitoring data produced is constantly monitored by experts in order to detect problems or misbehaviours. Given the scale of the system and the rates of data to be analyzed, the automation of the system functionality in the areas of operational monitoring, system verification, error detection and recovery is a strong requirement. To accomplish its objective, the Controls system includes some high-level components which are based on advanced software technologies, namely the rule-based Expert System and the Complex Event Processing engines. The chosen techniques allow to formalize, store and reuse the knowledge of experts and thus to assist the shifters in the ATLAS control room during the data-taking activities.

Image database for digital hand atlas

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente; Dey, Partha S.; Gertych, Arkadiusz; Pospiech-Kurkowska, Sywia

2003-05-01

Bone age assessment is a procedure frequently performed in pediatric patients to evaluate their growth disorder. A commonly used method is atlas matching by a visual comparison of a hand radiograph with a small reference set of old Greulich-Pyle atlas. We have developed a new digital hand atlas with a large set of clinically normal hand images of diverse ethnic groups. In this paper, we will present our system design and implementation of the digital atlas database to support the computer-aided atlas matching for bone age assessment. The system consists of a hand atlas image database, a computer-aided diagnostic (CAD) software module for image processing and atlas matching, and a Web user interface. Users can use a Web browser to push DICOM images, directly or indirectly from PACS, to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, are then extracted and compared with patterns from the atlas image database to assess the bone age. The digital atlas method built on a large image database and current Internet technology provides an alternative to supplement or replace the traditional one for a quantitative, accurate and cost-effective assessment of bone age.

Digital hand atlas and computer-aided bone age assessment via the Web

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente

1999-07-01

A frequently used assessment method of bone age is atlas matching by a radiological examination of a hand image against a reference set of atlas patterns of normal standards. We are in a process of developing a digital hand atlas with a large standard set of normal hand and wrist images that reflect the skeletal maturity, race and sex difference, and current child development. The digital hand atlas will be used for a computer-aided bone age assessment via Web. We have designed and partially implemented a computer-aided diagnostic (CAD) system for Web-based bone age assessment. The system consists of a digital hand atlas, a relational image database and a Web-based user interface. The digital atlas is based on a large standard set of normal hand an wrist images with extracted bone objects and quantitative features. The image database uses a content- based indexing to organize the hand images and their attributes and present to users in a structured way. The Web-based user interface allows users to interact with the hand image database from browsers. Users can use a Web browser to push a clinical hand image to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, will be extracted and compared with patterns from the atlas database to assess the bone age. The relevant reference imags and the final assessment report will be sent back to the user's browser via Web. The digital atlas will remove the disadvantages of the currently out-of-date one and allow the bone age assessment to be computerized and done conveniently via Web. In this paper, we present the system design and Web-based client-server model for computer-assisted bone age assessment and our initial implementation of the digital atlas database.

The ATLAS PanDA Monitoring System and its Evolution

NASA Astrophysics Data System (ADS)

Klimentov, A.; Nevski, P.; Potekhin, M.; Wenaus, T.

2011-12-01

The PanDA (Production and Distributed Analysis) Workload Management System is used for ATLAS distributed production and analysis worldwide. The needs of ATLAS global computing imposed challenging requirements on the design of PanDA in areas such as scalability, robustness, automation, diagnostics, and usability for both production shifters and analysis users. Through a system-wide job database, the PanDA monitor provides a comprehensive and coherent view of the system and job execution, from high level summaries to detailed drill-down job diagnostics. It is (like the rest of PanDA) an Apache-based Python application backed by Oracle. The presentation layer is HTML code generated on the fly in the Python application which is also responsible for managing database queries. However, this approach is lacking in user interface flexibility, simplicity of communication with external systems, and ease of maintenance. A decision was therefore made to migrate the PanDA monitor server to Django Web Application Framework and apply JSON/AJAX technology in the browser front end. This allows us to greatly reduce the amount of application code, separate data preparation from presentation, leverage open source for tools such as authentication and authorization mechanisms, and provide a richer and more dynamic user experience. We describe our approach, design and initial experience with the migration process.

Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

NASA Astrophysics Data System (ADS)

Ritsch, E.; Atlas Collaboration

2014-06-01

The huge success of the physics program of the ATLAS experiment at the Large Hadron Collider (LHC) during Run 1 relies upon a great number of simulated Monte Carlo events. This Monte Carlo production takes the biggest part of the computing resources being in use by ATLAS as of now. In this document we describe the plans to overcome the computing resource limitations for large scale Monte Carlo production in the ATLAS Experiment for Run 2, and beyond. A number of fast detector simulation, digitization and reconstruction techniques are being discussed, based upon a new flexible detector simulation framework. To optimally benefit from these developments, a redesigned ATLAS MC production chain is presented at the end of this document.

OSiRIS: a distributed Ceph deployment using software defined networking for multi-institutional research

NASA Astrophysics Data System (ADS)

McKee, Shawn; Kissel, Ezra; Meekhof, Benjeman; Swany, Martin; Miller, Charles; Gregorowicz, Michael

2017-10-01

We report on the first year of the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) which is targeting the creation of a distributed Ceph storage infrastructure coupled together with software-defined networking to provide high-performance access for well-connected locations on any participating campus. The projects goal is to provide a single scalable, distributed storage infrastructure that allows researchers at each campus to read, write, manage and share data directly from their own computing locations. The NSF CC*DNI DIBBS program which funded OSiRIS is seeking solutions to the challenges of multi-institutional collaborations involving large amounts of data and we are exploring the creative use of Ceph and networking to address those challenges. While OSiRIS will eventually be serving a broad range of science domains, its first adopter will be the LHC ATLAS detector project via the ATLAS Great Lakes Tier-2 (AGLT2) jointly located at the University of Michigan and Michigan State University. Part of our presentation will cover how ATLAS is using the OSiRIS infrastructure and our experiences integrating our first user community. The presentation will also review the motivations for and goals of the project, the technical details of the OSiRIS infrastructure, the challenges in providing such an infrastructure, and the technical choices made to address those challenges. We will conclude with our plans for the remaining 4 years of the project and our vision for what we hope to deliver by the projects end.

High-Throughput Computing on High-Performance Platforms: A Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oleynik, D; Panitkin, S; Matteo, Turilli

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan -- a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i)more » a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner.« less

The ATLAS Event Service: A new approach to event processing

NASA Astrophysics Data System (ADS)

Calafiura, P.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.

2015-12-01

The ATLAS Event Service (ES) implements a new fine grained approach to HEP event processing, designed to be agile and efficient in exploiting transient, short-lived resources such as HPC hole-filling, spot market commercial clouds, and volunteer computing. Input and output control and data flows, bookkeeping, monitoring, and data storage are all managed at the event level in an implementation capable of supporting ATLAS-scale distributed processing throughputs (about 4M CPU-hours/day). Input data flows utilize remote data repositories with no data locality or pre-staging requirements, minimizing the use of costly storage in favor of strongly leveraging powerful networks. Object stores provide a highly scalable means of remotely storing the quasi-continuous, fine grained outputs that give ES based applications a very light data footprint on a processing resource, and ensure negligible losses should the resource suddenly vanish. We will describe the motivations for the ES system, its unique features and capabilities, its architecture and the highly scalable tools and technologies employed in its implementation, and its applications in ATLAS processing on HPCs, commercial cloud resources, volunteer computing, and grid resources. Notice: This manuscript has been authored by employees of Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. The publisher by accepting the manuscript for publication acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Exploiting opportunistic resources for ATLAS with ARC CE and the Event Service

NASA Astrophysics Data System (ADS)

Cameron, D.; Filipčič, A.; Guan, W.; Tsulaia, V.; Walker, R.; Wenaus, T.; ATLAS Collaboration

2017-10-01

With ever-greater computing needs and fixed budgets, big scientific experiments are turning to opportunistic resources as a means to add much-needed extra computing power. These resources can be very different in design from those that comprise the Grid computing of most experiments, therefore exploiting them requires a change in strategy for the experiment. They may be highly restrictive in what can be run or in connections to the outside world, or tolerate opportunistic usage only on condition that tasks may be terminated without warning. The Advanced Resource Connector Computing Element (ARC CE) with its nonintrusive architecture is designed to integrate resources such as High Performance Computing (HPC) systems into a computing Grid. The ATLAS experiment developed the ATLAS Event Service (AES) primarily to address the issue of jobs that can be terminated at any point when opportunistic computing capacity is needed by someone else. This paper describes the integration of these two systems in order to exploit opportunistic resources for ATLAS in a restrictive environment. In addition to the technical details, results from deployment of this solution in the SuperMUC HPC centre in Munich are shown.

Multi-threaded ATLAS simulation on Intel Knights Landing processors

NASA Astrophysics Data System (ADS)

Farrell, Steven; Calafiura, Paolo; Leggett, Charles; Tsulaia, Vakhtang; Dotti, Andrea; ATLAS Collaboration

2017-10-01

The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), was delivered to its users in two phases with the first phase online at the end of 2015 and the second phase now online at the end of 2016. Cori Phase 2 is based on the KNL architecture and contains over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a good potential use-case for the KNL architecture and supercomputers like Cori. ATLAS simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this paper we will give an overview of the ATLAS simulation application with details on its multi-threaded design. Then, we will present a performance analysis of the application on KNL devices and compare it to a traditional x86 platform to demonstrate the capabilities of the architecture and evaluate the benefits of utilizing KNL platforms like Cori for ATLAS production.

SU-E-J-128: Two-Stage Atlas Selection in Multi-Atlas-Based Image Segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, T; Ruan, D

2015-06-15

Purpose: In the new era of big data, multi-atlas-based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two-stage atlas selection scheme to achieve computational economy with performance guarantee. Methods: We develop a low-cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full-fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is firstmore » roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full-fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability. Results: The performance and complexity of the proposed two-stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one-stage method with full-fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one-stage cost-saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78). Conclusion: This work has developed a model-guided two-stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit in both complexity and performance is expected to be most pronounced with large-scale heterogeneous data.« less

Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction

PubMed Central

Chen, Ishita; Ong, Rowena E.; Simpson, Amber L.; Sun, Kay; Thompson, Reid C.

2015-01-01

In recent work, an atlas-based statistical model for brain shift prediction, which accounts for uncertainty in the intraoperative environment, has been proposed. Previous work reported in the literature using this technique did not account for local deformation caused by surgical retraction. It is challenging to precisely localize the retractor location prior to surgery and the retractor is often moved in the course of the procedure. This paper proposes a technique that involves computing the retractor-induced brain deformation in the operating room through an active model solve and linearly superposing the solution with the precomputed deformation atlas. As a result, the new method takes advantage of the atlas-based framework’s accounting for uncertainties while also incorporating the effects of retraction with minimal intraoperative computing. This new approach was tested using simulation and phantom experiments. The results showed an improvement in average shift correction from 50% (ranging from 14 to 81%) for gravity atlas alone to 80% using the active solve retraction component (ranging from 73 to 85%). This paper presents a novel yet simple way to integrate retraction into the atlas-based brain shift computation framework. PMID:23864146

Three-dimensional atlas of iron, copper, and zinc in the mouse cerebrum and brainstem.

PubMed

Hare, Dominic J; Lee, Jason K; Beavis, Alison D; van Gramberg, Amanda; George, Jessica; Adlard, Paul A; Finkelstein, David I; Doble, Philip A

2012-05-01

Atlases depicting molecular and functional features of the brain are becoming an integral part of modern neuroscience. In this study we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICPMS) to quantitatively measure iron (Fe), copper (Cu), and zinc (Zn) levels in a serially sectioned C57BL/6 mouse brain (cerebrum and brainstem). Forty-six sections were analyzed in a single experiment of approximately 158 h in duration. We constructed a 46-plate reference atlas by aligning quantified images of metal distribution with corresponding coronal sections from the Allen Mouse Brain Reference Atlas. The 46 plates were also used to construct three-dimensional models of Fe, Cu, and Zn distribution. This atlas represents the first reconstruction of quantitative trace metal distribution through the brain by LA-ICPMS and will facilitate the study of trace metals in the brain and help to elucidate their role in neurobiology.

Design and implementation of a UNIX based distributed computing system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Love, J.S.; Michael, M.W.

1994-12-31

We have designed, implemented, and are running a corporate-wide distributed processing batch queue on a large number of networked workstations using the UNIX{reg_sign} operating system. Atlas Wireline researchers and scientists have used the system for over a year. The large increase in available computer power has greatly reduced the time required for nuclear and electromagnetic tool modeling. Use of remote distributed computing has simultaneously reduced computation costs and increased usable computer time. The system integrates equipment from different manufacturers, using various CPU architectures, distinct operating system revisions, and even multiple processors per machine. Various differences between the machines have tomore » be accounted for in the master scheduler. These differences include shells, command sets, swap spaces, memory sizes, CPU sizes, and OS revision levels. Remote processing across a network must be performed in a manner that is seamless from the users` perspective. The system currently uses IBM RISC System/6000{reg_sign}, SPARCstation{sup TM}, HP9000s700, HP9000s800, and DEC Alpha AXP{sup TM} machines. Each CPU in the network has its own speed rating, allowed working hours, and workload parameters. The system if designed so that all of the computers in the network can be optimally scheduled without adversely impacting the primary users of the machines. The increase in the total usable computational capacity by means of distributed batch computing can change corporate computing strategy. The integration of disparate computer platforms eliminates the need to buy one type of computer for computations, another for graphics, and yet another for day-to-day operations. It might be possible, for example, to meet all research and engineering computing needs with existing networked computers.« less

INTEGRATION OF PANDA WORKLOAD MANAGEMENT SYSTEM WITH SUPERCOMPUTERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

De, K; Jha, S; Maeno, T

Abstract The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the funda- mental nature of matter and the basic forces that shape our universe, and were recently credited for the dis- covery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Datamore » Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data cen- ters are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Com- puting Facility (OLCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single- threaded workloads in parallel on Titan s multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accom- plishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility s infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.« less

Workflow Management Systems for Molecular Dynamics on Leadership Computers

NASA Astrophysics Data System (ADS)

Wells, Jack; Panitkin, Sergey; Oleynik, Danila; Jha, Shantenu

Molecular Dynamics (MD) simulations play an important role in a range of disciplines from Material Science to Biophysical systems and account for a large fraction of cycles consumed on computing resources. Increasingly science problems require the successful execution of ''many'' MD simulations as opposed to a single MD simulation. There is a need to provide scalable and flexible approaches to the execution of the workload. We present preliminary results on the Titan computer at the Oak Ridge Leadership Computing Facility that demonstrate a general capability to manage workload execution agnostic of a specific MD simulation kernel or execution pattern, and in a manner that integrates disparate grid-based and supercomputing resources. Our results build upon our extensive experience of distributed workload management in the high-energy physics ATLAS project using PanDA (Production and Distributed Analysis System), coupled with recent conceptual advances in our understanding of workload management on heterogeneous resources. We will discuss how we will generalize these initial capabilities towards a more production level service on DOE leadership resources. This research is sponsored by US DOE/ASCR and used resources of the OLCF computing facility.

Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

NASA Astrophysics Data System (ADS)

Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Twomey, M. S.; Zaytsev, A.

2014-06-01

With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

Model Stellar Atmospheres and Real Stellar Atmospheres and Status of the ATLAS12 Opacity Sampling Program and of New Programs for Rosseland and for Distribution Function Opacity

NASA Technical Reports Server (NTRS)

Kurucz, Robert L.

1996-01-01

I discuss errors in theory and in interpreting observations that are produced by the failure to consider resolution in space, time, and energy. I discuss convection in stellar model atmospheres and in stars. Large errors in abundances are possible such as the factor of ten error in the Li abundance for extreme Population II stars. Finally I discuss the variation of microturbulent velocity with depth, effective temperature, gravity, and abundance. These variations must be dealt with in computing models and grids and in any type of photometric calibration. I have also developed a new opacity-sampling version of my model atmosphere program called ATLAS12. It recognizes more than 1000 atomic and molecular species, each in up to 10 isotopic forms. It can treat all ions of the elements up through Zn and the first 5 ions of heavier elements up through Es. The elemental and isotopic abundances are treated as variables with depth. The fluxes predicted by ATLAS12 are not accurate in intermediate or narrow bandpass intervals because the sample size is too small. A special stripped version of the spectrum synthesis program SYNTHE is used to generate the surface flux for the converged model using the line data on CD-ROMs 1 and 15. ATLAS12 can be used to produce improved models for Am and Ap stars. It should be very useful for investigating diffusion effects in atmospheres. It can be used to model exciting stars for H II regions with abundances consistent with those of the H II region. These programs and line files will be distributed on CD-ROMs.

ATLAS, an integrated structural analysis and design system. Volume 1: ATLAS user's guide

NASA Technical Reports Server (NTRS)

Dreisbach, R. L. (Editor)

1979-01-01

Some of the many analytical capabilities provided by the ATLAS Version 4.0 System in the logical sequence are described in which model-definition data are prepared and the subsequent computer job is executed. The example data presented and the fundamental technical considerations that are highlighted can be used as guides during the problem solving process. This guide does not describe the details of the ATLAS capabilities, but provides an introduction to the new user of ATLAS to the level at which the complete array of capabilities described in the ATLAS User's Manual can be exploited fully.

DoE Early Career Research Program: Final Report: Model-Independent Dark-Matter Searches at the ATLAS Experiment and Applications of Many-core Computing to High Energy Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farbin, Amir

2015-07-15

This is the final report of for DoE Early Career Research Program Grant Titled "Model-Independent Dark-Matter Searches at the ATLAS Experiment and Applications of Many-core Computing to High Energy Physics".

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.; Abat, E.; Abbott, B.

2011-11-28

The Large Hadron Collider (LHC) at CERN promises a major step forward in the understanding of the fundamental nature of matter. The ATLAS experiment is a general-purpose detector for the LHC, whose design was guided by the need to accommodate the wide spectrum of possible physics signatures. The major remit of the ATLAS experiment is the exploration of the TeV mass scale where groundbreaking discoveries are expected. In the focus are the investigation of the electroweak symmetry breaking and linked to this the search for the Higgs boson as well as the search for Physics beyond the Standard Model. Inmore » this report a detailed examination of the expected performance of the ATLAS detector is provided, with a major aim being to investigate the experimental sensitivity to a wide range of measurements and potential observations of new physical processes. An earlier summary of the expected capabilities of ATLAS was compiled in 1999 [1]. A survey of physics capabilities of the CMS detector was published in [2]. The design of the ATLAS detector has now been finalised, and its construction and installation have been completed [3]. An extensive test-beam programme was undertaken. Furthermore, the simulation and reconstruction software code and frameworks have been completely rewritten. Revisions incorporated reflect improved detector modelling as well as major technical changes to the software technology. Greatly improved understanding of calibration and alignment techniques, and their practical impact on performance, is now in place. The studies reported here are based on full simulations of the ATLAS detector response. A variety of event generators were employed. The simulation and reconstruction of these large event samples thus provided an important operational test of the new ATLAS software system. In addition, the processing was distributed world-wide over the ATLAS Grid facilities and hence provided an important test of the ATLAS computing system - this is the origin of the expression 'CSC studies' ('computing system commissioning'), which is occasionally referred to in these volumes. The work reported does generally assume that the detector is fully operational, and in this sense represents an idealised detector: establishing the best performance of the ATLAS detector with LHC proton-proton collisions is a challenging task for the future. The results summarised here therefore represent the best estimate of ATLAS capabilities before real operational experience of the full detector with beam. Unless otherwise stated, simulations also do not include the effect of additional interactions in the same or other bunch-crossings, and the effect of neutron background is neglected. Thus simulations correspond to the low-luminosity performance of the ATLAS detector. This report is broadly divided into two parts: firstly the performance for identification of physics objects is examined in detail, followed by a detailed assessment of the performance of the trigger system. This part is subdivided into chapters surveying the capabilities for charged particle tracking, each of electron/photon, muon and tau identification, jet and missing transverse energy reconstruction, b-tagging algorithms and performance, and finally the trigger system performance. In each chapter of the report, there is a further subdivision into shorter notes describing different aspects studied. The second major subdivision of the report addresses physics measurement capabilities, and new physics search sensitivities. Individual chapters in this part discuss ATLAS physics capabilities in Standard Model QCD and electroweak processes, in the top quark sector, in b-physics, in searches for Higgs bosons, supersymmetry searches, and finally searches for other new particles predicted in more exotic models.« less

A Multiatlas Segmentation Using Graph Cuts with Applications to Liver Segmentation in CT Scans

PubMed Central

2014-01-01

An atlas-based segmentation approach is presented that combines low-level operations, an affine probabilistic atlas, and a multiatlas-based segmentation. The proposed combination provides highly accurate segmentation due to registrations and atlas selections based on the regions of interest (ROIs) and coarse segmentations. Our approach shares the following common elements between the probabilistic atlas and multiatlas segmentation: (a) the spatial normalisation and (b) the segmentation method, which is based on minimising a discrete energy function using graph cuts. The method is evaluated for the segmentation of the liver in computed tomography (CT) images. Low-level operations define a ROI around the liver from an abdominal CT. We generate a probabilistic atlas using an affine registration based on geometry moments from manually labelled data. Next, a coarse segmentation of the liver is obtained from the probabilistic atlas with low computational effort. Then, a multiatlas segmentation approach improves the accuracy of the segmentation. Both the atlas selections and the nonrigid registrations of the multiatlas approach use a binary mask defined by coarse segmentation. We experimentally demonstrate that this approach performs better than atlas selections and nonrigid registrations in the entire ROI. The segmentation results are comparable to those obtained by human experts and to other recently published results. PMID:25276219

Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters.

PubMed

Dill, Vanderson; Klein, Pedro Costa; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

2018-04-01

Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy. Copyright © 2018 Elsevier Ltd. All rights reserved.

The consistency service of the ATLAS Distributed Data Management system

NASA Astrophysics Data System (ADS)

Serfon, Cédric; Garonne, Vincent; ATLAS Collaboration

2011-12-01

With the continuously increasing volume of data produced by ATLAS and stored on the WLCG sites, the probability of data corruption or data losses, due to software and hardware failures is increasing. In order to ensure the consistency of all data produced by ATLAS a Consistency Service has been developed as part of the DQ2 Distributed Data Management system. This service is fed by the different ATLAS tools, i.e. the analysis tools, production tools, DQ2 site services or by site administrators that report corrupted or lost files. It automatically corrects the errors reported and informs the users in case of irrecoverable file loss.

Research on Spectroscopy, Opacity, and Atmospheres

NASA Technical Reports Server (NTRS)

Kurucz, Robert L.

1999-01-01

A web site has been set up to make the calculations accessible; (i.e., cfakus.harvard.edu) This data can also be accessed by FTP. It has all of the atomic and diatomic molecular data, tables of distribution function opacities, grids of model atmospheres, colors, fluxes, etc, programs that are ready for distribution, and most of recent papers developed during this grant. Atlases and computed spectra will be added as they are completed. New atomic and molecular calculations will be added as they are completed. The atomic programs that had been running on a Cray at the San Diego Supercomputer Center can now run on the Vaxes and Alpha. The work started with Ni and Co because there were new laboratory analyses that included isotopic and hyperfine splitting. Those calculations are described in the appended abstract for the 6th Atomic Spectroscopy and oscillator Strengths meeting in Victoria last summer. A surprising finding is that quadrupole transitions have been grossly in error because mixing with higher levels has not been included. All levels up through n=9 for Fe I and II, the spectra for which the most information is available, are now included. After Fe I and Fe II, all other spectra are "easy". ATLAS12, the opacity sampling program for computing models with arbitrary abundances, has been put on the web server. A new distribution function opacity program for workstations that replaces the one used on the Cray at the San Diego Supercomputer Center has been written. Each set of abundances would take 100 Cray hours costing $100,000.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer.

PubMed

Wu, Abraham J; Bosch, Walter R; Chang, Daniel T; Hong, Theodore S; Jabbour, Salma K; Kleinberg, Lawrence R; Mamon, Harvey J; Thomas, Charles R; Goodman, Karyn A

2015-07-15

Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future. Copyright © 2015 Elsevier Inc. All rights reserved.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Abraham J., E-mail: wua@mskcc.org; Bosch, Walter R.; Chang, Daniel T.

Purpose/Objective(s): Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials: Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophagealmore » cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results: The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions: This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future.« less

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

NASA Astrophysics Data System (ADS)

Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-06-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for collecting and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This requires strong competence and experience in understanding and discovering problems and root causes, and often the meaningful information is not in the single message or update, but in the aggregated behavior in a certain time-line. The AAL project is meant at reducing the man power needs and at assuring a constant high quality of problem detection by automating most of the monitoring tasks and providing real-time correlation of data-taking and system metrics. This project combines technologies coming from different disciplines, in particular it leverages on an Event Driven Architecture to unify the flow of data from the ATLAS infrastructure, on a Complex Event Processing (CEP) engine for correlation of events and on a message oriented architecture for components integration. The project is composed of 2 main components: a core processing engine, responsible for correlation of events through expert-defined queries and a web based front-end to present real-time information and interact with the system. All components works in a loose-coupled event based architecture, with a message broker to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

Consolidation of cloud computing in ATLAS

NASA Astrophysics Data System (ADS)

Taylor, Ryan P.; Domingues Cordeiro, Cristovao Jose; Giordano, Domenico; Hover, John; Kouba, Tomas; Love, Peter; McNab, Andrew; Schovancova, Jaroslava; Sobie, Randall; ATLAS Collaboration

2017-10-01

Throughout the first half of LHC Run 2, ATLAS cloud computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS cloud computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 cloud for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial cloud capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems.

ATLAS and LHC computing on CRAY

NASA Astrophysics Data System (ADS)

Sciacca, F. G.; Haug, S.; ATLAS Collaboration

2017-10-01

Access and exploitation of large scale computing resources, such as those offered by general purpose HPC centres, is one important measure for ATLAS and the other Large Hadron Collider experiments in order to meet the challenge posed by the full exploitation of the future data within the constraints of flat budgets. We report on the effort of moving the Swiss WLCG T2 computing, serving ATLAS, CMS and LHCb, from a dedicated cluster to the large Cray systems at the Swiss National Supercomputing Centre CSCS. These systems do not only offer very efficient hardware, cooling and highly competent operators, but also have large backfill potentials due to size and multidisciplinary usage and potential gains due to economy at scale. Technical solutions, performance, expected return and future plans are discussed.

Automatic testing and assessment of neuroanatomy using a digital brain atlas: method and development of computer- and mobile-based applications.

PubMed

Nowinski, Wieslaw L; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G; Marchenko, Yevgen; Volkau, Ihar

2009-10-01

Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to Terminologia Anatomica. Because the cerebral models are fully segmented and labeled, our approach enables automatic and random atlas-derived generation of questions to test location and naming of cerebral structures. This is done in four steps: test individualization by the instructor, test taking by the students at their convenience, automatic student assessment by the application, and communication of the individual assessment to the instructor. A computer-based application with an interactive 3D atlas and a preliminary mobile-based application were developed to realize this approach. The application works in two test modes: instructor and student. In the instructor mode, the instructor customizes the test by setting the scope of testing and student performance criteria, which takes a few seconds. In the student mode, the student is tested and automatically assessed. Self-testing is also feasible at any time and pace. Our approach is automatic both with respect to test generation and student assessment. It is also objective, rapid, and customizable. We believe that this approach is novel from computer-based, mobile-based, and atlas-assisted standpoints.

ATLAS, an integrated structural analysis and design system. Volume 4: Random access file catalog

NASA Technical Reports Server (NTRS)

Gray, F. P., Jr. (Editor)

1979-01-01

A complete catalog is presented for the random access files used by the ATLAS integrated structural analysis and design system. ATLAS consists of several technical computation modules which output data matrices to corresponding random access file. A description of the matrices written on these files is contained herein.

Quantitative Analyses of Pediatric Cervical Spine Ossification Patterns Using Computed Tomography

PubMed Central

Yoganandan, Narayan; Pintar, Frank A.; Lew, Sean M.; Rao, Raj D.; Rangarajan, Nagarajan

2011-01-01

The objective of the present study was to quantify ossification processes of the human pediatric cervical spine. Computed tomography images were obtained from a high resolution scanner according to clinical protocols. Bone window images were used to identify the presence of the primary synchondroses of the atlas, axis, and C3 vertebrae in 101 children. Principles of logistic regression were used to determine probability distributions as a function of subject age for each synchondrosis for each vertebra. The mean and 95% upper and 95% lower confidence intervals are given for each dataset delineating probability curves. Posterior ossifications preceded bilateral anterior closures of the synchondroses in all vertebrae. However, ossifications occurred at different ages. Logistic regression results for closures of different synchondrosis indicated p-values of <0.001 for the atlas, ranging from 0.002 to <0.001 for the axis, and 0.021 to 0.005 for the C3 vertebra. Fifty percent probability of three, two, and one synchondroses occurred at 2.53, 6.97, and 7.57 years of age for the atlas; 3.59, 4.74, and 5.7 years of age for the axis; and 1.28, 2.22, and 3.17 years of age for the third cervical vertebrae, respectively. Ossifications occurring at different ages indicate non-uniform maturations of bone growth/strength. They provide an anatomical rationale to reexamine dummies, scaling processes, and injury metrics for improved understanding of pediatric neck injuries PMID:22105393

Atlas of current and potential future distributions of common trees of the eastern United States

Treesearch

Louis R. Iverson; Anantha M. Prasad; Betsy J. Hale; Elaine Kennedy Sutherland

1999-01-01

This atlas documents the current and possible future distribution of 80 common tree species in the Eastern United States and gives detailed information on environmental characteristics defining these distributions. Also included are outlines of life history characteristics and summary statistics for these species. Much of the data are derived from Forest Inventory and...

SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, X; Gao, H; Sharp, G

2015-06-15

Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to eachmore » chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection.

PubMed

Zhuang, Xiahai; Bai, Wenjia; Song, Jingjing; Zhan, Songhua; Qian, Xiaohua; Shi, Wenzhe; Lian, Yanyun; Rueckert, Daniel

2015-07-01

Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors' proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p < 0.03). In the atlas database study, the authors showed that the MAS using larger atlas databases generated better performance curves than the MAS using smaller ones, indicating larger atlas databases could produce more accurate segmentation. The authors have developed a new MAS framework for automatic WHS of CTA and investigated alternative implementations of MAS. With the proposed atlas ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation within practically acceptable computation time. This method can be useful for the development of new clinical applications of cardiac CT.

Energy Frontier Research With ATLAS: Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, John; Black, Kevin; Ahlen, Steve

2016-06-14

The Boston University (BU) group is playing key roles across the ATLAS experiment: in detector operations, the online trigger, the upgrade, computing, and physics analysis. Our team has been critical to the maintenance and operations of the muon system since its installation. During Run 1 we led the muon trigger group and that responsibility continues into Run 2. BU maintains and operates the ATLAS Northeast Tier 2 computing center. We are actively engaged in the analysis of ATLAS data from Run 1 and Run 2. Physics analyses we have contributed to include Standard Model measurements (W and Z cross sections,more » t\\bar{t} differential cross sections, WWW^* production), evidence for the Higgs decaying to \\tau^+\\tau^-, and searches for new phenomena (technicolor, Z' and W', vector-like quarks, dark matter).« less

A web-based solution to visualize operational monitoring data in the Trigger and Data Acquisition system of the ATLAS experiment at the LHC

NASA Astrophysics Data System (ADS)

Avolio, G.; D'Ascanio, M.; Lehmann-Miotto, G.; Soloviev, I.

2017-10-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider at CERN is composed of a large number of distributed hardware and software components (about 3000 computers and more than 25000 applications) which, in a coordinated manner, provide the data-taking functionality of the overall system. During data taking runs, a huge flow of operational data is produced in order to constantly monitor the system and allow proper detection of anomalies or misbehaviours. In the ATLAS trigger and data acquisition system, operational data are archived and made available to applications by the P-BEAST (Persistent Back-End for the Atlas Information System of TDAQ) service, implementing a custom time-series database. The possibility to efficiently visualize both realtime and historical operational data is a great asset facilitating both online identification of problems and post-mortem analysis. This paper will present a web-based solution developed to achieve such a goal: the solution leverages the flexibility of the P-BEAST archiver to retrieve data, and exploits the versatility of the Grafana dashboard builder to offer a very rich user experience. Additionally, particular attention will be given to the way some technical challenges (like the efficient visualization of a huge amount of data and the integration of the P-BEAST data source in Grafana) have been faced and solved.

Atlas2 Cloud: a framework for personal genome analysis in the cloud

PubMed Central

2012-01-01

Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms. PMID:23134663

Atlas2 Cloud: a framework for personal genome analysis in the cloud.

PubMed

Evani, Uday S; Challis, Danny; Yu, Jin; Jackson, Andrew R; Paithankar, Sameer; Bainbridge, Matthew N; Jakkamsetti, Adinarayana; Pham, Peter; Coarfa, Cristian; Milosavljevic, Aleksandar; Yu, Fuli

2012-01-01

Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.

Production experience with the ATLAS Event Service

NASA Astrophysics Data System (ADS)

Benjamin, D.; Calafiura, P.; Childers, T.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The ATLAS Event Service (AES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the AES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Google Compute Engine, and a growing number of HPC platforms. After briefly reviewing the concept and the architecture of the Event Service, we will report the status and experience gained in AES commissioning and production operations on supercomputers, and our plans for extending ES application beyond Geant4 simulation to other workflows, such as reconstruction and data analysis.

Reference geometry-based detection of (4D-)CT motion artifacts: a feasibility study

NASA Astrophysics Data System (ADS)

Werner, René; Gauer, Tobias

2015-03-01

Respiration-correlated computed tomography (4D or 3D+t CT) can be considered as standard of care in radiation therapy treatment planning for lung and liver lesions. The decision about an application of motion management devices and the estimation of patient-specific motion effects on the dose distribution relies on precise motion assessment in the planning 4D CT data { which is impeded in case of CT motion artifacts. The development of image-based/post-processing approaches to reduce motion artifacts would benefit from precise detection and localization of the artifacts. Simple slice-by-slice comparison of intensity values and threshold-based analysis of related metrics suffer from- depending on the threshold- high false-positive or -negative rates. In this work, we propose exploiting prior knowledge about `ideal' (= artifact free) reference geometries to stabilize metric-based artifact detection by transferring (multi-)atlas-based concepts to this specific task. Two variants are introduced and evaluated: (S1) analysis and comparison of warped atlas data obtained by repeated non-linear atlas-to-patient registration with different levels of regularization; (S2) direct analysis of vector field properties (divergence, curl magnitude) of the atlas-to-patient transformation. Feasibility of approaches (S1) and (S2) is evaluated by motion-phantom data and intra-subject experiments (four patients) as well as - adopting a multi-atlas strategy- inter-subject investigations (twelve patients involved). It is demonstrated that especially sorting/double structure artifacts can be precisely detected and localized by (S1). In contrast, (S2) suffers from high false positive rates.

Statistical atlas based extrapolation of CT data

NASA Astrophysics Data System (ADS)

Chintalapani, Gouthami; Murphy, Ryan; Armiger, Robert S.; Lepisto, Jyri; Otake, Yoshito; Sugano, Nobuhiko; Taylor, Russell H.; Armand, Mehran

2010-02-01

We present a framework to estimate the missing anatomical details from a partial CT scan with the help of statistical shape models. The motivating application is periacetabular osteotomy (PAO), a technique for treating developmental hip dysplasia, an abnormal condition of the hip socket that, if untreated, may lead to osteoarthritis. The common goals of PAO are to reduce pain, joint subluxation and improve contact pressure distribution by increasing the coverage of the femoral head by the hip socket. While current diagnosis and planning is based on radiological measurements, because of significant structural variations in dysplastic hips, a computer-assisted geometrical and biomechanical planning based on CT data is desirable to help the surgeon achieve optimal joint realignments. Most of the patients undergoing PAO are young females, hence it is usually desirable to minimize the radiation dose by scanning only the joint portion of the hip anatomy. These partial scans, however, do not provide enough information for biomechanical analysis due to missing iliac region. A statistical shape model of full pelvis anatomy is constructed from a database of CT scans. The partial volume is first aligned with the statistical atlas using an iterative affine registration, followed by a deformable registration step and the missing information is inferred from the atlas. The atlas inferences are further enhanced by the use of X-ray images of the patient, which are very common in an osteotomy procedure. The proposed method is validated with a leave-one-out analysis method. Osteotomy cuts are simulated and the effect of atlas predicted models on the actual procedure is evaluated.

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

PubMed Central

Tang, Xiaoying; Yoshida, Shoko; Hsu, John; Huisman, Thierry A. G. M.; Faria, Andreia V.; Oishi, Kenichi; Kutten, Kwame; Poretti, Andrea; Li, Yue; Miller, Michael I.; Mori, Susumu

2014-01-01

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure. PMID:24809486

A study of dynamic data placement for ATLAS distributed data management

NASA Astrophysics Data System (ADS)

Beermann, T.; Stewart, G. A.; Maettig, P.

2015-12-01

This contribution presents a study on the applicability and usefulness of dynamic data placement methods for data-intensive systems, such as ATLAS distributed data management (DDM). In this system the jobs are sent to the data, therefore having a good distribution of data is significant. Ways of forecasting workload patterns are examined which then are used to redistribute data to achieve a better overall utilisation of computing resources and to reduce waiting time for jobs before they can run on the grid. This method is based on a tracer infrastructure that is able to monitor and store historical data accesses and which is used to create popularity reports. These reports provide detailed summaries about data accesses in the past, including information about the accessed files, the involved users and the sites. From this past data it is possible to then make near-term forecasts for data popularity in the future. This study evaluates simple prediction methods as well as more complex methods like neural networks. Based on the outcome of the predictions a redistribution algorithm deletes unused replicas and adds new replicas for potentially popular datasets. Finally, a grid simulator is used to examine the effects of the redistribution. The simulator replays workload on different data distributions while measuring the job waiting time and site usage. The study examines how the average waiting time is affected by the amount of data that is moved, how it differs for the various forecasting methods and how that compares to the optimal data distribution.

Quantitative Evaluation of Atlas-based Attenuation Correction for Brain PET in an Integrated Time-of-Flight PET/MR Imaging System.

PubMed

Yang, Jaewon; Jian, Yiqiang; Jenkins, Nathaniel; Behr, Spencer C; Hope, Thomas A; Larson, Peder E Z; Vigneron, Daniel; Seo, Youngho

2017-07-01

Purpose To assess the patient-dependent accuracy of atlas-based attenuation correction (ATAC) for brain positron emission tomography (PET) in an integrated time-of-flight (TOF) PET/magnetic resonance (MR) imaging system. Materials and Methods Thirty recruited patients provided informed consent in this institutional review board-approved study. All patients underwent whole-body fluorodeoxyglucose PET/computed tomography (CT) followed by TOF PET/MR imaging. With use of TOF PET data, PET images were reconstructed with four different attenuation correction (AC) methods: PET with patient CT-based AC (CTAC), PET with ATAC (air and bone from an atlas), PET with ATAC patientBone (air and tissue from the atlas with patient bone), and PET with ATAC boneless (air and tissue from the atlas without bone). For quantitative evaluation, PET mean activity concentration values were measured in 14 1-mL volumes of interest (VOIs) distributed throughout the brain and statistical significance was tested with a paired t test. Results The mean overall difference (±standard deviation) of PET with ATAC compared with PET with CTAC was -0.69 kBq/mL ± 0.60 (-4.0% ± 3.2) (P < .001). The results were patient dependent (range, -9.3% to 0.57%) and VOI dependent (range, -5.9 to -2.2). In addition, when bone was not included for AC, the overall difference of PET with ATAC boneless (-9.4% ± 3.7) was significantly worse than that of PET with ATAC (-4.0% ± 3.2) (P < .001). Finally, when patient bone was used for AC instead of atlas bone, the overall difference of PET with ATAC patientBone (-1.5% ± 1.5) improved over that of PET with ATAC (-4.0% ± 3.2) (P < .001). Conclusion ATAC in PET/MR imaging achieves similar quantification accuracy to that from CTAC by means of atlas-based bone compensation. However, patient-specific anatomic differences from the atlas causes bone attenuation differences and misclassified sinuses, which result in patient-dependent performance variation of ATAC. © RSNA, 2017 Online supplemental material is available for this article.

A Conditions Data Management System for HEP Experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laycock, P. J.; Dykstra, D.; Formica, A.

Conditions data infrastructure for both ATLAS and CMS have to deal with the management of several Terabytes of data. Distributed computing access to this data requires particular care and attention to manage request-rates of up to several tens of kHz. Thanks to the large overlap in use cases and requirements, ATLAS and CMS have worked towards a common solution for conditions data management with the aim of using this design for data-taking in Run 3. In the meantime other experiments, including NA62, have expressed an interest in this cross- experiment initiative. For experiments with a smaller payload volume and complexity,more » there is particular interest in simplifying the payload storage. The conditions data management model is implemented in a small set of relational database tables. A prototype access toolkit consisting of an intermediate web server has been implemented, using standard technologies available in the Java community. Access is provided through a set of REST services for which the API has been described in a generic way using standard Open API specications, implemented in Swagger. Such a solution allows the automatic generation of client code and server stubs and further allows changes in the backend technology transparently. An important advantage of using a REST API for conditions access is the possibility of caching identical URLs, addressing one of the biggest challenges that large distributed computing solutions impose on conditions data access, avoiding direct DB access by means of standard web proxy solutions.« less

Automatic Testing and Assessment of Neuroanatomy Using a Digital Brain Atlas: Method and Development of Computer- and Mobile-Based Applications

ERIC Educational Resources Information Center

Nowinski, Wieslaw L.; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G.; Marchenko, Yevgen; Volkau, Ihar

2009-01-01

Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to "Terminologia…

An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS buoy drift, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1990

NASA Technical Reports Server (NTRS)

Halpern, D.; Knauss, W.; Brown, O.; Wentz, F.

1993-01-01

The following monthly mean global distributions for 1990 are proposed with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (US) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components on the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation values are displayed. Annual mean distributions are displayed.

An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS buoy drift, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1991

NASA Technical Reports Server (NTRS)

Halpern, D.; Knauss, W.; Brown, O.; Wentz, F.

1993-01-01

The following monthly mean global distributions for 1991 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free-drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components of the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning.

PubMed

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multi-atlas-based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

A whole brain atlas with sub-parcellation of cortical gyri using resting fMRI

NASA Astrophysics Data System (ADS)

Joshi, Anand A.; Choi, Soyoung; Sonkar, Gaurav; Chong, Minqi; Gonzalez-Martinez, Jorge; Nair, Dileep; Shattuck, David W.; Damasio, Hanna; Leahy, Richard M.

2017-02-01

The new hybrid-BCI-DNI atlas is a high-resolution MPRAGE, single-subject atlas, constructed using both anatomical and functional information to guide the parcellation of the cerebral cortex. Anatomical labeling was performed manually on coronal single-slice images guided by sulcal and gyral landmarks to generate the original (non-hybrid) BCI-DNI atlas. Functional sub-parcellations of the gyral ROIs were then generated from 40 minimally preprocessed resting fMRI datasets from the HCP database. Gyral ROIs were transferred from the BCI-DNI atlas to the 40 subjects using the HCP grayordinate space as a reference. For each subject, each gyral ROI was subdivided using the fMRI data by applying spectral clustering to a similarity matrix computed from the fMRI time-series correlations between each vertex pair. The sub-parcellations were then transferred back to the original cortical mesh to create the subparcellated hBCI-DNI atlas with a total of 67 cortical regions per hemisphere. To assess the stability of the gyral subdivisons, a separate set of 60 HCP datasets were processed as follows: 1) coregistration of the structural scans to the hBCI-DNI atlas; 2) coregistration of the anatomical BCI-DNI atlas without functional subdivisions, followed by sub-parcellation of each subject's resting fMRI data as described above. We then computed consistency between the anatomically-driven delineation of each gyral subdivision and that obtained per subject using individual fMRI data. The gyral sub-parcellations generated by atlas-based registration show variable but generally good overlap of the confidence intervals with the resting fMRI-based subdivisions. These consistency measures will provide a quantitative measure of reliability of each subdivision to users of the atlas.

Enhancing atlas based segmentation with multiclass linear classifiers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sdika, Michaël, E-mail: michael.sdika@creatis.insa-lyon.fr

Purpose: To present a method to enrich atlases for atlas based segmentation. Such enriched atlases can then be used as a single atlas or within a multiatlas framework. Methods: In this paper, machine learning techniques have been used to enhance the atlas based segmentation approach. The enhanced atlas defined in this work is a pair composed of a gray level image alongside an image of multiclass classifiers with one classifier per voxel. Each classifier embeds local information from the whole training dataset that allows for the correction of some systematic errors in the segmentation and accounts for the possible localmore » registration errors. The authors also propose to use these images of classifiers within a multiatlas framework: results produced by a set of such local classifier atlases can be combined using a label fusion method. Results: Experiments have been made on the in vivo images of the IBSR dataset and a comparison has been made with several state-of-the-art methods such as FreeSurfer and the multiatlas nonlocal patch based method of Coupé or Rousseau. These experiments show that their method is competitive with state-of-the-art methods while having a low computational cost. Further enhancement has also been obtained with a multiatlas version of their method. It is also shown that, in this case, nonlocal fusion is unnecessary. The multiatlas fusion can therefore be done efficiently. Conclusions: The single atlas version has similar quality as state-of-the-arts multiatlas methods but with the computational cost of a naive single atlas segmentation. The multiatlas version offers a improvement in quality and can be done efficiently without a nonlocal strategy.« less

An automatically generated texture-based atlas of the lungs

NASA Astrophysics Data System (ADS)

Dicente Cid, Yashin; Puonti, Oula; Platon, Alexandra; Van Leemput, Koen; Müller, Henning; Poletti, Pierre-Alexandre

2018-02-01

Many pulmonary diseases can be characterized by visual abnormalities on lung CT scans. Some diseases manifest similar defects but require completely different treatments, as is the case for Pulmonary Hypertension (PH) and Pulmonary Embolism (PE): both present hypo- and hyper-perfused regions but with different distribution across the lung and require different treatment protocols. Finding these distributions by visual inspection is not trivial even for trained radiologists who currently use invasive catheterism to diagnose PH. A Computer-Aided Diagnosis (CAD) tool that could facilitate the non-invasive diagnosis of these diseases can benefit both the radiologists and the patients. Most of the visual differences in the parenchyma can be characterized using texture descriptors. Current CAD systems often use texture information but the texture is either computed in a patch-based fashion, or based on an anatomical division of the lung. The difficulty of precisely finding these divisions in abnormal lungs calls for new tools for obtaining new meaningful divisions of the lungs. In this paper we present a method for unsupervised segmentation of lung CT scans into subregions that are similar in terms of texture and spatial proximity. To this extent, we combine a previously validated Riesz-wavelet texture descriptor with a well-known superpixel segmentation approach that we extend to 3D. We demonstrate the feasibility and accuracy of our approach on a simulated texture dataset, and show preliminary results for CT scans of the lung comparing subjects suffering either from PH or PE. The resulting texture-based atlas of individual lungs can potentially help physicians in diagnosis or be used for studying common texture distributions related to other diseases.

Atlas de Recursos Eólicos del Estado de Oaxaca (The Spanish version of Wind Energy Resource Atlas of Oaxaca) (in Spanish)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elliott, D.; Schwartz, M.; Scott, G.

The Oaxaca Wind Resource Atlas, produced by the National Renewable Energy Laboratory's (NREL's) wind resource group, is the result of an extensive mapping study for the Mexican State of Oaxaca. This atlas identifies the wind characteristics and distribution of the wind resource in Oaxaca. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications.

Cortical bone thickening in Type A posterior atlas arch defects: experimental report.

PubMed

Sanchis-Gimeno, Juan A; Llido, Susanna; Guede, David; Martinez-Soriano, Francisco; Ramon Caeiro, Jose; Blanco-Perez, Esther

2017-03-01

To date, no information about the cortical bone microstructural properties in atlas vertebrae with posterior arch defects has been reported. To test if there is an increased cortical bone thickening in atlases with Type A posterior atlas arch defects in an experimental model. Micro-computed tomography (CT) study on cadaveric atlas vertebrae. We analyzed the cortical bone thickness, the cortical volume, and the medullary volume (SkyScan 1172 Bruker micro-CT NV, Kontich, Belgium) in cadaveric dry vertebrae with a Type A atlas arch defect and normal control vertebrae. The micro-CT study revealed significant differences in cortical bone thickness (p=.005), cortical volume (p=.003), and medullary volume (p=.009) values between the normal and the Type A vertebrae. Type A congenital atlas arch defects present a cortical bone thickening that may play a protective role against atlas fractures. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhuang, Xiahai, E-mail: zhuangxiahai@sjtu.edu.cn; Qian, Xiaohua; Bai, Wenjia

Purpose: Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluatingmore » the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Methods: Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors’ proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. Results: The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p < 0.03). In the atlas database study, the authors showed that the MAS using larger atlas databases generated better performance curves than the MAS using smaller ones, indicating larger atlas databases could produce more accurate segmentation. Conclusions: The authors have developed a new MAS framework for automatic WHS of CTA and investigated alternative implementations of MAS. With the proposed atlas ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation within practically acceptable computation time. This method can be useful for the development of new clinical applications of cardiac CT.« less

Web Proxy Auto Discovery for the WLCG

NASA Astrophysics Data System (ADS)

Dykstra, D.; Blomer, J.; Blumenfeld, B.; De Salvo, A.; Dewhurst, A.; Verguilov, V.

2017-10-01

All four of the LHC experiments depend on web proxies (that is, squids) at each grid site to support software distribution by the CernVM FileSystem (CVMFS). CMS and ATLAS also use web proxies for conditions data distributed through the Frontier Distributed Database caching system. ATLAS & CMS each have their own methods for their grid jobs to find out which web proxies to use for Frontier at each site, and CVMFS has a third method. Those diverse methods limit usability and flexibility, particularly for opportunistic use cases, where an experiment’s jobs are run at sites that do not primarily support that experiment. This paper describes a new Worldwide LHC Computing Grid (WLCG) system for discovering the addresses of web proxies. The system is based on an internet standard called Web Proxy Auto Discovery (WPAD). WPAD is in turn based on another standard called Proxy Auto Configuration (PAC). Both the Frontier and CVMFS clients support this standard. The input into the WLCG system comes from squids registered in the ATLAS Grid Information System (AGIS) and CMS SITECONF files, cross-checked with squids registered by sites in the Grid Configuration Database (GOCDB) and the OSG Information Management (OIM) system, and combined with some exceptions manually configured by people from ATLAS and CMS who operate WLCG Squid monitoring. WPAD servers at CERN respond to http requests from grid nodes all over the world with a PAC file that lists available web proxies, based on IP addresses matched from a database that contains the IP address ranges registered to organizations. Large grid sites are encouraged to supply their own WPAD web servers for more flexibility, to avoid being affected by short term long distance network outages, and to offload the WLCG WPAD servers at CERN. The CERN WPAD servers additionally support requests from jobs running at non-grid sites (particularly for LHC@Home) which they direct to the nearest publicly accessible web proxy servers. The responses to those requests are geographically ordered based on a separate database that maps IP addresses to longitude and latitude.

Web Proxy Auto Discovery for the WLCG

DOE PAGES

Dykstra, D.; Blomer, J.; Blumenfeld, B.; ...

2017-11-23

All four of the LHC experiments depend on web proxies (that is, squids) at each grid site to support software distribution by the CernVM FileSystem (CVMFS). CMS and ATLAS also use web proxies for conditions data distributed through the Frontier Distributed Database caching system. ATLAS & CMS each have their own methods for their grid jobs to find out which web proxies to use for Frontier at each site, and CVMFS has a third method. Those diverse methods limit usability and flexibility, particularly for opportunistic use cases, where an experiment’s jobs are run at sites that do not primarily supportmore » that experiment. This paper describes a new Worldwide LHC Computing Grid (WLCG) system for discovering the addresses of web proxies. The system is based on an internet standard called Web Proxy Auto Discovery (WPAD). WPAD is in turn based on another standard called Proxy Auto Configuration (PAC). Both the Frontier and CVMFS clients support this standard. The input into the WLCG system comes from squids registered in the ATLAS Grid Information System (AGIS) and CMS SITECONF files, cross-checked with squids registered by sites in the Grid Configuration Database (GOCDB) and the OSG Information Management (OIM) system, and combined with some exceptions manually configured by people from ATLAS and CMS who operate WLCG Squid monitoring. WPAD servers at CERN respond to http requests from grid nodes all over the world with a PAC file that lists available web proxies, based on IP addresses matched from a database that contains the IP address ranges registered to organizations. Large grid sites are encouraged to supply their own WPAD web servers for more flexibility, to avoid being affected by short term long distance network outages, and to offload the WLCG WPAD servers at CERN. The CERN WPAD servers additionally support requests from jobs running at non-grid sites (particularly for LHC@Home) which it directs to the nearest publicly accessible web proxy servers. Furthermore, the responses to those requests are geographically ordered based on a separate database that maps IP addresses to longitude and latitude.« less

Web Proxy Auto Discovery for the WLCG

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykstra, D.; Blomer, J.; Blumenfeld, B.

All four of the LHC experiments depend on web proxies (that is, squids) at each grid site to support software distribution by the CernVM FileSystem (CVMFS). CMS and ATLAS also use web proxies for conditions data distributed through the Frontier Distributed Database caching system. ATLAS & CMS each have their own methods for their grid jobs to find out which web proxies to use for Frontier at each site, and CVMFS has a third method. Those diverse methods limit usability and flexibility, particularly for opportunistic use cases, where an experiment’s jobs are run at sites that do not primarily supportmore » that experiment. This paper describes a new Worldwide LHC Computing Grid (WLCG) system for discovering the addresses of web proxies. The system is based on an internet standard called Web Proxy Auto Discovery (WPAD). WPAD is in turn based on another standard called Proxy Auto Configuration (PAC). Both the Frontier and CVMFS clients support this standard. The input into the WLCG system comes from squids registered in the ATLAS Grid Information System (AGIS) and CMS SITECONF files, cross-checked with squids registered by sites in the Grid Configuration Database (GOCDB) and the OSG Information Management (OIM) system, and combined with some exceptions manually configured by people from ATLAS and CMS who operate WLCG Squid monitoring. WPAD servers at CERN respond to http requests from grid nodes all over the world with a PAC file that lists available web proxies, based on IP addresses matched from a database that contains the IP address ranges registered to organizations. Large grid sites are encouraged to supply their own WPAD web servers for more flexibility, to avoid being affected by short term long distance network outages, and to offload the WLCG WPAD servers at CERN. The CERN WPAD servers additionally support requests from jobs running at non-grid sites (particularly for LHC@Home) which it directs to the nearest publicly accessible web proxy servers. Furthermore, the responses to those requests are geographically ordered based on a separate database that maps IP addresses to longitude and latitude.« less

A New Stellar Atmosphere Grid and Comparisons with HST /STIS CALSPEC Flux Distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bohlin, Ralph C.; Fleming, Scott W.; Gordon, Karl D.

The Space Telescope Imaging Spectrograph has measured the spectral energy distributions for several stars of types O, B, A, F, and G. These absolute fluxes from the CALSPEC database are fit with a new spectral grid computed from the ATLAS-APOGEE ATLAS9 model atmosphere database using a chi-square minimization technique in four parameters. The quality of the fits are compared for complete LTE grids by Castelli and Kurucz (CK04) and our new comprehensive LTE grid (BOSZ). For the cooler stars, the fits with the MARCS LTE grid are also evaluated, while the hottest stars are also fit with the NLTE Lanzmore » and Hubeny OB star grids. Unfortunately, these NLTE models do not transition smoothly in the infrared to agree with our new BOSZ LTE grid at the NLTE lower limit of T {sub eff} = 15,000 K. The new BOSZ grid is available via the Space Telescope Institute MAST archive and has a much finer sampled IR wavelength scale than CK04, which will facilitate the modeling of stars observed by the James Webb Space Telescope . Our result for the angular diameter of Sirius agrees with the ground-based interferometric value.« less

A New Stellar Atmosphere Grid and Comparisons with HST/STIS CALSPEC Flux Distributions

NASA Astrophysics Data System (ADS)

Bohlin, Ralph C.; Mészáros, Szabolcs; Fleming, Scott W.; Gordon, Karl D.; Koekemoer, Anton M.; Kovács, József

2017-05-01

The Space Telescope Imaging Spectrograph has measured the spectral energy distributions for several stars of types O, B, A, F, and G. These absolute fluxes from the CALSPEC database are fit with a new spectral grid computed from the ATLAS-APOGEE ATLAS9 model atmosphere database using a chi-square minimization technique in four parameters. The quality of the fits are compared for complete LTE grids by Castelli & Kurucz (CK04) and our new comprehensive LTE grid (BOSZ). For the cooler stars, the fits with the MARCS LTE grid are also evaluated, while the hottest stars are also fit with the NLTE Lanz & Hubeny OB star grids. Unfortunately, these NLTE models do not transition smoothly in the infrared to agree with our new BOSZ LTE grid at the NLTE lower limit of T eff = 15,000 K. The new BOSZ grid is available via the Space Telescope Institute MAST archive and has a much finer sampled IR wavelength scale than CK04, which will facilitate the modeling of stars observed by the James Webb Space Telescope. Our result for the angular diameter of Sirius agrees with the ground-based interferometric value.

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

PubMed

Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

2015-07-15

Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy). Copyright © 2015. Published by Elsevier Inc.

The Japan Lung Cancer Society–Japanese Society for Radiation Oncology consensus-based computed tomographic atlas for defining regional lymph node stations in radiotherapy for lung cancer

PubMed Central

Itazawa, Tomoko; Tamaki, Yukihisa; Komiyama, Takafumi; Nishimura, Yasumasa; Nakayama, Yuko; Ito, Hiroyuki; Ohde, Yasuhisa; Kusumoto, Masahiko; Sakai, Shuji; Suzuki, Kenji; Watanabe, Hirokazu; Asamura, Hisao

2017-01-01

The purpose of this study was to develop a consensus-based computed tomographic (CT) atlas that defines lymph node stations in radiotherapy for lung cancer based on the lymph node map of the International Association for the Study of Lung Cancer (IASLC). A project group in the Japanese Radiation Oncology Study Group (JROSG) initially prepared a draft of the atlas in which lymph node Stations 1–11 were illustrated on axial CT images. Subsequently, a joint committee of the Japan Lung Cancer Society (JLCS) and the Japanese Society for Radiation Oncology (JASTRO) was formulated to revise this draft. The committee consisted of four radiation oncologists, four thoracic surgeons and three thoracic radiologists. The draft prepared by the JROSG project group was intensively reviewed and discussed at four meetings of the committee over several months. Finally, we proposed definitions for the regional lymph node stations and the consensus-based CT atlas. This atlas was approved by the Board of Directors of JLCS and JASTRO. This resulted in the first official CT atlas for defining regional lymph node stations in radiotherapy for lung cancer authorized by the JLCS and JASTRO. In conclusion, the JLCS–JASTRO consensus-based CT atlas, which conforms to the IASLC lymph node map, was established. PMID:27609192

Pelvic Normal Tissue Contouring Guidelines for Radiation Therapy: A Radiation Therapy Oncology Group Consensus Panel Atlas

PubMed Central

Gay, Hiram A.; Barthold, H. Joseph; O’Meara, Elizabeth; Bosch, Walter R.; El Naqa, Issam; Al-Lozi, Rawan; Rosenthal, Seth A.; Lawton, Colleen; Lee, W. Robert; Sandler, Howard; Zietman, Anthony; Myerson, Robert; Dawson, Laura A.; Willett, Christopher; Kachnic, Lisa A.; Jhingran, Anuja; Portelance, Lorraine; Ryu, Janice; Small, William; Gaffney, David; Viswanathan, Akila N.; Michalski, Jeff M.

2012-01-01

Purpose To define a male and female pelvic normal tissue contouring atlas for Radiation Therapy Oncology Group (RTOG) trials. Methods and Materials One male pelvis computed tomography (CT) data set and one female pelvis CT data set were shared via the Image-Guided Therapy QA Center. A total of 16 radiation oncologists participated. The following organs at risk were contoured in both CT sets: anus, anorectum, rectum (gastrointestinal and genitourinary definitions), bowel NOS (not otherwise specified), small bowel, large bowel, and proximal femurs. The following were contoured in the male set only: bladder, prostate, seminal vesicles, and penile bulb. The following were contoured in the female set only: uterus, cervix, and ovaries. A computer program used the binomial distribution to generate 95% group consensus contours. These contours and definitions were then reviewed by the group and modified. Results The panel achieved consensus definitions for pelvic normal tissue contouring in RTOG trials with these standardized names: Rectum, AnoRectum, SmallBowel, Colon, BowelBag, Bladder, UteroCervix, Adnexa_R, Adnexa_L, Prostate, SeminalVesc, PenileBulb, Femur_R, and Femur_L. Two additional normal structures whose purpose is to serve as targets in anal and rectal cancer were defined: AnoRectumSig and Mesorectum. Detailed target volume contouring guidelines and images are discussed. Conclusions Consensus guidelines for pelvic normal tissue contouring were reached and are available as a CT image atlas on the RTOG Web site. This will allow uniformity in defining normal tissues for clinical trials delivering pelvic radiation and will facilitate future normal tissue complication research. PMID:22483697

The ATLAS PanDA Pilot in Operation

NASA Astrophysics Data System (ADS)

Nilsson, P.; Caballero, J.; De, K.; Maeno, T.; Stradling, A.; Wenaus, T.; ATLAS Collaboration

2011-12-01

The Production and Distributed Analysis system (PanDA) [1-2] was designed to meet ATLAS [3] requirements for a data-driven workload management system capable of operating at LHC data processing scale. Submitted jobs are executed on worker nodes by pilot jobs sent to the grid sites by pilot factories. This paper provides an overview of the PanDA pilot [4] system and presents major features added in light of recent operational experience, including multi-job processing, advanced job recovery for jobs with output storage failures, gLExec [5-6] based identity switching from the generic pilot to the actual user, and other security measures. The PanDA system serves all ATLAS distributed processing and is the primary system for distributed analysis; it is currently used at over 100 sites worldwide. We analyze the performance of the pilot system in processing real LHC data on the OSG [7], EGI [8] and Nordugrid [9-10] infrastructures used by ATLAS, and describe plans for its evolution.

Congenital bipartite atlas with hypodactyly in a dog: clinical, radiographic and CT findings.

PubMed

Wrzosek, M; Płonek, M; Zeira, O; Bieżyński, J; Kinda, W; Guziński, M

2014-07-01

A three-year-old Border collie was diagnosed with a bipartite atlas and bilateral forelimb hypodactyly. The dog showed signs of acute, non-progressive neck pain, general stiffness and right thoracic limb non-weight-bearing lameness. Computed tomography imaging revealed a bipartite atlas with abaxial vertical bone proliferation, which was the cause of the clinical signs. In addition, bilateral hypodactyly of the second and fifth digits was incidentally found. This report suggests that hypodactyly may be associated with atlas malformations. © 2014 British Small Animal Veterinary Association.

Exploring JavaScript and ROOT technologies to create Web-based ATLAS analysis and monitoring tools

NASA Astrophysics Data System (ADS)

Sánchez Pineda, A.

2015-12-01

We explore the potential of current web applications to create online interfaces that allow the visualization, interaction and real cut-based physics analysis and monitoring of processes through a web browser. The project consists in the initial development of web- based and cloud computing services to allow students and researchers to perform fast and very useful cut-based analysis on a browser, reading and using real data and official Monte- Carlo simulations stored in ATLAS computing facilities. Several tools are considered: ROOT, JavaScript and HTML. Our study case is the current cut-based H → ZZ → llqq analysis of the ATLAS experiment. Preliminary but satisfactory results have been obtained online.

ATLAS, an integrated structural analysis and design system. Volume 3: User's manual, input and execution data

NASA Technical Reports Server (NTRS)

Dreisbach, R. L. (Editor)

1979-01-01

The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.

The evolution of computer monitoring of real time data during the Atlas Centaur launch countdown

NASA Technical Reports Server (NTRS)

Thomas, W. F.

1981-01-01

In the last decade, improvements in computer technology have provided new 'tools' for controlling and monitoring critical missile systems. In this connection, computers have gradually taken a large role in monitoring all flights and ground systems on the Atlas Centaur. The wide body Centaur which will be launched in the Space Shuttle Cargo Bay will use computers to an even greater extent. It is planned to use the wide body Centaur to boost the Galileo spacecraft toward Jupiter in 1985. The critical systems which must be monitored prior to liftoff are examined. Computers have now been programmed to monitor all critical parameters continuously. At this time, there are two separate computer systems used to monitor these parameters.

Bone Age Assessment of Children using a Digital Hand Atlas

PubMed Central

Gertych, Arkadiusz; Zhang, Aifeng; Sayre, James; Pospiech-Kurkowska, Sylwia; Huang, H.K

2007-01-01

We have developed an automated method to assess bone age of children using a digital hand atlas. The hand Atlas consists of two components. The first component is a database which is comprised of a collection of 1,400 digitized left hand radiographs from evenly distributed normally developed children of Caucasian (CA), Asian (AS), African-American (AA) and Hispanic (HI) origin, male (M) and female (F), ranged from 1 to 18 year old; and relevant patient demographic data along with pediatric radiologists' readings of each radiograph. This data is separate into eight categories: CAM, CAF, AAM, AAF, HIM, HIF, ASM, and ASF. In addition, CAM, AAM, HIM, and ASM are combined as one male category; and CAF, AAF, HIF, and ASF are combined as one female category. The male and female are further combined as the F & M category. The second component is a computer-assisted diagnosis (CAD) module to assess a child bone age based on the collected data. The CAD method is derived from features extracted from seven regions of interest (ROIs): the carpal bone ROI, and six phanlangeal PROIs. The PROIs are six areas including the distal and middle regions of three middle fingers. These features were used to train the eleven category fuzzy classifiers: one for each race and gender, one for the female, one male, and one F & M, to assess the bone age of a child. The digital hand atlas is being integrated with a PACS for validation of clinical use. PMID:17387000

Sex-Related Differences in the Developmental Morphology of the Atlas: A Computed Tomography Study.

PubMed

Asukai, Mitsuru; Fujita, Tomotada; Suzuki, Daisuke; Nishida, Tatsuya; Ohishi, Tsuyoshi; Matsuyama, Yukihiro

2018-05-15

A retrospective study. To elucidate sex-related differences in the age at synchondroses closure, the normative size of the atlas, and the ossification patterns of the atlas in Japanese children. The atlas develops from three ossification centers during childhood. The anterior and posterior synchondroses, which are separate ossification centers, mimic fracture lines on computed tomography (CT). Sex-related differences of age dependent morphological changes of the atlas in a large sample size have not been reported. This study analyzed data of 688 subjects (449 boys) between 0 and 18 years old who underwent CT examination of the head and/or neck between January 2010 and July 2016. The age at synchondroses closure, anteroposterior outer, inner, and spinal canal widths of the atlas, and variations of the ossification centers were examined. Anterior synchondroses closed by 10 years in boys and by 7 years in girls. Significant earlier closure of anterior synchondroses was observed in girls than in boys (P < 0.05 at 4 and 5 years old). Posterior synchondrosis closed by 6 years in boys and by 5 years in girls. The outer, inner, and spinal canal widths increased up to 10 to 15 years in both sexes, although all three parameters in girls peaked 3 years earlier than those in boys. All parameters in boys were significantly larger than those in girls, except in the 10- to 12-year-old age category. Two or more ossification centers in the anterior arch were observed in 18.3% subjects, and 6% had midline ossification centers in the posterior arch of the atlas. Distinct sex-related differences in the age at anterior synchondroses closure and the size of the atlas were observed in Japanese children. Knowledge of morphological features of the atlas could help distinguish fractures from synchondroses. 3.

Atlas Fractures and Atlas Osteosynthesis: A Comprehensive Narrative Review.

PubMed

Kandziora, Frank; Chapman, Jens R; Vaccaro, Alexander R; Schroeder, Gregory D; Scholz, Matti

2017-09-01

Most atlas fractures are the result of compression forces. They are often combined with fractures of the axis and especially with the odontoid process. Multiple classification systems for atlas fractures have been described. For an adequate diagnosis, a computed tomography is mandatory. To distinguish between stable and unstable atlas injury, it is necessary to evaluate the integrity of the transverse atlantal ligament (TAL) by magnetic resonance imaging and to classify the TAL lesion. Studies comparing conservative and operative management of unstable atlas fractures are unfortunately not available in the literature; neither are studies comparing different operative treatment strategies. Hence all treatment recommendations are based on low level evidence. Most of atlas fractures are stable and will be successfully managed by immobilization in a soft/hard collar. Unstable atlas fractures may be treated conservatively by halo-fixation, but nowadays more and more surgeons prefer surgery because of the potential discomfort and complications of halo-traction. Atlas fractures with a midsubstance ligamentous disruption of TAL or severe bony ligamentous avulsion can be treated by a C1/2 fusion. Unstable atlas fractures with moderate bony ligamentous avulsion may be treated by atlas osteosynthesis. Although the evidence for the different treatment strategies of atlas fractures is low, atlas osteosynthesis has the potential to change treatment philosophies. The reasons for this are described in this review.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

Big Data Tools as Applied to ATLAS Event Data

NASA Astrophysics Data System (ADS)

Vukotic, I.; Gardner, R. W.; Bryant, L. A.

2017-10-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Logfiles, database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and associated analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data. Such modes would simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning environments and tools like Spark, Jupyter, R, SciPy, Caffe, TensorFlow, etc. Machine learning challenges such as the Higgs Boson Machine Learning Challenge, the Tracking challenge, Event viewers (VP1, ATLANTIS, ATLASrift), and still to be developed educational and outreach tools would be able to access the data through a simple REST API. In this preliminary investigation we focus on derived xAOD data sets. These are much smaller than the primary xAODs having containers, variables, and events of interest to a particular analysis. Being encouraged with the performance of Elasticsearch for the ADC analytics platform, we developed an algorithm for indexing derived xAOD event data. We have made an appropriate document mapping and have imported a full set of standard model W/Z datasets. We compare the disk space efficiency of this approach to that of standard ROOT files, the performance in simple cut flow type of data analysis, and will present preliminary results on its scaling characteristics with different numbers of clients, query complexity, and size of the data retrieved.

Mapping Patterns of Ipsilateral Supraclavicular Nodal Metastases in Breast Cancer: Rethinking the Clinical Target Volume for High-risk Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jing, Hao; Wang, Shu-Lian, E-mail: wsl20040118@yahoo.com; Li, Jing

2015-10-01

Purpose: To map the location of metastatic supraclavicular (SCV) lymph nodes (LNMs) in breast cancer patients with SCV node involvement and determine whether and where the radiation therapy clinical target volume (CTV) of this region could be modified in high-risk subsets. Methods and Materials: Fifty-five patients with metastatic SCV LNMs were eligible for geographic mapping and atlas coverage analysis. All LNMs and their epicenters were registered proportionally by referencing the surrounding landmarks onto simulation computed tomography images of a standard patient. CTVs based on selected SCV atlases, including the one by the Radiation Therapy Oncology Group (RTOG) were contoured. Amore » modified SCV CTV was tried and shown to have better involved-node coverage and thus theoretically improved prophylaxis in this setting. Results: A total of 50 (91%) and 45 (81.8%) patients had LNMs in the medial and lateral SCV subregions, respectively. Also, 36 patients (65.5%) had LNMs located at the junction of the jugular-subclavian veins. All nodes were covered in only 25.5% to 41.8% of patients by different atlases. The RTOG atlas covered all nodes in 25.5% of patients. Stratified by the nodes in all the patients as a whole, 49.2% to 81.3% were covered, and the RTOG atlas covered 62.6%. The lateral and posterior borders were the most overlooked locations. Modification by extending the borders to natural anatomic barriers allowed the new CTV to cover all the nodes in 81.8% of patients and encompass 96.1% of all the nodes. Conclusions: According to the distribution of SCV LNMs, the extent of existing atlases might not be adequate for potential metastatic sites in certain groups of patients. The extension of the lateral and posterior CTV borders in high-risk or recurrent patients might be a reasonable approach for increasing coverage. However, additional data in more homogeneous populations with localized disease are needed before routine application.« less

Computed tomographic atlas for the new international lymph node map for lung cancer: A radiation oncologist perspective.

PubMed

Lynch, Rod; Pitson, Graham; Ball, David; Claude, Line; Sarrut, David

2013-01-01

To develop a reproducible definition for each mediastinal lymph node station based on the new TNM classification for lung cancer. This paper proposes an atlas using the new international lymph node map used in the seventh edition of the TNM classification for lung cancer. Four radiation oncologists and 1 diagnostic radiologist were involved in the project to put forward a reproducible radiologic description for the lung lymph node stations. The International Association for the Study of Lung Cancer lymph node definitions for stations 1 to 11 have been described and illustrated on axial computed tomographic scan images using a certified radiotherapy planning system. This atlas will assist both diagnostic radiologists and radiation oncologists in accurately defining the lymph node stations on computed tomographic scan in patients diagnosed with lung cancer. Copyright © 2013 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

A four-dimensional motion field atlas of the tongue from tagged and cine magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Xing, Fangxu; Prince, Jerry L.; Stone, Maureen; Wedeen, Van J.; El Fakhri, Georges; Woo, Jonghye

2017-02-01

Representation of human tongue motion using three-dimensional vector fields over time can be used to better understand tongue function during speech, swallowing, and other lingual behaviors. To characterize the inter-subject variability of the tongue's shape and motion of a population carrying out one of these functions it is desirable to build a statistical model of the four-dimensional (4D) tongue. In this paper, we propose a method to construct a spatio-temporal atlas of tongue motion using magnetic resonance (MR) images acquired from fourteen healthy human subjects. First, cine MR images revealing the anatomical features of the tongue are used to construct a 4D intensity image atlas. Second, tagged MR images acquired to capture internal motion are used to compute a dense motion field at each time frame using a phase-based motion tracking method. Third, motion fields from each subject are pulled back to the cine atlas space using the deformation fields computed during the cine atlas construction. Finally, a spatio-temporal motion field atlas is created to show a sequence of mean motion fields and their inter-subject variation. The quality of the atlas was evaluated by deforming cine images in the atlas space. Comparison between deformed and original cine images showed high correspondence. The proposed method provides a quantitative representation to observe the commonality and variability of the tongue motion field for the first time, and shows potential in evaluation of common properties such as strains and other tensors based on motion fields.

A Four-dimensional Motion Field Atlas of the Tongue from Tagged and Cine Magnetic Resonance Imaging.

PubMed

Xing, Fangxu; Prince, Jerry L; Stone, Maureen; Wedeen, Van J; Fakhri, Georges El; Woo, Jonghye

2017-01-01

Representation of human tongue motion using three-dimensional vector fields over time can be used to better understand tongue function during speech, swallowing, and other lingual behaviors. To characterize the inter-subject variability of the tongue's shape and motion of a population carrying out one of these functions it is desirable to build a statistical model of the four-dimensional (4D) tongue. In this paper, we propose a method to construct a spatio-temporal atlas of tongue motion using magnetic resonance (MR) images acquired from fourteen healthy human subjects. First, cine MR images revealing the anatomical features of the tongue are used to construct a 4D intensity image atlas. Second, tagged MR images acquired to capture internal motion are used to compute a dense motion field at each time frame using a phase-based motion tracking method. Third, motion fields from each subject are pulled back to the cine atlas space using the deformation fields computed during the cine atlas construction. Finally, a spatio-temporal motion field atlas is created to show a sequence of mean motion fields and their inter-subject variation. The quality of the atlas was evaluated by deforming cine images in the atlas space. Comparison between deformed and original cine images showed high correspondence. The proposed method provides a quantitative representation to observe the commonality and variability of the tongue motion field for the first time, and shows potential in evaluation of common properties such as strains and other tensors based on motion fields.

Implementation of Grid Tier 2 and Tier 3 facilities on a Distributed OpenStack Cloud

NASA Astrophysics Data System (ADS)

Limosani, Antonio; Boland, Lucien; Coddington, Paul; Crosby, Sean; Huang, Joanna; Sevior, Martin; Wilson, Ross; Zhang, Shunde

2014-06-01

The Australian Government is making a AUD 100 million investment in Compute and Storage for the academic community. The Compute facilities are provided in the form of 30,000 CPU cores located at 8 nodes around Australia in a distributed virtualized Infrastructure as a Service facility based on OpenStack. The storage will eventually consist of over 100 petabytes located at 6 nodes. All will be linked via a 100 Gb/s network. This proceeding describes the development of a fully connected WLCG Tier-2 grid site as well as a general purpose Tier-3 computing cluster based on this architecture. The facility employs an extension to Torque to enable dynamic allocations of virtual machine instances. A base Scientific Linux virtual machine (VM) image is deployed in the OpenStack cloud and automatically configured as required using Puppet. Custom scripts are used to launch multiple VMs, integrate them into the dynamic Torque cluster and to mount remote file systems. We report on our experience in developing this nation-wide ATLAS and Belle II Tier 2 and Tier 3 computing infrastructure using the national Research Cloud and storage facilities.

DISTRIBUTED CONTROL AND DA FOR ATLAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

D. SCUDDER; ET AL

1999-05-01

The control system for the Atlas pulsed power generator being built at Los Alamos National Laboratory will utilize a significant level of distributed control. Other principal design characteristics include noise immunity, modularity and use of commercial products wherever possible. The data acquisition system is tightly coordinated with the control system. Both share a common database server and a fiber-optic ethernet communications backbone.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-02-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation.

Microallopatry caused strong diversification in Buthus scorpions (Scorpiones: Buthidae) in the Atlas Mountains (NW Africa).

PubMed

Habel, Jan C; Husemann, Martin; Schmitt, Thomas; Zachos, Frank E; Honnen, Ann-Christin; Petersen, Britt; Parmakelis, Aristeidis; Stathi, Iasmi

2012-01-01

The immense biodiversity of the Atlas Mountains in North Africa might be the result of high rates of microallopatry caused by mountain barriers surpassing 4000 meters leading to patchy habitat distributions. We test the influence of geographic structures on the phylogenetic patterns among Buthus scorpions using mtDNA sequences. We sampled 91 individuals of the genus Buthus from 51 locations scattered around the Atlas Mountains (Antiatlas, High Atlas, Middle Atlas and Jebel Sahro). We sequenced 452 bp of the Cytochrome Oxidase I gene which proved to be highly variable within and among Buthus species. Our phylogenetic analysis yielded 12 distinct genetic groups one of which comprised three subgroups mostly in accordance with the orographic structure of the mountain systems. Main clades overlap with each other, while subclades are distributed parapatrically. Geographic structures likely acted as long-term barriers among populations causing restriction of gene flow and allowing for strong genetic differentiation. Thus, genetic structure and geographical distribution of genetic (sub)clusters follow the classical theory of allopatric differentiation where distinct groups evolve without range overlap until reproductive isolation and ecological differentiation has built up. Philopatry and low dispersal ability of Buthus scorpions are the likely causes for the observed strong genetic differentiation at this small geographic scale.

Microallopatry Caused Strong Diversification in Buthus scorpions (Scorpiones: Buthidae) in the Atlas Mountains (NW Africa)

PubMed Central

Habel, Jan C.; Husemann, Martin; Schmitt, Thomas; Zachos, Frank E.; Honnen, Ann-Christin; Petersen, Britt; Parmakelis, Aristeidis; Stathi, Iasmi

2012-01-01

The immense biodiversity of the Atlas Mountains in North Africa might be the result of high rates of microallopatry caused by mountain barriers surpassing 4000 meters leading to patchy habitat distributions. We test the influence of geographic structures on the phylogenetic patterns among Buthus scorpions using mtDNA sequences. We sampled 91 individuals of the genus Buthus from 51 locations scattered around the Atlas Mountains (Antiatlas, High Atlas, Middle Atlas and Jebel Sahro). We sequenced 452 bp of the Cytochrome Oxidase I gene which proved to be highly variable within and among Buthus species. Our phylogenetic analysis yielded 12 distinct genetic groups one of which comprised three subgroups mostly in accordance with the orographic structure of the mountain systems. Main clades overlap with each other, while subclades are distributed parapatrically. Geographic structures likely acted as long-term barriers among populations causing restriction of gene flow and allowing for strong genetic differentiation. Thus, genetic structure and geographical distribution of genetic (sub)clusters follow the classical theory of allopatric differentiation where distinct groups evolve without range overlap until reproductive isolation and ecological differentiation has built up. Philopatry and low dispersal ability of Buthus scorpions are the likely causes for the observed strong genetic differentiation at this small geographic scale. PMID:22383951

Optimisation of the usage of LHC and local computing resources in a multidisciplinary physics department hosting a WLCG Tier-2 centre

NASA Astrophysics Data System (ADS)

Barberis, Stefano; Carminati, Leonardo; Leveraro, Franco; Mazza, Simone Michele; Perini, Laura; Perlz, Francesco; Rebatto, David; Tura, Ruggero; Vaccarossa, Luca; Villaplana, Miguel

2015-12-01

We present the approach of the University of Milan Physics Department and the local unit of INFN to allow and encourage the sharing among different research areas of computing, storage and networking resources (the largest ones being those composing the Milan WLCG Tier-2 centre and tailored to the needs of the ATLAS experiment). Computing resources are organised as independent HTCondor pools, with a global master in charge of monitoring them and optimising their usage. The configuration has to provide satisfactory throughput for both serial and parallel (multicore, MPI) jobs. A combination of local, remote and cloud storage options are available. The experience of users from different research areas operating on this shared infrastructure is discussed. The promising direction of improving scientific computing throughput by federating access to distributed computing and storage also seems to fit very well with the objectives listed in the European Horizon 2020 framework for research and development.

Three-dimensional Talairach-Tournoux brain atlas

NASA Astrophysics Data System (ADS)

Fang, Anthony; Nowinski, Wieslaw L.; Nguyen, Bonnie T.; Bryan, R. Nick

1995-04-01

The Talairach-Tournoux Stereotaxic Atlas of the human brain is a frequently consulted resource in stereotaxic neurosurgery and computer-based neuroradiology. Its primary application lies in the 2-D analysis and interpretation of neurological images. However, for the purpose of the analysis and visualization of shapes and forms, accurate mensuration of volumes, or 3-D models matching, a 3-D representation of the atlas is essential. This paper proposes and describes, along with its difficulties, a 3-D geometric extension of the atlas. We introduce a `zero-potential' surface smoothing technique, along with a space-dependent convolution kernel and space-dependent normalization. The mesh-based atlas structures are hierarchically organized, and anatomically conform to the original atlas. Structures and their constituents can be independently selected and manipulated in real-time within an integrated system. The extended atlas may be navigated by itself, or interactively registered with patient data with the proportional grid system (piecewise linear) transformation. Visualization of the geometric atlas along with patient data gives a remarkable visual `feel' of the biological structures, not usually perceivable to the untrained eyes in conventional 2-D atlas to image analysis.

The Japan Lung Cancer Society-Japanese Society for Radiation Oncology consensus-based computed tomographic atlas for defining regional lymph node stations in radiotherapy for lung cancer.

PubMed

Itazawa, Tomoko; Tamaki, Yukihisa; Komiyama, Takafumi; Nishimura, Yasumasa; Nakayama, Yuko; Ito, Hiroyuki; Ohde, Yasuhisa; Kusumoto, Masahiko; Sakai, Shuji; Suzuki, Kenji; Watanabe, Hirokazu; Asamura, Hisao

2017-01-01

The purpose of this study was to develop a consensus-based computed tomographic (CT) atlas that defines lymph node stations in radiotherapy for lung cancer based on the lymph node map of the International Association for the Study of Lung Cancer (IASLC). A project group in the Japanese Radiation Oncology Study Group (JROSG) initially prepared a draft of the atlas in which lymph node Stations 1-11 were illustrated on axial CT images. Subsequently, a joint committee of the Japan Lung Cancer Society (JLCS) and the Japanese Society for Radiation Oncology (JASTRO) was formulated to revise this draft. The committee consisted of four radiation oncologists, four thoracic surgeons and three thoracic radiologists. The draft prepared by the JROSG project group was intensively reviewed and discussed at four meetings of the committee over several months. Finally, we proposed definitions for the regional lymph node stations and the consensus-based CT atlas. This atlas was approved by the Board of Directors of JLCS and JASTRO. This resulted in the first official CT atlas for defining regional lymph node stations in radiotherapy for lung cancer authorized by the JLCS and JASTRO. In conclusion, the JLCS-JASTRO consensus-based CT atlas, which conforms to the IASLC lymph node map, was established. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

ATLAS, an integrated structural analysis and design system. Volume 2: System design document

NASA Technical Reports Server (NTRS)

Erickson, W. J. (Editor)

1979-01-01

ATLAS is a structural analysis and design system, operational on the Control Data Corporation 6600/CYBER computers. The overall system design, the design of the individual program modules, and the routines in the ATLAS system library are described. The overall design is discussed in terms of system architecture, executive function, data base structure, user program interfaces and operational procedures. The program module sections include detailed code description, common block usage and random access file usage. The description of the ATLAS program library includes all information needed to use these general purpose routines.

A geochemical atlas of South Carolina--an example using data from the National Geochemical Survey

USGS Publications Warehouse

Sutphin, David M.

2005-01-01

National Geochemical Survey data from stream-sediment and soil samples, which have been analyzed using consistent methods, were used to create maps, graphs, and tables that were assembled in a consistent atlas format that characterizes the distribution of major and trace chemical elements in South Carolina. Distribution patterns of the elements in South Carolina may assist mineral exploration, agriculture, waste-disposal-siting issues, health, environmental, and other studies. This atlas is an example of how data from the National Geochemical Survey may be used to identify general or regional patterns of elemental occurrences and to provide a snapshot of element concentration in smaller areas.

The Dutch National Atlas of Public Health.

PubMed

Zwakhals, S L N; Giesbers, H; Mac Gillavry, E; van Boven, P F; van der Veen, A A

2004-09-01

The Dutch National Atlas of Public Health (http://www.zorgatlas.nl) maps the regional distribution of demand and usage of health care, public health status and influencing factors. The Atlas provides answers to locational questions, e. g. 'Where are the highest mortality rates?', 'Where are the longest waiting lists?' and 'Where are hospitals located?' Maps play a pivotal role in the Atlas. Texts, graphics and diagrams support the interpretation of the maps. The information in the Atlas specifically targets policy makers at the Ministry of Health, Welfare and Sport. For them, the Atlas is a tool for problem detection, policy making and policy evaluation. The Atlas is also aimed at all professionals in health care. In practice, also the general public appears to access and use the Atlas. The Atlas is part of the Dutch Public Health Status and Forecasts (PHSF). The PHSF is made by the National Institute of Public Health and the Environment mandated by the Ministry of Health, Welfare and Sport.

Atlas of climate change effects in 150 bird species of the Eastern United States

Treesearch

Stephen Matthews; Raymond O' Connor; Louis R. Iverson; Anantha M. Prasad

2004-01-01

NOTE: Instructions for navigating this publication can be found on the front cover. This atlas documents the current and potential future distribution of 150 common bird species in the Eastern United States. Distribution data for individual species were derived from the Breeding Bird Survey (BBS) from 1981 to 1990. Regression tree analysis was used to model the BBS...

The version control service for the ATLAS data acquisition configuration files

NASA Astrophysics Data System (ADS)

Soloviev, Igor

2012-12-01

The ATLAS experiment at the LHC in Geneva uses a complex and highly distributed Trigger and Data Acquisition system, involving a very large number of computing nodes and custom modules. The configuration of the system is specified by schema and data in more than 1000 XML files, with various experts responsible for updating the files associated with their components. Maintaining an error free and consistent set of XML files proved a major challenge. Therefore a special service was implemented; to validate any modifications; to check the authorization of anyone trying to modify a file; to record who had made changes, plus when and why; and to provide tools to compare different versions of files and to go back to earlier versions if required. This paper provides details of the implementation and exploitation experience, that may be interesting for other applications using many human-readable files maintained by different people, where consistency of the files and traceability of modifications are key requirements.

Monitoring of computing resource utilization of the ATLAS experiment

NASA Astrophysics Data System (ADS)

Rousseau, David; Dimitrov, Gancho; Vukotic, Ilija; Aidel, Osman; Schaffer, Rd; Albrand, Solveig

2012-12-01

Due to the good performance of the LHC accelerator, the ATLAS experiment has seen higher than anticipated levels for both the event rate and the average number of interactions per bunch crossing. In order to respond to these changing requirements, the current and future usage of CPU, memory and disk resources has to be monitored, understood and acted upon. This requires data collection at a fairly fine level of granularity: the performance of each object written and each algorithm run, as well as a dozen per-job variables, are gathered for the different processing steps of Monte Carlo generation and simulation and the reconstruction of both data and Monte Carlo. We present a system to collect and visualize the data from both the online Tier-0 system and distributed grid production jobs. Around 40 GB of performance data are expected from up to 200k jobs per day, thus making performance optimization of the underlying Oracle database of utmost importance.

Rucio, the next-generation Data Management system in ATLAS

NASA Astrophysics Data System (ADS)

Serfon, C.; Barisits, M.; Beermann, T.; Garonne, V.; Goossens, L.; Lassnig, M.; Nairz, A.; Vigne, R.; ATLAS Collaboration

2016-04-01

Rucio is the next-generation of Distributed Data Management (DDM) system benefiting from recent advances in cloud and ;Big Data; computing to address HEP experiments scaling requirements. Rucio is an evolution of the ATLAS DDM system Don Quixote 2 (DQ2), which has demonstrated very large scale data management capabilities with more than 160 petabytes spread worldwide across 130 sites, and accesses from 1,000 active users. However, DQ2 is reaching its limits in terms of scalability, requiring a large number of support staff to operate and being hard to extend with new technologies. Rucio addresses these issues by relying on new technologies to ensure system scalability, cover new user requirements and employ new automation framework to reduce operational overheads. This paper shows the key concepts of Rucio, details the Rucio design, and the technology it employs, the tests that were conducted to validate it and finally describes the migration steps that were conducted to move from DQ2 to Rucio.

QMachine: commodity supercomputing in web browsers.

PubMed

Wilkinson, Sean R; Almeida, Jonas S

2014-06-09

Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics' "Big Data" from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine. QM is an open-sourced, publicly available web service that acts as a messaging system for posting tasks and retrieving results over HTTP. The illustrative application described here distributes the analyses of 20 Streptococcus pneumoniae genomes for shared suffixes. Because all analytical and data retrieval tasks are executed by volunteer machines, few server resources are required. Any modern web browser can submit those tasks and/or volunteer to execute them without installing any extra plugins or programs. A client library provides high-level distribution templates including MapReduce. This stark departure from the current reliance on expensive server hardware running "download and install" software has already gathered substantial community interest, as QM received more than 2.2 million API calls from 87 countries in 12 months. QM was found adequate to deliver the sort of scalable bioinformatics solutions that computation- and data-intensive workflows require. Paradoxically, the sandboxed execution of code by web browsers was also found to enable them, as compute nodes, to address critical privacy concerns that characterize biomedical environments.

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning

NASA Astrophysics Data System (ADS)

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L.

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multiatlas- based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi

2017-05-01

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

Lung lobe segmentation based on statistical atlas and graph cuts

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a novel method that can extract lung lobes by utilizing probability atlas and multilabel graph cuts. Information about pulmonary structures plays very important role for decision of the treatment strategy and surgical planning. The human lungs are divided into five anatomical regions, the lung lobes. Precise segmentation and recognition of lung lobes are indispensable tasks in computer aided diagnosis systems and computer aided surgery systems. A lot of methods for lung lobe segmentation are proposed. However, these methods only target the normal cases. Therefore, these methods cannot extract the lung lobes in abnormal cases, such as COPD cases. To extract lung lobes in abnormal cases, this paper propose a lung lobe segmentation method based on probability atlas of lobe location and multilabel graph cuts. The process consists of three components; normalization based on the patient's physique, probability atlas generation, and segmentation based on graph cuts. We apply this method to six cases of chest CT images including COPD cases. Jaccard index was 79.1%.

Evaluation of atlas-based auto-segmentation software in prostate cancer patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenham, Stuart, E-mail: stuart.greenham@ncahs.health.nsw.gov.au; Dean, Jenna; Fu, Cheuk Kuen Kenneth

2014-09-15

The performance and limitations of an atlas-based auto-segmentation software package (ABAS; Elekta Inc.) was evaluated using male pelvic anatomy as the area of interest. Contours from 10 prostate patients were selected to create atlases in ABAS. The contoured regions of interest were created manually to align with published guidelines and included the prostate, bladder, rectum, femoral heads and external patient contour. Twenty-four clinically treated prostate patients were auto-contoured using a randomised selection of two, four, six, eight or ten atlases. The concordance between the manually drawn and computer-generated contours were evaluated statistically using Pearson's product–moment correlation coefficient (r) and clinicallymore » in a validated qualitative evaluation. In the latter evaluation, six radiation therapists classified the degree of agreement for each structure using seven clinically appropriate categories. The ABAS software generated clinically acceptable contours for the bladder, rectum, femoral heads and external patient contour. For these structures, ABAS-generated volumes were highly correlated with ‘as treated’ volumes, manually drawn; for four atlases, for example, bladder r = 0.988 (P < 0.001), rectum r = 0.739 (P < 0.001) and left femoral head r = 0.560 (P < 0.001). Poorest results were seen for the prostate (r = 0.401, P < 0.05) (four atlases); however this was attributed to the comparison prostate volume being contoured on magnetic resonance imaging (MRI) rather than computed tomography (CT) data. For all structures, increasing the number of atlases did not consistently improve accuracy. ABAS-generated contours are clinically useful for a range of structures in the male pelvis. Clinically appropriate volumes were created, but editing of some contours was inevitably required. The ideal number of atlases to improve generated automatic contours is yet to be determined.« less

Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

PubMed

Dalmış, Mehmet Ufuk; Litjens, Geert; Holland, Katharina; Setio, Arnaud; Mann, Ritse; Karssemeijer, Nico; Gubern-Mérida, Albert

2017-02-01

Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surface detection, have been applied to solve this task. However, applicability of these methods is usually limited by the characteristics of the images used in the study datasets, while breast MRI varies with respect to the different MRI protocols used, in addition to the variability in breast shapes. All this variability, in addition to various MRI artifacts, makes it a challenging task to develop a robust breast and FGT segmentation method using traditional approaches. Therefore, in this study, we investigated the use of a deep-learning approach known as "U-net." We used a dataset of 66 breast MRI's randomly selected from our scientific archive, which includes five different MRI acquisition protocols and breasts from four breast density categories in a balanced distribution. To prepare reference segmentations, we manually segmented breast and FGT for all images using an in-house developed workstation. We experimented with the application of U-net in two different ways for breast and FGT segmentation. In the first method, following the same pipeline used in traditional approaches, we trained two consecutive (2C) U-nets: first for segmenting the breast in the whole MRI volume and the second for segmenting FGT inside the segmented breast. In the second method, we used a single 3-class (3C) U-net, which performs both tasks simultaneously by segmenting the volume into three regions: nonbreast, fat inside the breast, and FGT inside the breast. For comparison, we applied two existing and published methods to our dataset: an atlas-based method and a sheetness-based method. We used Dice Similarity Coefficient (DSC) to measure the performances of the automated methods, with respect to the manual segmentations. Additionally, we computed Pearson's correlation between the breast density values computed based on manual and automated segmentations. The average DSC values for breast segmentation were 0.933, 0.944, 0.863, and 0.848 obtained from 3C U-net, 2C U-nets, atlas-based method, and sheetness-based method, respectively. The average DSC values for FGT segmentation obtained from 3C U-net, 2C U-nets, and atlas-based methods were 0.850, 0.811, and 0.671, respectively. The correlation between breast density values based on 3C U-net and manual segmentations was 0.974. This value was significantly higher than 0.957 as obtained from 2C U-nets (P < 0.0001, Steiger's Z-test with Bonferoni correction) and 0.938 as obtained from atlas-based method (P = 0.0016). In conclusion, we applied a deep-learning method, U-net, for segmenting breast and FGT in MRI in a dataset that includes a variety of MRI protocols and breast densities. Our results showed that U-net-based methods significantly outperformed the existing algorithms and resulted in significantly more accurate breast density computation. © 2016 American Association of Physicists in Medicine.

Pelvic Normal Tissue Contouring Guidelines for Radiation Therapy: A Radiation Therapy Oncology Group Consensus Panel Atlas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gay, Hiram A., E-mail: hgay@radonc.wustl.edu; Barthold, H. Joseph; Beth Israel Deaconess Medical Center, Boston, MA

2012-07-01

Purpose: To define a male and female pelvic normal tissue contouring atlas for Radiation Therapy Oncology Group (RTOG) trials. Methods and Materials: One male pelvis computed tomography (CT) data set and one female pelvis CT data set were shared via the Image-Guided Therapy QA Center. A total of 16 radiation oncologists participated. The following organs at risk were contoured in both CT sets: anus, anorectum, rectum (gastrointestinal and genitourinary definitions), bowel NOS (not otherwise specified), small bowel, large bowel, and proximal femurs. The following were contoured in the male set only: bladder, prostate, seminal vesicles, and penile bulb. The followingmore » were contoured in the female set only: uterus, cervix, and ovaries. A computer program used the binomial distribution to generate 95% group consensus contours. These contours and definitions were then reviewed by the group and modified. Results: The panel achieved consensus definitions for pelvic normal tissue contouring in RTOG trials with these standardized names: Rectum, AnoRectum, SmallBowel, Colon, BowelBag, Bladder, UteroCervix, Adnexa{sub R}, Adnexa{sub L}, Prostate, SeminalVesc, PenileBulb, Femur{sub R}, and Femur{sub L}. Two additional normal structures whose purpose is to serve as targets in anal and rectal cancer were defined: AnoRectumSig and Mesorectum. Detailed target volume contouring guidelines and images are discussed. Conclusions: Consensus guidelines for pelvic normal tissue contouring were reached and are available as a CT image atlas on the RTOG Web site. This will allow uniformity in defining normal tissues for clinical trials delivering pelvic radiation and will facilitate future normal tissue complication research.« less

Construction of 4D high-definition cortical surface atlases of infants: Methods and applications.

PubMed

Li, Gang; Wang, Li; Shi, Feng; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-10-01

In neuroimaging, cortical surface atlases play a fundamental role for spatial normalization, analysis, visualization, and comparison of results across individuals and different studies. However, existing cortical surface atlases created for adults are not suitable for infant brains during the first two postnatal years, which is the most dynamic period of postnatal structural and functional development of the highly-folded cerebral cortex. Therefore, spatiotemporal cortical surface atlases for infant brains are highly desired yet still lacking for accurate mapping of early dynamic brain development. To bridge this significant gap, leveraging our infant-dedicated computational pipeline for cortical surface-based analysis and the unique longitudinal infant MRI dataset acquired in our research center, in this paper, we construct the first spatiotemporal (4D) high-definition cortical surface atlases for the dynamic developing infant cortical structures at seven time points, including 1, 3, 6, 9, 12, 18, and 24 months of age, based on 202 serial MRI scans from 35 healthy infants. For this purpose, we develop a novel method to ensure the longitudinal consistency and unbiasedness to any specific subject and age in our 4D infant cortical surface atlases. Specifically, we first compute the within-subject mean cortical folding by unbiased groupwise registration of longitudinal cortical surfaces of each infant. Then we establish longitudinally-consistent and unbiased inter-subject cortical correspondences by groupwise registration of the geometric features of within-subject mean cortical folding across all infants. Our 4D surface atlases capture both longitudinally-consistent dynamic mean shape changes and the individual variability of cortical folding during early brain development. Experimental results on two independent infant MRI datasets show that using our 4D infant cortical surface atlases as templates leads to significantly improved accuracy for spatial normalization of cortical surfaces across infant individuals, in comparison to the infant surface atlases constructed without longitudinal consistency and also the FreeSurfer adult surface atlas. Moreover, based on our 4D infant surface atlases, for the first time, we reveal the spatially-detailed, region-specific correlation patterns of the dynamic cortical developmental trajectories between different cortical regions during early brain development. Copyright © 2015 Elsevier B.V. All rights reserved.

MRIVIEW: An interactive computational tool for investigation of brain structure and function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranken, D.; George, J.

MRIVIEW is a software system which uses image processing and visualization to provide neuroscience researchers with an integrated environment for combining functional and anatomical information. Key features of the software include semi-automated segmentation of volumetric head data and an interactive coordinate reconciliation method which utilizes surface visualization. The current system is a precursor to a computational brain atlas. We describe features this atlas will incorporate, including methods under development for visualizing brain functional data obtained from several different research modalities.

Federated data storage system prototype for LHC experiments and data intensive science

NASA Astrophysics Data System (ADS)

Kiryanov, A.; Klimentov, A.; Krasnopevtsev, D.; Ryabinkin, E.; Zarochentsev, A.

2017-10-01

Rapid increase of data volume from the experiments running at the Large Hadron Collider (LHC) prompted physics computing community to evaluate new data handling and processing solutions. Russian grid sites and universities’ clusters scattered over a large area aim at the task of uniting their resources for future productive work, at the same time giving an opportunity to support large physics collaborations. In our project we address the fundamental problem of designing a computing architecture to integrate distributed storage resources for LHC experiments and other data-intensive science applications and to provide access to data from heterogeneous computing facilities. Studies include development and implementation of federated data storage prototype for Worldwide LHC Computing Grid (WLCG) centres of different levels and University clusters within one National Cloud. The prototype is based on computing resources located in Moscow, Dubna, Saint Petersburg, Gatchina and Geneva. This project intends to implement a federated distributed storage for all kind of operations such as read/write/transfer and access via WAN from Grid centres, university clusters, supercomputers, academic and commercial clouds. The efficiency and performance of the system are demonstrated using synthetic and experiment-specific tests including real data processing and analysis workflows from ATLAS and ALICE experiments, as well as compute-intensive bioinformatics applications (PALEOMIX) running on supercomputers. We present topology and architecture of the designed system, report performance and statistics for different access patterns and show how federated data storage can be used efficiently by physicists and biologists. We also describe how sharing data on a widely distributed storage system can lead to a new computing model and reformations of computing style, for instance how bioinformatics program running on supercomputers can read/write data from the federated storage.

Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.

PubMed

Spinczyk, Dominik; Krasoń, Agata

2018-05-29

Liver segmentation in computed tomography is required in many clinical applications. The segmentation methods used can be classified according to a number of criteria. One important criterion for method selection is the shape representation of the segmented organ. The aim of the work is automatic liver segmentation using general purpose shape modeling methods. As part of the research, methods based on shape information at various levels of advancement were used. The single atlas based segmentation method was used as the simplest shape-based method. This method is derived from a single atlas using the deformable free-form deformation of the control point curves. Subsequently, the classic and modified Active Shape Model (ASM) was used, using medium body shape models. As the most advanced and main method generalized statistical shape models, Gaussian Process Morphable Models was used, which are based on multi-dimensional Gaussian distributions of the shape deformation field. Mutual information and sum os square distance were used as similarity measures. The poorest results were obtained for the single atlas method. For the ASM method in 10 analyzed cases for seven test images, the Dice coefficient was above 55[Formula: see text], of which for three of them the coefficient was over 70[Formula: see text], which placed the method in second place. The best results were obtained for the method of generalized statistical distribution of the deformation field. The DICE coefficient for this method was 88.5[Formula: see text] CONCLUSIONS: This value of 88.5 [Formula: see text] Dice coefficient can be explained by the use of general-purpose shape modeling methods with a large variance of the shape of the modeled object-the liver and limitations on the size of our training data set, which was limited to 10 cases. The obtained results in presented fully automatic method are comparable with dedicated methods for liver segmentation. In addition, the deforamtion features of the model can be modeled mathematically by using various kernel functions, which allows to segment the liver on a comparable level using a smaller learning set.

Nuclear Computational Low Energy Initiative (NUCLEI)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reddy, Sanjay K.

This is the final report for University of Washington for the NUCLEI SciDAC-3. The NUCLEI -project, as defined by the scope of work, will develop, implement and run codes for large-scale computations of many topics in low-energy nuclear physics. Physics to be studied include the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques to be used include Quantum Monte Carlo, Configuration Interaction, Coupled Cluster, and Density Functional methods. The research program will emphasize areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS andmore » FRIB (nuclear structure and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrino-less double-beta decay and physics beyond the Standard Model), and LANSCE (fission studies).« less

Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects.

PubMed

Schiffler, Patrick; Tenberge, Jan-Gerd; Wiendl, Heinz; Meuth, Sven G

2017-01-01

The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner.

Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects

PubMed Central

Schiffler, Patrick; Tenberge, Jan-Gerd; Wiendl, Heinz; Meuth, Sven G.

2017-01-01

The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner. PMID:28729829

Measurement of the underlying event in jet events from 7 proton-proton collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abajyan, T.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Gonzalez, B. Alvarez; Alviggi, M. G.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Ammosov, V. V.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bangert, A.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belloni, A.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; De Mendizabal, J. Bilbao; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bolnet, N. M.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Branchini, P.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, G.; Brown, J.; Renstrom, P. A. Bruckman de; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Urbán, S. Cabrera; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarda, S.; Cameron, D.; Caminada, L. M.; Armadans, R. Caminal; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cantero, J.; Cantrill, R.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Castaneda-Miranda, E.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Barajas, C. A. Chavez; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; El Moursli, R. Cherkaoui; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Christidi, I. A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collins-Tooth, C.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Muiño, P. Conde; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Ortuzar, M. Crispin; Cristinziani, M.; Crosetti, G.; Cuciuc, C.-M.; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darlea, G. L.; Darmora, S.; Dassoulas, J. A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. 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2014-08-01

Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on of proton-proton collision data collected at a centre-of-mass energy of 7 . Charged-particle mean and densities of all-particle and charged-particle multiplicity and have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 to 800 . The correlation of charged-particle mean with charged-particle multiplicity is also studied, and the densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.

MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera

NASA Astrophysics Data System (ADS)

Wang, Hongkai; Stout, David B.; Taschereau, Richard; Gu, Zheng; Vu, Nam T.; Prout, David L.; Chatziioannou, Arion F.

2012-10-01

This paper introduces a mouse atlas registration system (MARS), composed of a stationary top-view x-ray projector and a side-view optical camera, coupled to a mouse atlas registration algorithm. This system uses the x-ray and optical images to guide a fully automatic co-registration of a mouse atlas with each subject, in order to provide anatomical reference for small animal molecular imaging systems such as positron emission tomography (PET). To facilitate the registration, a statistical atlas that accounts for inter-subject anatomical variations was constructed based on 83 organ-labeled mouse micro-computed tomography (CT) images. The statistical shape model and conditional Gaussian model techniques were used to register the atlas with the x-ray image and optical photo. The accuracy of the atlas registration was evaluated by comparing the registered atlas with the organ-labeled micro-CT images of the test subjects. The results showed excellent registration accuracy of the whole-body region, and good accuracy for the brain, liver, heart, lungs and kidneys. In its implementation, the MARS was integrated with a preclinical PET scanner to deliver combined PET/MARS imaging, and to facilitate atlas-assisted analysis of the preclinical PET images.

MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera.

PubMed

Wang, Hongkai; Stout, David B; Taschereau, Richard; Gu, Zheng; Vu, Nam T; Prout, David L; Chatziioannou, Arion F

2012-10-07

This paper introduces a mouse atlas registration system (MARS), composed of a stationary top-view x-ray projector and a side-view optical camera, coupled to a mouse atlas registration algorithm. This system uses the x-ray and optical images to guide a fully automatic co-registration of a mouse atlas with each subject, in order to provide anatomical reference for small animal molecular imaging systems such as positron emission tomography (PET). To facilitate the registration, a statistical atlas that accounts for inter-subject anatomical variations was constructed based on 83 organ-labeled mouse micro-computed tomography (CT) images. The statistical shape model and conditional Gaussian model techniques were used to register the atlas with the x-ray image and optical photo. The accuracy of the atlas registration was evaluated by comparing the registered atlas with the organ-labeled micro-CT images of the test subjects. The results showed excellent registration accuracy of the whole-body region, and good accuracy for the brain, liver, heart, lungs and kidneys. In its implementation, the MARS was integrated with a preclinical PET scanner to deliver combined PET/MARS imaging, and to facilitate atlas-assisted analysis of the preclinical PET images.

Pc as Physics Computer for Lhc ?

NASA Astrophysics Data System (ADS)

Jarp, Sverre; Simmins, Antony; Tang, Hong; Yaari, R.

In the last five years, we have seen RISC workstations take over the computing scene that was once controlled by mainframes and supercomputers. In this paper we will argue that the same phenomenon might happen again. A project, active since March this year in the Physics Data Processing group, of CERN's CN division is described where ordinary desktop PCs running Windows (NT and 3.11) have been used for creating an environment for running large LHC batch jobs (initially the DICE simulation job of Atlas). The problems encountered in porting both the CERN library and the specific Atlas codes are described together with some encouraging benchmark results when comparing to existing RISC workstations in use by the Atlas collaboration. The issues of establishing the batch environment (Batch monitor, staging software, etc.) are also covered. Finally a quick extrapolation of commodity computing power available in the future is touched upon to indicate what kind of cost envelope could be sufficient for the simulation farms required by the LHC experiments.

Improved ATLAS HammerCloud Monitoring for Local Site Administration

NASA Astrophysics Data System (ADS)

Böhler, M.; Elmsheuser, J.; Hönig, F.; Legger, F.; Mancinelli, V.; Sciacca, G.

2015-12-01

Every day hundreds of tests are run on the Worldwide LHC Computing Grid for the ATLAS, and CMS experiments in order to evaluate the performance and reliability of the different computing sites. All this activity is steered, controlled, and monitored by the HammerCloud testing infrastructure. Sites with failing functionality tests are auto-excluded from the ATLAS computing grid, therefore it is essential to provide a detailed and well organized web interface for the local site administrators such that they can easily spot and promptly solve site issues. Additional functionality has been developed to extract and visualize the most relevant information. The site administrators can now be pointed easily to major site issues which lead to site blacklisting as well as possible minor issues that are usually not conspicuous enough to warrant the blacklisting of a specific site, but can still cause undesired effects such as a non-negligible job failure rate. This paper summarizes the different developments and optimizations of the HammerCloud web interface and gives an overview of typical use cases.

How Data Becomes Physics: Inside the RACF

ScienceCinema

Ernst, Michael; Rind, Ofer; Rajagopalan, Srini; Lauret, Jerome; Pinkenburg, Chris

2018-06-22

The RHIC & ATLAS Computing Facility (RACF) at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory sits at the center of a global computing network. It connects more than 2,500 researchers around the world with the data generated by millions of particle collisions taking place each second at Brookhaven Lab's Relativistic Heavy Ion Collider (RHIC, a DOE Office of Science User Facility for nuclear physics research), and the ATLAS experiment at the Large Hadron Collider in Europe. Watch this video to learn how the people and computing resources of the RACF serve these scientists to turn petabytes of raw data into physics discoveries.

ATLAS, an integrated structural analysis and design system. Volume 5: System demonstration problems

NASA Technical Reports Server (NTRS)

Samuel, R. A. (Editor)

1979-01-01

One of a series of documents describing the ATLAS System for structural analysis and design is presented. A set of problems is described that demonstrate the various analysis and design capabilities of the ATLAS System proper as well as capabilities available by means of interfaces with other computer programs. Input data and results for each demonstration problem are discussed. Results are compared to theoretical solutions or experimental data where possible. Listings of all input data are included.

Scaling up ATLAS Event Service to production levels on opportunistic computing platforms

NASA Astrophysics Data System (ADS)

Benjamin, D.; Caballero, J.; Ernst, M.; Guan, W.; Hover, J.; Lesny, D.; Maeno, T.; Nilsson, P.; Tsulaia, V.; van Gemmeren, P.; Vaniachine, A.; Wang, F.; Wenaus, T.; ATLAS Collaboration

2016-10-01

Continued growth in public cloud and HPC resources is on track to exceed the dedicated resources available for ATLAS on the WLCG. Examples of such platforms are Amazon AWS EC2 Spot Instances, Edison Cray XC30 supercomputer, backfill at Tier 2 and Tier 3 sites, opportunistic resources at the Open Science Grid (OSG), and ATLAS High Level Trigger farm between the data taking periods. Because of specific aspects of opportunistic resources such as preemptive job scheduling and data I/O, their efficient usage requires workflow innovations provided by the ATLAS Event Service. Thanks to the finer granularity of the Event Service data processing workflow, the opportunistic resources are used more efficiently. We report on our progress in scaling opportunistic resource usage to double-digit levels in ATLAS production.

Glance Information System for ATLAS Management

NASA Astrophysics Data System (ADS)

Grael, F. F.; Maidantchik, C.; Évora, L. H. R. A.; Karam, K.; Moraes, L. O. F.; Cirilli, M.; Nessi, M.; Pommès, K.; ATLAS Collaboration

2011-12-01

ATLAS Experiment is an international collaboration where more than 37 countries, 172 institutes and laboratories, 2900 physicists, engineers, and computer scientists plus 700 students participate. The management of this teamwork involves several aspects such as institute contribution, employment records, members' appointment, authors' list, preparation and publication of papers and speakers nomination. Previously, most of the information was accessible by a limited group and developers had to face problems such as different terminology, diverse data modeling, heterogeneous databases and unlike users needs. Moreover, the systems were not designed to handle new requirements. The maintenance has to be an easy task due to the long lifetime experiment and professionals turnover. The Glance system, a generic mechanism for accessing any database, acts as an intermediate layer isolating the user from the particularities of each database. It retrieves, inserts and updates the database independently of its technology and modeling. Relying on Glance, a group of systems were built to support the ATLAS management and operation aspects: ATLAS Membership, ATLAS Appointments, ATLAS Speakers, ATLAS Analysis Follow-Up, ATLAS Conference Notes, ATLAS Thesis, ATLAS Traceability and DSS Alarms Viewer. This paper presents the overview of the Glance information framework and describes the privilege mechanism developed to grant different level of access for each member and system.

High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

NASA Astrophysics Data System (ADS)

Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

2012-09-01

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data, and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.

Atlas Career Path Guidebook: Patterns and Common Practices in Systems Engineers’ Development

DTIC Science & Technology

2018-01-16

Overview of Atlas Proficiency Model .............................................................................. 68 5.1.2. Math /Science/General... Math /Science/General Engineering ................................ 72 Figure 42. Distribution for individuals with highest proficiency self...assessment in Math /Science/General Engineering ..................................................................................... 73 Figure 43

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

PubMed

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

2015-12-23

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.

ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation

PubMed Central

Li, Hai; Fan, Lingzhong; Zhuo, Junjie; Wang, Jiaojian; Zhang, Yu; Yang, Zhengyi; Jiang, Tianzi

2017-01-01

There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation. PMID:28611620

The OSG open facility: A sharing ecosystem

DOE PAGES

Jayatilaka, B.; Levshina, T.; Rynge, M.; ...

2015-12-23

The Open Science Grid (OSG) ties together individual experiments’ computing power, connecting their resources to create a large, robust computing grid, this computing infrastructure started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero. In the years since, the OSG has broadened its focus to also address the needs of other US researchers and increased delivery of Distributed High Through-put Computing (DHTC) to users from a wide variety of disciplines via the OSG Open Facility. Presently, the Open Facility delivers about 100 million computing wall hours per year to researchers whomore » are not already associated with the owners of the computing sites, this is primarily accomplished by harvesting and organizing the temporarily unused capacity (i.e. opportunistic cycles) from the sites in the OSG. Using these methods, OSG resource providers and scientists share computing hours with researchers in many other fields to enable their science, striving to make sure that these computing power used with maximal efficiency. Furthermore, we believe that expanded access to DHTC is an essential tool for scientific innovation and work continues in expanding this service.« less

Automated method for structural segmentation of nasal airways based on cone beam computed tomography

NASA Astrophysics Data System (ADS)

Tymkovych, Maksym Yu.; Avrunin, Oleg G.; Paliy, Victor G.; Filzow, Maksim; Gryshkov, Oleksandr; Glasmacher, Birgit; Omiotek, Zbigniew; DzierŻak, RóŻa; Smailova, Saule; Kozbekova, Ainur

2017-08-01

The work is dedicated to the segmentation problem of human nasal airways using Cone Beam Computed Tomography. During research, we propose a specialized approach of structured segmentation of nasal airways. That approach use spatial information, symmetrisation of the structures. The proposed stages can be used for construction a virtual three dimensional model of nasal airways and for production full-scale personalized atlases. During research we build the virtual model of nasal airways, which can be used for construction specialized medical atlases and aerodynamics researches.

Fine grained event processing on HPCs with the ATLAS Yoda system

NASA Astrophysics Data System (ADS)

Calafiura, Paolo; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Tsulaia, Vakhtang; Van Gemmeren, Peter; Wenaus, Torre

2015-12-01

High performance computing facilities present unique challenges and opportunities for HEP event processing. The massive scale of many HPC systems means that fractionally small utilization can yield large returns in processing throughput. Parallel applications which can dynamically and efficiently fill any scheduling opportunities the resource presents benefit both the facility (maximal utilization) and the (compute-limited) science. The ATLAS Yoda system provides this capability to HEP-like event processing applications by implementing event-level processing in an MPI-based master-client model that integrates seamlessly with the more broadly scoped ATLAS Event Service. Fine grained, event level work assignments are intelligently dispatched to parallel workers to sustain full utilization on all cores, with outputs streamed off to destination object stores in near real time with similarly fine granularity, such that processing can proceed until termination with full utilization. The system offers the efficiency and scheduling flexibility of preemption without requiring the application actually support or employ check-pointing. We will present the new Yoda system, its motivations, architecture, implementation, and applications in ATLAS data processing at several US HPC centers.

Charting molecular free-energy landscapes with an atlas of collective variables

NASA Astrophysics Data System (ADS)

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2016-11-01

Collective variables (CVs) are a fundamental tool to understand molecular flexibility, to compute free energy landscapes, and to enhance sampling in molecular dynamics simulations. However, identifying suitable CVs is challenging, and is increasingly addressed with systematic data-driven manifold learning techniques. Here, we provide a flexible framework to model molecular systems in terms of a collection of locally valid and partially overlapping CVs: an atlas of CVs. The specific motivation for such a framework is to enhance the applicability and robustness of CVs based on manifold learning methods, which fail in the presence of periodicities in the underlying conformational manifold. More generally, using an atlas of CVs rather than a single chart may help us better describe different regions of conformational space. We develop the statistical mechanics foundation for our multi-chart description and propose an algorithmic implementation. The resulting atlas of data-based CVs are then used to enhance sampling and compute free energy surfaces in two model systems, alanine dipeptide and β-D-glucopyranose, whose conformational manifolds have toroidal and spherical topologies.

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases

PubMed Central

Forbes, Jessica L.; Kim, Regina E. Y.; Paulsen, Jane S.; Johnson, Hans J.

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%. PMID:27536233

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases.

PubMed

Forbes, Jessica L; Kim, Regina E Y; Paulsen, Jane S; Johnson, Hans J

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%.

Applying graph theory to protein structures: an atlas of coiled coils.

PubMed

Heal, Jack W; Bartlett, Gail J; Wood, Christopher W; Thomson, Andrew R; Woolfson, Derek N

2018-05-02

To understand protein structure, folding and function fully and to design proteins de novo reliably, we must learn from natural protein structures that have been characterised experimentally. The number of protein structures available is large and growing exponentially, which makes this task challenging. Indeed, computational resources are becoming increasingly important for classifying and analysing this resource. Here, we use tools from graph theory to define an atlas classification scheme for automatically categorising certain protein substructures. Focusing on the α-helical coiled coils, which are ubiquitous protein-structure and protein-protein interaction motifs, we present a suite of computational resources designed for analysing these assemblies. iSOCKET enables interactive analysis of side-chain packing within proteins to identify coiled coils automatically and with considerable user control. Applying a graph theory-based atlas classification scheme to structures identified by iSOCKET gives the Atlas of Coiled Coils, a fully automated, updated overview of extant coiled coils. The utility of this approach is illustrated with the first formal classification of an emerging subclass of coiled coils called α-helical barrels. Furthermore, in the Atlas, the known coiled-coil universe is presented alongside a partial enumeration of the 'dark matter' of coiled-coil structures; i.e., those coiled-coil architectures that are theoretically possible but have not been observed to date, and thus present defined targets for protein design. iSOCKET is available as part of the open-source GitHub repository associated with this work (https://github.com/woolfson-group/isocket). This repository also contains all the data generated when classifying the protein graphs. The Atlas of Coiled Coils is available at: http://coiledcoils.chm.bris.ac.uk/atlas/app.

QMachine: commodity supercomputing in web browsers

PubMed Central

2014-01-01

Background Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics’ “Big Data” from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine. Results QM is an open-sourced, publicly available web service that acts as a messaging system for posting tasks and retrieving results over HTTP. The illustrative application described here distributes the analyses of 20 Streptococcus pneumoniae genomes for shared suffixes. Because all analytical and data retrieval tasks are executed by volunteer machines, few server resources are required. Any modern web browser can submit those tasks and/or volunteer to execute them without installing any extra plugins or programs. A client library provides high-level distribution templates including MapReduce. This stark departure from the current reliance on expensive server hardware running “download and install” software has already gathered substantial community interest, as QM received more than 2.2 million API calls from 87 countries in 12 months. Conclusions QM was found adequate to deliver the sort of scalable bioinformatics solutions that computation- and data-intensive workflows require. Paradoxically, the sandboxed execution of code by web browsers was also found to enable them, as compute nodes, to address critical privacy concerns that characterize biomedical environments. PMID:24913605

Bone age assessment in Hispanic children: digital hand atlas compared with the Greulich and Pyle (G&P) atlas

NASA Astrophysics Data System (ADS)

Fernandez, James Reza; Zhang, Aifeng; Vachon, Linda; Tsao, Sinchai

2008-03-01

Bone age assessment is most commonly performed with the use of the Greulich and Pyle (G&P) book atlas, which was developed in the 1950s. The population of theUnited States is not as homogenous as the Caucasian population in the Greulich and Pyle in the 1950s, especially in the Los Angeles, California area. A digital hand atlas (DHA) based on 1,390 hand images of children of different racial backgrounds (Caucasian, African American, Hispanic, and Asian) aged 0-18 years was collected from Children's Hospital Los Angeles. Statistical analysis discovered significant discrepancies exist between Hispanic and the G&P atlas standard. To validate the usage of DHA as a clinical standard, diagnostic radiologists performed reads on Hispanic pediatric hand and wrist computed radiography images using either the G&P pediatric radiographic atlas or the Children's Hospital Los Angeles Digital Hand Atlas (DHA) as reference. The order in which the atlas is used (G&P followed by DHA or vice versa) for each image was prepared before actual reading begins. Statistical analysis of the results was then performed to determine if a discrepancy exists between the two readings.

Access to the Mars Global Surveyor Data Through the Planetary Image Atlas

NASA Technical Reports Server (NTRS)

Ivanov, A. B.; Duxbury, E. D.; LaVoie, S. K.; McAuley, M.; Woncik, P. J.

2002-01-01

We will present our latest results in providing access to the Mars Global Surveyor Data through the Planetary Image Atlas. This work is a prototype for future Internet based data distribution systems. Additional information is contained in the original extended abstract.

One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI.

PubMed

Arabi, Hossein; Zaidi, Habib

2016-10-01

The outcome of a detailed assessment of various strategies for atlas-based whole-body bone segmentation from magnetic resonance imaging (MRI) was exploited to select the optimal parameters and setting, with the aim of proposing a novel one-registration multi-atlas (ORMA) pseudo-CT generation approach. The proposed approach consists of only one online registration between the target and reference images, regardless of the number of atlas images (N), while for the remaining atlas images, the pre-computed transformation matrices to the reference image are used to align them to the target image. The performance characteristics of the proposed method were evaluated and compared with conventional atlas-based attenuation map generation strategies (direct registration of the entire atlas images followed by voxel-wise weighting (VWW) and arithmetic averaging atlas fusion). To this end, four different positron emission tomography (PET) attenuation maps were generated via arithmetic averaging and VWW scheme using both direct registration and ORMA approaches as well as the 3-class attenuation map obtained from the Philips Ingenuity TF PET/MRI scanner commonly used in the clinical setting. The evaluation was performed based on the accuracy of extracted whole-body bones by the different attenuation maps and by quantitative analysis of resulting PET images compared to CT-based attenuation-corrected PET images serving as reference. The comparison of validation metrics regarding the accuracy of extracted bone using the different techniques demonstrated the superiority of the VWW atlas fusion algorithm achieving a Dice similarity measure of 0.82 ± 0.04 compared to arithmetic averaging atlas fusion (0.60 ± 0.02), which uses conventional direct registration. Application of the ORMA approach modestly compromised the accuracy, yielding a Dice similarity measure of 0.76 ± 0.05 for ORMA-VWW and 0.55 ± 0.03 for ORMA-averaging. The results of quantitative PET analysis followed the same trend with less significant differences in terms of SUV bias, whereas massive improvements were observed compared to PET images corrected for attenuation using the 3-class attenuation map. The maximum absolute bias achieved by VWW and VWW-ORMA methods was 06.4 ± 5.5 in the lung and 07.9 ± 4.8 in the bone, respectively. The proposed algorithm is capable of generating decent attenuation maps. The quantitative analysis revealed a good correlation between PET images corrected for attenuation using the proposed pseudo-CT generation approach and the corresponding CT images. The computational time is reduced by a factor of 1/N at the expense of a modest decrease in quantitative accuracy, thus allowing us to achieve a reasonable compromise between computing time and quantitative performance.

Interactive 3D visualization tools for stereotactic atlas-based functional neurosurgery

NASA Astrophysics Data System (ADS)

St. Jean, Philippe; Kasrai, Reza; Clonda, Diego; Sadikot, Abbas F.; Evans, Alan C.; Peters, Terence M.

1998-06-01

Many of the critical basal ganglia structures are not distinguishable on anatomical magnetic resonance imaging (MRI) scans, even though they differ in functionality. In order to provide the neurosurgeon with this missing information, a deformable volumetric atlas of the basal ganglia has been created from the Shaltenbrand and Wahren atlas of cryogenic slices. The volumetric atlas can be non-linearly deformed to an individual patient's MRI. To facilitate the clinical use of the atlas, a visualization platform has been developed for pre- and intra-operative use which permits manipulation of the merged atlas and MRI data sets in two- and three-dimensional views. The platform includes graphical tools which allow the visualization of projections of the leukotome and other surgical tools with respect to the atlas data, as well as pre- registered images from any other imaging modality. In addition, a graphical interface has been designed to create custom virtual lesions using computer models of neurosurgical tools for intra-operative planning. To date 17 clinical cases have been successfully performed using the described system.

Wind Energy Resource Atlas of Sri Lanka and the Maldives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elliott, D.; Schwartz, M.; Scott, G.

2003-08-01

The Wind Energy Resource Atlas of Sri Lanka and the Maldives, produced by the National Renewable Energy Laboratory's (NREL's) wind resource group identifies the wind characteristics and distribution of the wind resource in Sri Lanka and the Maldives. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications.

An atlas of stellar spectra between 2.00 and 2.45 micrometers (Arnaud, Gilmore, and Collier Cameron 1989)

NASA Technical Reports Server (NTRS)

Warren, Wayne N., Jr.

1990-01-01

The machine-readable version of the atlas, as it is currently being distributed from the Astronomical Data Center, is described. The atlas represent a collection of spectra in the wavelength range 2.00 to 2.45 micros having a resolution of approximately 0.02 micron. The sample of 73 stars includes a supergiant, giants, dwarfs, and subdwarfs with a chemical abundance range of about -2 to +0.5 dex.

Multi atlas based segmentation: Should we prefer the best atlas group over the group of best atlases?

PubMed

Zaffino, Paolo; Ciardo, Delia; Raudaschl, Patrik; Fritscher, Karl; Ricotti, Rosalinda; Alterio, Daniela; Marvaso, Giulia; Fodor, Cristiana; Baroni, Guido; Amato, Francesco; Orecchia, Roberto; Jereczek-Fossa, Barbara Alicja; Sharp, Gregory C; Spadea, Maria Francesca

2018-05-22

Multi Atlas Based Segmentation (MABS) uses a database of atlas images, and an atlas selection process is used to choose an atlas subset for registration and voting. In the current state of the art, atlases are chosen according to a similarity criterion between the target subject and each atlas in the database. In this paper, we propose a new concept for atlas selection that relies on selecting the best performing group of atlases rather than the group of highest scoring individual atlases. Experiments were performed using CT images of 50 patients, with contours of brainstem and parotid glands. The dataset was randomly split in 2 groups: 20 volumes were used as an atlas database and 30 served as target subjects for testing. Classic oracle group selection, where atlases are chosen by the highest Dice Similarity Coefficient (DSC) with the target, was performed. This was compared to oracle Group selection, where all the combinations of atlas subgroups were considered and scored by computing DSC with the target subject. Subsequently, Convolutional Neural Networks (CNNs) were designed to predict the best group of atlases. The results were compared also with the selection strategy based on Normalized Mutual Information (NMI). Oracle group was proved to be significantly better that classic oracle selection (p<10-5). Atlas group selection led to a median±interquartile DSC of 0.740±0.084, 0.718±0.086 and 0.670±0.097 for brainstem and left/right parotid glands respectively, outperforming NMI selection 0.676±0.113, 0.632±0.104 and 0.606±0.118 (p<0.001) as well as classic oracle selection. The implemented methodology is a proof of principle that selecting the atlases by considering the performance of the entire group of atlases instead of each single atlas leads to higher segmentation accuracy, being even better then current oracle strategy. This finding opens a new discussion about the most appropriate atlas selection criterion for MABS. © 2018 Institute of Physics and Engineering in Medicine.

A geochemical atlas of North Carolina, USA

USGS Publications Warehouse

Reid, J.C.

1993-01-01

A geochemical atlas of North Carolina, U.S.A., was prepared using National Uranium Resource Evaluation (NURE) stream-sediment data. Before termination of the NURE program, sampling of nearly the entire state (48,666 square miles of land area) was completed and geochemical analyses were obtained. The NURE data are applicable to mineral exploration, agriculture, waste disposal siting issues, health, and environmental studies. Applications in state government include resource surveys to assist mineral exploration by identifying geochemical anomalies and areas of mineralization. Agriculture seeks to identify areas with favorable (or unfavorable) conditions for plant growth, disease, and crop productivity. Trace elements such as cobalt, copper, chromium, iron, manganese, zinc, and molybdenum must be present within narrow ranges in soils for optimum growth and productivity. Trace elements as a contributing factor to disease are of concern to health professionals. Industry can use pH and conductivity data for water samples to site facilities which require specific water quality. The North Carolina NURE database consists of stream-sediment samples, groundwater samples, and stream-water analyses. The statewide database consists of 6,744 stream-sediment sites, 5,778 groundwater sample sites, and 295 stream-water sites. Neutron activation analyses were provided for U, Br, Cl, F, Mn, Na, Al, V, Dy in groundwater and stream water, and for U, Th, Hf, Ce, Fe, Mn, Na, Sc, Ti, V, Al, Dy, Eu, La, Sm, Yb, and Lu in stream sediments. Supplemental analyses by other techniques were reported on U (extractable), Ag, As, Ba, Be, Ca, Co, Cr, Cu, K, Li, Mg, Mo, Nb, Ni, P, Pb, Se, Sn, Sr, W, Y, and Zn for 4,619 stream-sediment samples. A small subset of 334 stream samples was analyzed for gold. The goal of the atlas was to make available the statewide NURE data with minimal interpretation to enable prospective users to modify and manipulate the data for their end use. The atlas provides only very general indication of geochemical distribution patterns and should not be used for site specific studies. The atlas maps for each element were computer-generated at the state's geographic information system (Center for Geographic Information and Analysis [CGIA]). The Division of Statistics and Information Services provided input files. The maps in the atlas are point maps. Each sample is represented by a symbol generally corresponding to a quartile class. Other reports will transmit sample and analytical data for state regions. Data are tentatively planned to be available on disks in spreadsheet format for personal computers. During the second phase of this project, stream-sediment samples are being assigned to state geologic map unit names using a GIS system to determine background and anomaly values. Subsequent publications will make this geochemical data and accompanying interpretations available to a wide spectrum of interdisciplinary users. ?? 1993.

ATLAS user analysis on private cloud resources at GoeGrid

NASA Astrophysics Data System (ADS)

Glaser, F.; Nadal Serrano, J.; Grabowski, J.; Quadt, A.

2015-12-01

User analysis job demands can exceed available computing resources, especially before major conferences. ATLAS physics results can potentially be slowed down due to the lack of resources. For these reasons, cloud research and development activities are now included in the skeleton of the ATLAS computing model, which has been extended by using resources from commercial and private cloud providers to satisfy the demands. However, most of these activities are focused on Monte-Carlo production jobs, extending the resources at Tier-2. To evaluate the suitability of the cloud-computing model for user analysis jobs, we developed a framework to launch an ATLAS user analysis cluster in a cloud infrastructure on demand and evaluated two solutions. The first solution is entirely integrated in the Grid infrastructure by using the same mechanism, which is already in use at Tier-2: A designated Panda-Queue is monitored and additional worker nodes are launched in a cloud environment and assigned to a corresponding HTCondor queue according to the demand. Thereby, the use of cloud resources is completely transparent to the user. However, using this approach, submitted user analysis jobs can still suffer from a certain delay introduced by waiting time in the queue and the deployed infrastructure lacks customizability. Therefore, our second solution offers the possibility to easily deploy a totally private, customizable analysis cluster on private cloud resources belonging to the university.

Large scale digital atlases in neuroscience

NASA Astrophysics Data System (ADS)

Hawrylycz, M.; Feng, D.; Lau, C.; Kuan, C.; Miller, J.; Dang, C.; Ng, L.

2014-03-01

Imaging in neuroscience has revolutionized our current understanding of brain structure, architecture and increasingly its function. Many characteristics of morphology, cell type, and neuronal circuitry have been elucidated through methods of neuroimaging. Combining this data in a meaningful, standardized, and accessible manner is the scope and goal of the digital brain atlas. Digital brain atlases are used today in neuroscience to characterize the spatial organization of neuronal structures, for planning and guidance during neurosurgery, and as a reference for interpreting other data modalities such as gene expression and connectivity data. The field of digital atlases is extensive and in addition to atlases of the human includes high quality brain atlases of the mouse, rat, rhesus macaque, and other model organisms. Using techniques based on histology, structural and functional magnetic resonance imaging as well as gene expression data, modern digital atlases use probabilistic and multimodal techniques, as well as sophisticated visualization software to form an integrated product. Toward this goal, brain atlases form a common coordinate framework for summarizing, accessing, and organizing this knowledge and will undoubtedly remain a key technology in neuroscience in the future. Since the development of its flagship project of a genome wide image-based atlas of the mouse brain, the Allen Institute for Brain Science has used imaging as a primary data modality for many of its large scale atlas projects. We present an overview of Allen Institute digital atlases in neuroscience, with a focus on the challenges and opportunities for image processing and computation.

Popularity Prediction Tool for ATLAS Distributed Data Management

NASA Astrophysics Data System (ADS)

Beermann, T.; Maettig, P.; Stewart, G.; Lassnig, M.; Garonne, V.; Barisits, M.; Vigne, R.; Serfon, C.; Goossens, L.; Nairz, A.; Molfetas, A.; Atlas Collaboration

2014-06-01

This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

Stress change and fault interaction from a two century-long earthquake sequence in the central Tell Atlas (Algeria)

NASA Astrophysics Data System (ADS)

Kariche, Jughurta; Meghraoui, Mustapha; Ayadi, Abdelhakim; Salah Boughacha, Mohamed

2017-04-01

We study the role and distribution of stress transfer that may trigger destructive earthquakes in the Central Tell Atlas (Algeria). A sequence of historical events reaching Ms 7.3 and related stress tensors with thrust faulting mechanisms allows the modeling of the Coulomb Failure Function (deltaCFF). We explore here the physical parameters for a stress transfer along the Tell thrust-and-fold belt taking into account an eastward trending earthquake migration from 1891 to 2003. The Computation integrated the seismicity rate in the deltaCFF computation, which is in good agreement with the migration seismicity. The stress transfer progression and increase of 0.1 to 0.8 bar are obtained on fault planes at 7-km-depth with a friction coefficient µ' 0.4 showing stress loading lobes on targeted coseismic fault zone and location of stress shadow across other thrust-and-fold regions. The Coulomb modeling suggests a distinction in earthquake triggering between zones with moderate-sized and large earthquake ruptures. Recent InSAR and levelling studies and aftershocks that document postseismic deformation of major earthquakes are integrated into the static stress change calculations. The presence of fluid and related poroelastic deformation can be considered as an open question with regards to their contribution to major earthquakes and their implications in the seismic hazard assessment of northern Algeria.

Toward Mobile Assisted Language Learning Apps for Professionals That Integrate Learning into the Daily Routine

ERIC Educational Resources Information Center

Pareja-Lora, Antonio; Arús-Hita, Jorge; Read, Timothy; Rodríguez-Arancón, Pilar; Calle-Martínez, Cristina; Pomposo, Lourdes; Martín-Monje, Elena; Bárcena, Elena

2013-01-01

In this short paper, we present some initial work on Mobile Assisted Language Learning (MALL) undertaken by the ATLAS research group. ATLAS embraced this multidisciplinary field cutting across Mobile Learning and Computer Assisted Language Learning (CALL) as a natural step in their quest to find learning formulas for professional English that…

Computation of a high-resolution MRI 3D stereotaxic atlas of the sheep brain.

PubMed

Ella, Arsène; Delgadillo, José A; Chemineau, Philippe; Keller, Matthieu

2017-02-15

The sheep model was first used in the fields of animal reproduction and veterinary sciences and then was utilized in fundamental and preclinical studies. For more than a decade, magnetic resonance (MR) studies performed on this model have been increasingly reported, especially in the field of neuroscience. To contribute to MR translational neuroscience research, a brain template and an atlas are necessary. We have recently generated the first complete T1-weighted (T1W) and T2W MR population average images (or templates) of in vivo sheep brains. In this study, we 1) defined a 3D stereotaxic coordinate system for previously established in vivo population average templates; 2) used deformation fields obtained during optimized nonlinear registrations to compute nonlinear tissues or prior probability maps (nlTPMs) of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) tissues; 3) delineated 25 external and 28 internal sheep brain structures by segmenting both templates and nlTPMs; and 4) annotated and labeled these structures using an existing histological atlas. We built a quality high-resolution 3D atlas of average in vivo sheep brains linked to a reference stereotaxic space. The atlas and nlTPMs, associated with previously computed T1W and T2W in vivo sheep brain templates and nlTPMs, provide a complete set of imaging space that are able to be imported into other imaging software programs and could be used as standardized tools for neuroimaging studies or other neuroscience methods, such as image registration, image segmentation, identification of brain structures, implementation of recording devices, or neuronavigation. J. Comp. Neurol. 525:676-692, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Associated production of a quarkonium and a Z boson at one loop in a quark-hadron-duality approach

NASA Astrophysics Data System (ADS)

Lansberg, Jean-Philippe; Shao, Hua-Sheng

2016-10-01

In view of the large discrepancy about the associated production of a prompt J/ψ and a Z boson between the ATLAS data at √{s}=8 TeV and theoretical predictions for Single Parton Scattering (SPS) contributions, we perform an evaluation of the corresponding cross section at one loop accuracy (Next-to-Leading Order, NLO) in a quark-hadron-duality approach, also known as the Colour-Evaporation Model (CEM). This work is motivated by (i) the extremely disparate predictions based on the existing NRQCD fits conjugated with the absence of a full NLO NRQCD computation and (ii) the fact that we believe that such an evaluation provides a likely upper limit of the SPS cross section. In addition to these theory improvements, we argue that the ATLAS estimation of the Double Parton Scattering (DPS) yield may be underestimated by a factor as large as 3 which then reduces the size of the SPS yield extracted from the ATLAS data. Our NLO SPS evaluation also allows us to set an upper limit on σ eff driving the size of the DPS yield. Overall, the discrepancy between theory and experiment may be smaller than expected, which calls for further analyses by ATLAS and CMS, for which we provide predictions, and for full NLO computations in other models. As an interesting side product of our analysis, we have performed the first NLO computation of dσ /dP T for prompt single- J/ψ production in the CEM from which we have fit the CEM non-pertubative parameter at NLO using the most recent ATLAS data.

Distributed data analysis in ATLAS

NASA Astrophysics Data System (ADS)

Nilsson, Paul; Atlas Collaboration

2012-12-01

Data analysis using grid resources is one of the fundamental challenges to be addressed before the start of LHC data taking. The ATLAS detector will produce petabytes of data per year, and roughly one thousand users will need to run physics analyses on this data. Appropriate user interfaces and helper applications have been made available to ensure that the grid resources can be used without requiring expertise in grid technology. These tools enlarge the number of grid users from a few production administrators to potentially all participating physicists. ATLAS makes use of three grid infrastructures for the distributed analysis: the EGEE sites, the Open Science Grid, and Nordu Grid. These grids are managed by the gLite workload management system, the PanDA workload management system, and ARC middleware; many sites can be accessed via both the gLite WMS and PanDA. Users can choose between two front-end tools to access the distributed resources. Ganga is a tool co-developed with LHCb to provide a common interface to the multitude of execution backends (local, batch, and grid). The PanDA workload management system provides a set of utilities called PanDA Client; with these tools users can easily submit Athena analysis jobs to the PanDA-managed resources. Distributed data is managed by Don Quixote 2, a system developed by ATLAS; DQ2 is used to replicate datasets according to the data distribution policies and maintains a central catalog of file locations. The operation of the grid resources is continually monitored by the Ganga Robot functional testing system, and infrequent site stress tests are performed using the Hammer Cloud system. In addition, the DAST shift team is a group of power users who take shifts to provide distributed analysis user support; this team has effectively relieved the burden of support from the developers.

Distribution Atlas of Proliferating Bone Marrow in Non-Small Cell Lung Cancer Patients Measured by FLT-PET/CT Imaging, With Potential Applicability in Radiation Therapy Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, Belinda A., E-mail: Belinda.Campbell@petermac.org; Callahan, Jason; Bressel, Mathias

Purpose: Proliferating bone marrow is exquisitely sensitive to ionizing radiation. Knowledge of its distribution could improve radiation therapy planning to minimize unnecessary marrow exposure and avoid consequential prolonged myelosuppression. [18F]-Fluoro-3-deoxy-3-L-fluorothymidine (FLT)–positron emission tomography (PET) is a novel imaging modality that provides detailed quantitative images of proliferating tissues, including bone marrow. We used FLT-PET imaging in cancer patients to produce an atlas of marrow distribution with potential clinical utility. Methods and Materials: The FLT-PET and fused CT scans of eligible patients with non-small cell lung cancer (no distant metastases, no prior cytotoxic exposure, no hematologic disorders) were reviewed. The proportions of skeletalmore » FLT activity in 10 predefined bony regions were determined and compared according to age, sex, and recent smoking status. Results: Fifty-one patients were studied: 67% male; median age 68 (range, 31-87) years; 8% never smokers; 70% no smoking in the preceding 3 months. Significant differences in marrow distribution occurred between sex and age groups. No effect was detected from smoking in the preceding 3 months. Using the mean percentages of FLT uptake per body region, we created an atlas of the distribution of functional bone marrow in 4 subgroups defined by sex and age. Conclusions: This atlas has potential utility for estimating the distribution of active marrow in adult cancer patients to guide radiation therapy planning. However, because of interindividual variation it should be used with caution when radiation therapy risks ablating large proportions of active marrow; in such cases, individual FLT-PET scans may be required.« less

Lunar Orbiter 4 - Photographic Mission Summary. Volume 1

NASA Technical Reports Server (NTRS)

1968-01-01

Photographic summary report of Lunar Orbiter 4 mission. The fourth of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 22:25 GMT on May 4, 1967. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena-spacecraft combination was boosted to the proper coast ellipse by the Atlas booster prior to separation. Final maneuvering and acceleration to the velocity required to maintain the 100-nauticalmile- altitude Earth orbit was controlled by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver and engine-burn period required to inject the spacecraft on the cislunar trajectory 20 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the boost trajectory.

The benefits of the Atlas of Human Cardiac Anatomy website for the design of cardiac devices.

PubMed

Spencer, Julianne H; Quill, Jason L; Bateman, Michael G; Eggen, Michael D; Howard, Stephen A; Goff, Ryan P; Howard, Brian T; Quallich, Stephen G; Iaizzo, Paul A

2013-11-01

This paper describes how the Atlas of Human Cardiac Anatomy website can be used to improve cardiac device design throughout the process of development. The Atlas is a free-access website featuring novel images of both functional and fixed human cardiac anatomy from over 250 human heart specimens. This website provides numerous educational tutorials on anatomy, physiology and various imaging modalities. For instance, the 'device tutorial' provides examples of devices that were either present at the time of in vitro reanimation or were subsequently delivered, including leads, catheters, valves, annuloplasty rings and stents. Another section of the website displays 3D models of the vasculature, blood volumes and/or tissue volumes reconstructed from computed tomography and magnetic resonance images of various heart specimens. The website shares library images, video clips and computed tomography and MRI DICOM files in honor of the generous gifts received from donors and their families.

Lunar Orbiter 5. Photographic Mission Summary. Volume 1

NASA Technical Reports Server (NTRS)

1968-01-01

Selected photographs and mission summary of Lunar Orbiter 5. The last of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 22:33 GMT on August 1, 1967. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena-spacecraft combination was boosted to the proper coast ellipse by the Atlas booster prior to separation. Final maneuvering and acceleration to the velocity required to maintain the 100-nautical-mile-altitude Earth orbit were controlled by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver and engine-bum period required to inject the spacecraft on the cislunar trajectory about 33 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the boost trajectory.

Diffeomorphic Sulcal Shape Analysis on the Cortex

PubMed Central

Joshi, Shantanu H.; Cabeen, Ryan P.; Joshi, Anand A.; Sun, Bo; Dinov, Ivo; Narr, Katherine L.; Toga, Arthur W.; Woods, Roger P.

2014-01-01

We present a diffeomorphic approach for constructing intrinsic shape atlases of sulci on the human cortex. Sulci are represented as square-root velocity functions of continuous open curves in ℝ3, and their shapes are studied as functional representations of an infinite-dimensional sphere. This spherical manifold has some advantageous properties – it is equipped with a Riemannian metric on the tangent space and facilitates computational analyses and correspondences between sulcal shapes. Sulcal shape mapping is achieved by computing geodesics in the quotient space of shapes modulo scales, translations, rigid rotations and reparameterizations. The resulting sulcal shape atlas preserves important local geometry inherently present in the sample population. The sulcal shape atlas is integrated in a cortical registration framework and exhibits better geometric matching compared to the conventional euclidean method. We demonstrate experimental results for sulcal shape mapping, cortical surface registration, and sulcal classification for two different surface extraction protocols for separate subject populations. PMID:22328177

Lunar Orbiter 3 - Photographic Mission Summary

NASA Technical Reports Server (NTRS)

1968-01-01

Systems performance, lunar photography, and launch operations of Lunar Orbiter 3 photographic mission. The third of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 01:17 GMT on February 5,1967. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena-spacecraft combination was boosted to the proper coast ellipse by the Atlas booster prior to separation. Final 1 maneuvering and acceleration to the velocity required to maintain the 100-nautical-milealtitude Earth orbit was controlled by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver and engine-burn period required to inject the spacecraft on the cislunar trajectory 20 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the entire boost trajectory.

Segmenting the thoracic, abdominal and pelvic musculature on CT scans combining atlas-based model and active contour model

NASA Astrophysics Data System (ADS)

Zhang, Weidong; Liu, Jiamin; Yao, Jianhua; Summers, Ronald M.

2013-03-01

Segmentation of the musculature is very important for accurate organ segmentation, analysis of body composition, and localization of tumors in the muscle. In research fields of computer assisted surgery and computer-aided diagnosis (CAD), muscle segmentation in CT images is a necessary pre-processing step. This task is particularly challenging due to the large variability in muscle structure and the overlap in intensity between muscle and internal organs. This problem has not been solved completely, especially for all of thoracic, abdominal and pelvic regions. We propose an automated system to segment the musculature on CT scans. The method combines an atlas-based model, an active contour model and prior segmentation of fat and bones. First, body contour, fat and bones are segmented using existing methods. Second, atlas-based models are pre-defined using anatomic knowledge at multiple key positions in the body to handle the large variability in muscle shape. Third, the atlas model is refined using active contour models (ACM) that are constrained using the pre-segmented bone and fat. Before refining using ACM, the initialized atlas model of next slice is updated using previous atlas. The muscle is segmented using threshold and smoothed in 3D volume space. Thoracic, abdominal and pelvic CT scans were used to evaluate our method, and five key position slices for each case were selected and manually labeled as the reference. Compared with the reference ground truth, the overlap ratio of true positives is 91.1%+/-3.5%, and that of false positives is 5.5%+/-4.2%.

Monitoring of computing resource use of active software releases at ATLAS

NASA Astrophysics Data System (ADS)

Limosani, Antonio; ATLAS Collaboration

2017-10-01

The LHC is the world’s most powerful particle accelerator, colliding protons at centre of mass energy of 13 TeV. As the energy and frequency of collisions has grown in the search for new physics, so too has demand for computing resources needed for event reconstruction. We will report on the evolution of resource usage in terms of CPU and RAM in key ATLAS offline reconstruction workflows at the TierO at CERN and on the WLCG. Monitoring of workflows is achieved using the ATLAS PerfMon package, which is the standard ATLAS performance monitoring system running inside Athena jobs. Systematic daily monitoring has recently been expanded to include all workflows beginning at Monte Carlo generation through to end-user physics analysis, beyond that of event reconstruction. Moreover, the move to a multiprocessor mode in production jobs has facilitated the use of tools, such as “MemoryMonitor”, to measure the memory shared across processors in jobs. Resource consumption is broken down into software domains and displayed in plots generated using Python visualization libraries and collected into pre-formatted auto-generated Web pages, which allow the ATLAS developer community to track the performance of their algorithms. This information is however preferentially filtered to domain leaders and developers through the use of JIRA and via reports given at ATLAS software meetings. Finally, we take a glimpse of the future by reporting on the expected CPU and RAM usage in benchmark workflows associated with the High Luminosity LHC and anticipate the ways performance monitoring will evolve to understand and benchmark future workflows.

Localized-atlas-based segmentation of breast MRI in a decision-making framework.

PubMed

Fooladivanda, Aida; Shokouhi, Shahriar B; Ahmadinejad, Nasrin

2017-03-01

Breast-region segmentation is an important step for density estimation and Computer-Aided Diagnosis (CAD) systems in Magnetic Resonance Imaging (MRI). Detection of breast-chest wall boundary is often a difficult task due to similarity between gray-level values of fibroglandular tissue and pectoral muscle. This paper proposes a robust breast-region segmentation method which is applicable for both complex cases with fibroglandular tissue connected to the pectoral muscle, and simple cases with high contrast boundaries. We present a decision-making framework based on geometric features and support vector machine (SVM) to classify breasts in two main groups, complex and simple. For complex cases, breast segmentation is done using a combination of intensity-based and atlas-based techniques; however, only intensity-based operation is employed for simple cases. A novel atlas-based method, that is called localized-atlas, accomplishes the processes of atlas construction and registration based on the region of interest (ROI). Atlas-based segmentation is performed by relying on the chest wall template. Our approach is validated using a dataset of 210 cases. Based on similarity between automatic and manual segmentation results, the proposed method achieves Dice similarity coefficient, Jaccard coefficient, total overlap, false negative, and false positive values of 96.3, 92.9, 97.4, 2.61 and 4.77%, respectively. The localization error of the breast-chest wall boundary is 1.97 mm, in terms of averaged deviation distance. The achieved results prove that the suggested framework performs the breast segmentation with negligible errors and efficient computational time for different breasts from the viewpoints of size, shape, and density pattern.

ATLAS of Biochemistry: A Repository of All Possible Biochemical Reactions for Synthetic Biology and Metabolic Engineering Studies.

PubMed

Hadadi, Noushin; Hafner, Jasmin; Shajkofci, Adrian; Zisaki, Aikaterini; Hatzimanikatis, Vassily

2016-10-21

Because the complexity of metabolism cannot be intuitively understood or analyzed, computational methods are indispensable for studying biochemistry and deepening our understanding of cellular metabolism to promote new discoveries. We used the computational framework BNICE.ch along with cheminformatic tools to assemble the whole theoretical reactome from the known metabolome through expansion of the known biochemistry presented in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We constructed the ATLAS of Biochemistry, a database of all theoretical biochemical reactions based on known biochemical principles and compounds. ATLAS includes more than 130 000 hypothetical enzymatic reactions that connect two or more KEGG metabolites through novel enzymatic reactions that have never been reported to occur in living organisms. Moreover, ATLAS reactions integrate 42% of KEGG metabolites that are not currently present in any KEGG reaction into one or more novel enzymatic reactions. The generated repository of information is organized in a Web-based database ( http://lcsb-databases.epfl.ch/atlas/ ) that allows the user to search for all possible routes from any substrate compound to any product. The resulting pathways involve known and novel enzymatic steps that may indicate unidentified enzymatic activities and provide potential targets for protein engineering. Our approach of introducing novel biochemistry into pathway design and associated databases will be important for synthetic biology and metabolic engineering.

Measurement of the underlying event in jet events from 7 TeV proton–proton collisions with the ATLAS detector

DOE PAGES

Aad, G.; Abajyan, T.; Abbott, B.; ...

2014-08-12

Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on 37 pb -1 of proton–proton collision data collected at a centre-of-mass energy of 7 TeV. Charged-particle mean p T and densities of all-particle E T and charged-particle multiplicity and p T have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 to 800 GeV. The correlation of charged-particle mean p T with charged-particlemore » multiplicity is also studied, and the E T densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.« less

PGAS in-memory data processing for the Processing Unit of the Upgraded Electronics of the Tile Calorimeter of the ATLAS Detector

NASA Astrophysics Data System (ADS)

Ohene-Kwofie, Daniel; Otoo, Ekow

2015-10-01

The ATLAS detector, operated at the Large Hadron Collider (LHC) records proton-proton collisions at CERN every 50ns resulting in a sustained data flow up to PB/s. The upgraded Tile Calorimeter of the ATLAS experiment will sustain about 5PB/s of digital throughput. These massive data rates require extremely fast data capture and processing. Although there has been a steady increase in the processing speed of CPU/GPGPU assembled for high performance computing, the rate of data input and output, even under parallel I/O, has not kept up with the general increase in computing speeds. The problem then is whether one can implement an I/O subsystem infrastructure capable of meeting the computational speeds of the advanced computing systems at the petascale and exascale level. We propose a system architecture that leverages the Partitioned Global Address Space (PGAS) model of computing to maintain an in-memory data-store for the Processing Unit (PU) of the upgraded electronics of the Tile Calorimeter which is proposed to be used as a high throughput general purpose co-processor to the sROD of the upgraded Tile Calorimeter. The physical memory of the PUs are aggregated into a large global logical address space using RDMA- capable interconnects such as PCI- Express to enhance data processing throughput.

The NatCarb geoportal: Linking distributed data from the Carbon Sequestration Regional Partnerships

USGS Publications Warehouse

Carr, T.R.; Rich, P.M.; Bartley, J.D.

2007-01-01

The Department of Energy (DOE) Carbon Sequestration Regional Partnerships are generating the data for a "carbon atlas" of key geospatial data (carbon sources, potential sinks, etc.) required for rapid implementation of carbon sequestration on a broad scale. The NATional CARBon Sequestration Database and Geographic Information System (NatCarb) provides Web-based, nation-wide data access. Distributed computing solutions link partnerships and other publicly accessible repositories of geological, geophysical, natural resource, infrastructure, and environmental data. Data are maintained and enhanced locally, but assembled and accessed through a single geoportal. NatCarb, as a first attempt at a national carbon cyberinfrastructure (NCCI), assembles the data required to address technical and policy challenges of carbon capture and storage. We present a path forward to design and implement a comprehensive and successful NCCI. ?? 2007 The Haworth Press, Inc. All rights reserved.

Generating patient specific pseudo-CT of the head from MR using atlas-based regression

NASA Astrophysics Data System (ADS)

Sjölund, J.; Forsberg, D.; Andersson, M.; Knutsson, H.

2015-01-01

Radiotherapy planning and attenuation correction of PET images require simulation of radiation transport. The necessary physical properties are typically derived from computed tomography (CT) images, but in some cases, including stereotactic neurosurgery and combined PET/MR imaging, only magnetic resonance (MR) images are available. With these applications in mind, we describe how a realistic, patient-specific, pseudo-CT of the head can be derived from anatomical MR images. We refer to the method as atlas-based regression, because of its similarity to atlas-based segmentation. Given a target MR and an atlas database comprising MR and CT pairs, atlas-based regression works by registering each atlas MR to the target MR, applying the resulting displacement fields to the corresponding atlas CTs and, finally, fusing the deformed atlas CTs into a single pseudo-CT. We use a deformable registration algorithm known as the Morphon and augment it with a certainty mask that allows a tailoring of the influence certain regions are allowed to have on the registration. Moreover, we propose a novel method of fusion, wherein the collection of deformed CTs is iteratively registered to their joint mean and find that the resulting mean CT becomes more similar to the target CT. However, the voxelwise median provided even better results; at least as good as earlier work that required special MR imaging techniques. This makes atlas-based regression a good candidate for clinical use.

Parcellation of the Healthy Neonatal Brain into 107 Regions Using Atlas Propagation through Intermediate Time Points in Childhood.

PubMed

Blesa, Manuel; Serag, Ahmed; Wilkinson, Alastair G; Anblagan, Devasuda; Telford, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Macnaught, Gillian; Semple, Scott I; Bastin, Mark E; Boardman, James P

2016-01-01

Neuroimage analysis pipelines rely on parcellated atlases generated from healthy individuals to provide anatomic context to structural and diffusion MRI data. Atlases constructed using adult data introduce bias into studies of early brain development. We aimed to create a neonatal brain atlas of healthy subjects that can be applied to multi-modal MRI data. Structural and diffusion 3T MRI scans were acquired soon after birth from 33 typically developing neonates born at term (mean postmenstrual age at birth 39(+5) weeks, range 37(+2)-41(+6)). An adult brain atlas (SRI24/TZO) was propagated to the neonatal data using temporal registration via childhood templates with dense temporal samples (NIH Pediatric Database), with the final atlas (Edinburgh Neonatal Atlas, ENA33) constructed using the Symmetric Group Normalization (SyGN) method. After this step, the computed final transformations were applied to T2-weighted data, and fractional anisotropy, mean diffusivity, and tissue segmentations to provide a multi-modal atlas with 107 anatomical regions; a symmetric version was also created to facilitate studies of laterality. Volumes of each region of interest were measured to provide reference data from normal subjects. Because this atlas is generated from step-wise propagation of adult labels through intermediate time points in childhood, it may serve as a useful starting point for modeling brain growth during development.

Encoding probabilistic brain atlases using Bayesian inference.

PubMed

Van Leemput, Koen

2009-06-01

This paper addresses the problem of creating probabilistic brain atlases from manually labeled training data. Probabilistic atlases are typically constructed by counting the relative frequency of occurrence of labels in corresponding locations across the training images. However, such an "averaging" approach generalizes poorly to unseen cases when the number of training images is limited, and provides no principled way of aligning the training datasets using deformable registration. In this paper, we generalize the generative image model implicitly underlying standard "average" atlases, using mesh-based representations endowed with an explicit deformation model. Bayesian inference is used to infer the optimal model parameters from the training data, leading to a simultaneous group-wise registration and atlas estimation scheme that encompasses standard averaging as a special case. We also use Bayesian inference to compare alternative atlas models in light of the training data, and show how this leads to a data compression problem that is intuitive to interpret and computationally feasible. Using this technique, we automatically determine the optimal amount of spatial blurring, the best deformation field flexibility, and the most compact mesh representation. We demonstrate, using 2-D training datasets, that the resulting models are better at capturing the structure in the training data than conventional probabilistic atlases. We also present experiments of the proposed atlas construction technique in 3-D, and show the resulting atlases' potential in fully-automated, pulse sequence-adaptive segmentation of 36 neuroanatomical structures in brain MRI scans.

Hippocampal unified multi-atlas network (HUMAN): protocol and scale validation of a novel segmentation tool.

PubMed

Amoroso, N; Errico, R; Bruno, S; Chincarini, A; Garuccio, E; Sensi, F; Tangaro, S; Tateo, A; Bellotti, R

2015-11-21

In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of the hippocampus in structural magnetic resonance imaging. In multi-atlas approaches atlas selection is of crucial importance for the accuracy of the segmentation. Here we present an optimized method based on the definition of a small peri-hippocampal region to target the atlas learning with linear and non-linear embedded manifolds. All atlases were co-registered to a data driven template resulting in a computationally efficient method that requires only one test registration. The optimal atlases identified were used to train dedicated artificial neural networks whose labels were then propagated and fused to obtain the final segmentation. To quantify data heterogeneity and protocol inherent effects, HUMAN was tested on two independent data sets provided by the Alzheimer's Disease Neuroimaging Initiative and the Open Access Series of Imaging Studies. HUMAN is accurate and achieves state-of-the-art performance (Dice[Formula: see text] and Dice[Formula: see text]). It is also a robust method that remains stable when applied to the whole hippocampus or to sub-regions (patches). HUMAN also compares favorably with a basic multi-atlas approach and a benchmark segmentation tool such as FreeSurfer.

Hippocampal unified multi-atlas network (HUMAN): protocol and scale validation of a novel segmentation tool

NASA Astrophysics Data System (ADS)

Amoroso, N.; Errico, R.; Bruno, S.; Chincarini, A.; Garuccio, E.; Sensi, F.; Tangaro, S.; Tateo, A.; Bellotti, R.; Alzheimers Disease Neuroimaging Initiative,the

2015-11-01

In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of the hippocampus in structural magnetic resonance imaging. In multi-atlas approaches atlas selection is of crucial importance for the accuracy of the segmentation. Here we present an optimized method based on the definition of a small peri-hippocampal region to target the atlas learning with linear and non-linear embedded manifolds. All atlases were co-registered to a data driven template resulting in a computationally efficient method that requires only one test registration. The optimal atlases identified were used to train dedicated artificial neural networks whose labels were then propagated and fused to obtain the final segmentation. To quantify data heterogeneity and protocol inherent effects, HUMAN was tested on two independent data sets provided by the Alzheimer’s Disease Neuroimaging Initiative and the Open Access Series of Imaging Studies. HUMAN is accurate and achieves state-of-the-art performance (Dice{{}\\text{ADNI}} =0.929+/- 0.003 and Dice{{}\\text{OASIS}} =0.869+/- 0.002 ). It is also a robust method that remains stable when applied to the whole hippocampus or to sub-regions (patches). HUMAN also compares favorably with a basic multi-atlas approach and a benchmark segmentation tool such as FreeSurfer.

ATLAS computing on CSCS HPC

NASA Astrophysics Data System (ADS)

Filipcic, A.; Haug, S.; Hostettler, M.; Walker, R.; Weber, M.

2015-12-01

The Piz Daint Cray XC30 HPC system at CSCS, the Swiss National Supercomputing centre, was the highest ranked European system on TOP500 in 2014, also featuring GPU accelerators. Event generation and detector simulation for the ATLAS experiment have been enabled for this machine. We report on the technical solutions, performance, HPC policy challenges and possible future opportunities for HEP on extreme HPC systems. In particular a custom made integration to the ATLAS job submission system has been developed via the Advanced Resource Connector (ARC) middleware. Furthermore, a partial GPU acceleration of the Geant4 detector simulations has been implemented.

EnviroAtlas-Communities: Identifying Nature’s Benefits, Deficits, and Opportunities for Equitable Distribution in Populated Places

EPA Science Inventory

Cities, towns, and Tribes rely on clean air, water and other natural resources for economic sustainability and quality of life. Yet natural resources and their benefits are not always fully understood or considered in local decisions. EnviroAtlas is a web-based, easy-to-use map...

EPA’s EnviroAtlas: Identifying Nature’s Benefits, Deficits, and Opportunities for Equitable Distribution in Populated Places

EPA Science Inventory

Background Cities, towns, and Tribes rely on clean air, water and other natural resources for public health and well-being. Yet natural infrastructure and its benefits are not always fully understood or considered in local decisions. EnviroAtlas is a web-based, easy-to-use mapp...

EPA’s EnviroAtlas: Identifying Nature’s Benefits, Deficits, and Opportunities for Equitable Distribution in Populated Places#

EPA Science Inventory

The web-based EnviroAtlas is an easy-to-use mapping and analysis tool built by the U.S. Environmental Protection Agency and its partners to provide information, data, and research on the relationships between ecosystems, built infrastructure, and societal well-being. The tool is ...

Interactive Agricultural Ecological Atlas of Russia and Neighboring Countries:Economic Plants and their Diseases, Pests and Weeds.

USDA-ARS?s Scientific Manuscript database

The AgroAtlas is a comprehensive on-line bilingual reference on the geographic distribution of economic plants, their diseases, pests and weeds, and environmental factors that influence agricultural production through out the Former Soviet Union. Online users can read about and examine maps and ima...

Computerized Bone Age Estimation Using Deep Learning Based Program: Evaluation of the Accuracy and Efficiency.

PubMed

Kim, Jeong Rye; Shim, Woo Hyun; Yoon, Hee Mang; Hong, Sang Hyup; Lee, Jin Seong; Cho, Young Ah; Kim, Sangki

2017-12-01

The purpose of this study is to evaluate the accuracy and efficiency of a new automatic software system for bone age assessment and to validate its feasibility in clinical practice. A Greulich-Pyle method-based deep-learning technique was used to develop the automatic software system for bone age determination. Using this software, bone age was estimated from left-hand radiographs of 200 patients (3-17 years old) using first-rank bone age (software only), computer-assisted bone age (two radiologists with software assistance), and Greulich-Pyle atlas-assisted bone age (two radiologists with Greulich-Pyle atlas assistance only). The reference bone age was determined by the consensus of two experienced radiologists. First-rank bone ages determined by the automatic software system showed a 69.5% concordance rate and significant correlations with the reference bone age (r = 0.992; p < 0.001). Concordance rates increased with the use of the automatic software system for both reviewer 1 (63.0% for Greulich-Pyle atlas-assisted bone age vs 72.5% for computer-assisted bone age) and reviewer 2 (49.5% for Greulich-Pyle atlas-assisted bone age vs 57.5% for computer-assisted bone age). Reading times were reduced by 18.0% and 40.0% for reviewers 1 and 2, respectively. Automatic software system showed reliably accurate bone age estimations and appeared to enhance efficiency by reducing reading times without compromising the diagnostic accuracy.

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

PubMed Central

Wang, Jiahui; Vachet, Clement; Rumple, Ashley; Gouttard, Sylvain; Ouziel, Clémentine; Perrot, Emilie; Du, Guangwei; Huang, Xuemei; Gerig, Guido; Styner, Martin

2014-01-01

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual “atlases” that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures. PMID:24567717

Development of an ADC radiation tolerance characterization system for the upgrade of the ATLAS LAr calorimeter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Hong-Bin; Chen, Hu-Cheng; Chen, Kai

ATLAS LAr calorimeter will undergo its Phase-I upgrade during the long shutdown (LS2) in 2018, and a new LAr Trigger Digitizer Board (LTDB) will be designed and installed. Several commercial-off-the-shelf (COTS) multi-channel high-speed ADCs have been selected as possible backups of the radiation tolerant ADC ASICs for the LTDB. Here, to evaluate the radiation tolerance of these backup commercial ADCs, we developed an ADC radiation tolerance characterization system, which includes the ADC boards, data acquisition (DAQ) board, signal generator, external power supplies and a host computer. The ADC board is custom designed for different ADCs, with ADC drivers and clockmore » distribution circuits integrated on board. The Xilinx ZC706 FPGA development board is used as a DAQ board. The data from the ADC are routed to the FPGA through the FMC (FPGA Mezzanine Card) connector, de-serialized and monitored by the FPGA, and then transmitted to the host computer through the Gigabit Ethernet. A software program has been developed with Python, and all the commands are sent to the DAQ board through Gigabit Ethernet by this program. Two ADC boards have been designed for the ADC, ADS52J90 from Texas Instruments and AD9249 from Analog Devices respectively. TID tests for both ADCs have been performed at BNL, and an SEE test for the ADS52J90 has been performed at Massachusetts General Hospital (MGH). Test results have been analyzed and presented. The test results demonstrate that this test system is very versatile, and works well for the radiation tolerance characterization of commercial multi-channel high-speed ADCs for the upgrade of the ATLAS LAr calorimeter. It is applicable to other collider physics experiments where radiation tolerance is required as well.« less

Development of an ADC radiation tolerance characterization system for the upgrade of the ATLAS LAr calorimeter

DOE PAGES

Liu, Hong-Bin; Chen, Hu-Cheng; Chen, Kai; ...

2017-02-01

ATLAS LAr calorimeter will undergo its Phase-I upgrade during the long shutdown (LS2) in 2018, and a new LAr Trigger Digitizer Board (LTDB) will be designed and installed. Several commercial-off-the-shelf (COTS) multi-channel high-speed ADCs have been selected as possible backups of the radiation tolerant ADC ASICs for the LTDB. Here, to evaluate the radiation tolerance of these backup commercial ADCs, we developed an ADC radiation tolerance characterization system, which includes the ADC boards, data acquisition (DAQ) board, signal generator, external power supplies and a host computer. The ADC board is custom designed for different ADCs, with ADC drivers and clockmore » distribution circuits integrated on board. The Xilinx ZC706 FPGA development board is used as a DAQ board. The data from the ADC are routed to the FPGA through the FMC (FPGA Mezzanine Card) connector, de-serialized and monitored by the FPGA, and then transmitted to the host computer through the Gigabit Ethernet. A software program has been developed with Python, and all the commands are sent to the DAQ board through Gigabit Ethernet by this program. Two ADC boards have been designed for the ADC, ADS52J90 from Texas Instruments and AD9249 from Analog Devices respectively. TID tests for both ADCs have been performed at BNL, and an SEE test for the ADS52J90 has been performed at Massachusetts General Hospital (MGH). Test results have been analyzed and presented. The test results demonstrate that this test system is very versatile, and works well for the radiation tolerance characterization of commercial multi-channel high-speed ADCs for the upgrade of the ATLAS LAr calorimeter. It is applicable to other collider physics experiments where radiation tolerance is required as well.« less

Development of an ADC radiation tolerance characterization system for the upgrade of the ATLAS LAr calorimeter

NASA Astrophysics Data System (ADS)

Liu, Hong-Bin; Chen, Hu-Cheng; Chen, Kai; Kierstead, James; Lanni, Francesco; Takai, Helio; Jin, Ge

2017-02-01

ATLAS LAr calorimeter will undergo its Phase-I upgrade during the long shutdown (LS2) in 2018, and a new LAr Trigger Digitizer Board (LTDB) will be designed and installed. Several commercial-off-the-shelf (COTS) multi-channel high-speed ADCs have been selected as possible backups of the radiation tolerant ADC ASICs for the LTDB. To evaluate the radiation tolerance of these backup commercial ADCs, we developed an ADC radiation tolerance characterization system, which includes the ADC boards, data acquisition (DAQ) board, signal generator, external power supplies and a host computer. The ADC board is custom designed for different ADCs, with ADC drivers and clock distribution circuits integrated on board. The Xilinx ZC706 FPGA development board is used as a DAQ board. The data from the ADC are routed to the FPGA through the FMC (FPGA Mezzanine Card) connector, de-serialized and monitored by the FPGA, and then transmitted to the host computer through the Gigabit Ethernet. A software program has been developed with Python, and all the commands are sent to the DAQ board through Gigabit Ethernet by this program. Two ADC boards have been designed for the ADC, ADS52J90 from Texas Instruments and AD9249 from Analog Devices respectively. TID tests for both ADCs have been performed at BNL, and an SEE test for the ADS52J90 has been performed at Massachusetts General Hospital (MGH). Test results have been analyzed and presented. The test results demonstrate that this test system is very versatile, and works well for the radiation tolerance characterization of commercial multi-channel high-speed ADCs for the upgrade of the ATLAS LAr calorimeter. It is applicable to other collider physics experiments where radiation tolerance is required as well. Supported by the U. S. Department of Energy (DE-SC001270)

PanDA Pilot Submission using Condor-G: Experience and Improvements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao X.; Hover John; Wlodek Tomasz

2011-01-01

PanDA (Production and Distributed Analysis) is the workload management system of the ATLAS experiment, used to run managed production and user analysis jobs on the grid. As a late-binding, pilot-based system, the maintenance of a smooth and steady stream of pilot jobs to all grid sites is critical for PanDA operation. The ATLAS Computing Facility (ACF) at BNL, as the ATLAS Tier1 center in the US, operates the pilot submission systems for the US. This is done using the PanDA 'AutoPilot' scheduler component which submits pilot jobs via Condor-G, a grid job scheduling system developed at the University of Wisconsin-Madison.more » In this paper, we discuss the operation and performance of the Condor-G pilot submission at BNL, with emphasis on the challenges and issues encountered in the real grid production environment. With the close collaboration of Condor and PanDA teams, the scalability and stability of the overall system has been greatly improved over the last year. We review improvements made to Condor-G resulting from this collaboration, including isolation of site-based issues by running a separate Gridmanager for each remote site, introduction of the 'Nonessential' job attribute to allow Condor to optimize its behavior for the specific character of pilot jobs, better understanding and handling of the Gridmonitor process, as well as better scheduling in the PanDA pilot scheduler component. We will also cover the monitoring of the health of the system.« less

Probabilistic Air Segmentation and Sparse Regression Estimated Pseudo CT for PET/MR Attenuation Correction

PubMed Central

Chen, Yasheng; Juttukonda, Meher; Su, Yi; Benzinger, Tammie; Rubin, Brian G.; Lee, Yueh Z.; Lin, Weili; Shen, Dinggang; Lalush, David

2015-01-01

Purpose To develop a positron emission tomography (PET) attenuation correction method for brain PET/magnetic resonance (MR) imaging by estimating pseudo computed tomographic (CT) images from T1-weighted MR and atlas CT images. Materials and Methods In this institutional review board–approved and HIPAA-compliant study, PET/MR/CT images were acquired in 20 subjects after obtaining written consent. A probabilistic air segmentation and sparse regression (PASSR) method was developed for pseudo CT estimation. Air segmentation was performed with assistance from a probabilistic air map. For nonair regions, the pseudo CT numbers were estimated via sparse regression by using atlas MR patches. The mean absolute percentage error (MAPE) on PET images was computed as the normalized mean absolute difference in PET signal intensity between a method and the reference standard continuous CT attenuation correction method. Friedman analysis of variance and Wilcoxon matched-pairs tests were performed for statistical comparison of MAPE between the PASSR method and Dixon segmentation, CT segmentation, and population averaged CT atlas (mean atlas) methods. Results The PASSR method yielded a mean MAPE ± standard deviation of 2.42% ± 1.0, 3.28% ± 0.93, and 2.16% ± 1.75, respectively, in the whole brain, gray matter, and white matter, which were significantly lower than the Dixon, CT segmentation, and mean atlas values (P < .01). Moreover, 68.0% ± 16.5, 85.8% ± 12.9, and 96.0% ± 2.5 of whole-brain volume had within ±2%, ±5%, and ±10% percentage error by using PASSR, respectively, which was significantly higher than other methods (P < .01). Conclusion PASSR outperformed the Dixon, CT segmentation, and mean atlas methods by reducing PET error owing to attenuation correction. © RSNA, 2014 PMID:25521778

Computer aided planning of orthopaedic surgeries: the definition of generic planning steps for bone removal procedures.

PubMed

Putzer, David; Moctezuma, Jose Luis; Nogler, Michael

2017-11-01

An increasing number of orthopaedic surgeons are using computer aided planning tools for bone removal applications. The aim of the study was to consolidate a set of generic functions to be used for a 3D computer assisted planning or simulation. A limited subset of 30 surgical procedures was analyzed and verified in 243 surgical procedures of a surgical atlas. Fourteen generic functions to be used in 3D computer assisted planning and simulations were extracted. Our results showed that the average procedure comprises 14 ± 10 (SD) steps with ten different generic planning steps and four generic bone removal steps. In conclusion, the study shows that with a limited number of 14 planning functions it is possible to perform 243 surgical procedures out of Campbell's Operative Orthopedics atlas. The results may be used as a basis for versatile generic intraoperative planning software.

Contributions to the NUCLEI SciDAC-3 Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bogner, Scott; Nazarewicz, Witek

This is the Final Report for Michigan State University for the NUCLEI SciDAC-3 project. The NUCLEI project, as defined by the scope of work, has developed, implemented and run codes for large-scale computations of many topics in low-energy nuclear physics. Physics studied included the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques used included Configuration Interaction, Coupled Cluster, and Density Functional methods. The research program emphasized areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS at ANL and FRIB at MSU (nuclear structuremore » and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrinoless double-beta decay and physics beyond the Standard Model), and LANSCE (fission studies).« less

Morphometric Atlas Selection for Automatic Brachial Plexus Segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van de Velde, Joris, E-mail: joris.vandevelde@ugent.be; Department of Radiotherapy, Ghent University, Ghent; Wouters, Johan

Purpose: The purpose of this study was to determine the effects of atlas selection based on different morphometric parameters, on the accuracy of automatic brachial plexus (BP) segmentation for radiation therapy planning. The segmentation accuracy was measured by comparing all of the generated automatic segmentations with anatomically validated gold standard atlases developed using cadavers. Methods and Materials: Twelve cadaver computed tomography (CT) atlases (3 males, 9 females; mean age: 73 years) were included in the study. One atlas was selected to serve as a patient, and the other 11 atlases were registered separately onto this “patient” using deformable image registration. Thismore » procedure was repeated for every atlas as a patient. Next, the Dice and Jaccard similarity indices and inclusion index were calculated for every registered BP with the original gold standard BP. In parallel, differences in several morphometric parameters that may influence the BP segmentation accuracy were measured for the different atlases. Specific brachial plexus-related CT-visible bony points were used to define the morphometric parameters. Subsequently, correlations between the similarity indices and morphometric parameters were calculated. Results: A clear negative correlation between difference in protraction-retraction distance and the similarity indices was observed (mean Pearson correlation coefficient = −0.546). All of the other investigated Pearson correlation coefficients were weak. Conclusions: Differences in the shoulder protraction-retraction position between the atlas and the patient during planning CT influence the BP autosegmentation accuracy. A greater difference in the protraction-retraction distance between the atlas and the patient reduces the accuracy of the BP automatic segmentation result.« less

ATLAS computing on Swiss Cloud SWITCHengines

NASA Astrophysics Data System (ADS)

Haug, S.; Sciacca, F. G.; ATLAS Collaboration

2017-10-01

Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

--No Title--

Science.gov Websites

interoperability emerging infrastructure for data management on computational grids Software Packages Services : ATLAS: Management and Steering: Computing Management Board Software Project Management Board Database Model Group Computing TDR: 4.5 Event Data 4.8 Database and Data Management Services 6.3.4 Production and

Browsing Software of the Visible Korean Data Used for Teaching Sectional Anatomy

ERIC Educational Resources Information Center

Shin, Dong Sun; Chung, Min Suk; Park, Hyo Seok; Park, Jin Seo; Hwang, Sung Bae

2011-01-01

The interpretation of computed tomographs (CTs) and magnetic resonance images (MRIs) to diagnose clinical conditions requires basic knowledge of sectional anatomy. Sectional anatomy has traditionally been taught using sectioned cadavers, atlases, and/or computer software. The computer software commonly used for this subject is practical and…

A Computer-Based Atlas of Global Instrumental Climate Data (DB1003)

DOE Data Explorer

Bradley, Raymond S.; Ahern, Linda G.; Keimig, Frank T.

1994-01-01

Color-shaded and contoured images of global, gridded instrumental data have been produced as a computer-based atlas. Each image simultaneously depicts anomaly maps of surface temperature, sea-level pressure, 500-mbar geopotential heights, and percentages of reference-period precipitation. Monthly, seasonal, and annual composites are available in either cylindrical equidistant or northern and southern hemisphere polar projections. Temperature maps are available from 1854 to 1991, precipitation from 1851 to 1989, sea-level pressure from 1899 to 1991, and 500-mbar heights from 1946 to 1991. The source of data for the temperature images is Jones et al.'s global gridded temperature anomalies. The precipitation images were derived from Eischeid et al.'s global gridded precipitation percentages. Grids from the Data Support Section, National Center for Atmospheric Research (NCAR) were the sources for the sea-level-pressure and 500-mbar geopotential-height images. All images are in GIF files (1024 × 822 pixels, 256 colors) and can be displayed on many different computer platforms. Each annual subdirectory contains 141 images, each seasonal subdirectory contains 563 images, and each monthly subdirectory contains 1656 images. The entire atlas requires approximately 340 MB of disk space, but users may retrieve any number of images at one time.

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

PubMed

Liyanage, Kishan Andre; Steward, Christopher; Moffat, Bradford Armstrong; Opie, Nicholas Lachlan; Rind, Gil Simon; John, Sam Emmanuel; Ronayne, Stephen; May, Clive Newton; O'Brien, Terence John; Milne, Marjorie Eileen; Oxley, Thomas James

2016-01-01

Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution) MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap) to 1 (complete overlap). For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

A comparison study of atlas-based 3D cardiac MRI segmentation: global versus global and local transformations

NASA Astrophysics Data System (ADS)

Daryanani, Aditya; Dangi, Shusil; Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Magnetic Resonance Imaging (MRI) is a standard-of-care imaging modality for cardiac function assessment and guidance of cardiac interventions thanks to its high image quality and lack of exposure to ionizing radiation. Cardiac health parameters such as left ventricular volume, ejection fraction, myocardial mass, thickness, and strain can be assessed by segmenting the heart from cardiac MRI images. Furthermore, the segmented pre-operative anatomical heart models can be used to precisely identify regions of interest to be treated during minimally invasive therapy. Hence, the use of accurate and computationally efficient segmentation techniques is critical, especially for intra-procedural guidance applications that rely on the peri-operative segmentation of subject-specific datasets without delaying the procedure workflow. Atlas-based segmentation incorporates prior knowledge of the anatomy of interest from expertly annotated image datasets. Typically, the ground truth atlas label is propagated to a test image using a combination of global and local registration. The high computational cost of non-rigid registration motivated us to obtain an initial segmentation using global transformations based on an atlas of the left ventricle from a population of patient MRI images and refine it using well developed technique based on graph cuts. Here we quantitatively compare the segmentations obtained from the global and global plus local atlases and refined using graph cut-based techniques with the expert segmentations according to several similarity metrics, including Dice correlation coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.

Subcortical structure segmentation using probabilistic atlas priors

NASA Astrophysics Data System (ADS)

Gouttard, Sylvain; Styner, Martin; Joshi, Sarang; Smith, Rachel G.; Cody Hazlett, Heather; Gerig, Guido

2007-03-01

The segmentation of the subcortical structures of the brain is required for many forms of quantitative neuroanatomic analysis. The volumetric and shape parameters of structures such as lateral ventricles, putamen, caudate, hippocampus, pallidus and amygdala are employed to characterize a disease or its evolution. This paper presents a fully automatic segmentation of these structures via a non-rigid registration of a probabilistic atlas prior and alongside a comprehensive validation. Our approach is based on an unbiased diffeomorphic atlas with probabilistic spatial priors built from a training set of MR images with corresponding manual segmentations. The atlas building computes an average image along with transformation fields mapping each training case to the average image. These transformation fields are applied to the manually segmented structures of each case in order to obtain a probabilistic map on the atlas. When applying the atlas for automatic structural segmentation, an MR image is first intensity inhomogeneity corrected, skull stripped and intensity calibrated to the atlas. Then the atlas image is registered to the image using an affine followed by a deformable registration matching the gray level intensity. Finally, the registration transformation is applied to the probabilistic maps of each structures, which are then thresholded at 0.5 probability. Using manual segmentations for comparison, measures of volumetric differences show high correlation with our results. Furthermore, the dice coefficient, which quantifies the volumetric overlap, is higher than 62% for all structures and is close to 80% for basal ganglia. The intraclass correlation coefficient computed on these same datasets shows a good inter-method correlation of the volumetric measurements. Using a dataset of a single patient scanned 10 times on 5 different scanners, reliability is shown with a coefficient of variance of less than 2 percents over the whole dataset. Overall, these validation and reliability studies show that our method accurately and reliably segments almost all structures. Only the hippocampus and amygdala segmentations exhibit relative low correlation with the manual segmentation in at least one of the validation studies, whereas they still show appropriate dice overlap coefficients.

EPA’s EnviroAtlas: Identifying Nature’s benefits, deficits, and opportunities for equitable distribution to support public health

EPA Science Inventory

Cities, towns, and Tribes rely on clean air, water and other natural resources for public health and well-being. Yet natural infrastructure and its benefits are not always fully understood or considered in local decisions. EnviroAtlas is a free, online, easy-to-use mapping tool...

Atlas Based Segmentation and Mapping of Organs at Risk from Planning CT for the Development of Voxel-Wise Predictive Models of Toxicity in Prostate Radiotherapy

NASA Astrophysics Data System (ADS)

Acosta, Oscar; Dowling, Jason; Cazoulat, Guillaume; Simon, Antoine; Salvado, Olivier; de Crevoisier, Renaud; Haigron, Pascal

The prediction of toxicity is crucial to managing prostate cancer radiotherapy (RT). This prediction is classically organ wise and based on the dose volume histograms (DVH) computed during the planning step, and using for example the mathematical Lyman Normal Tissue Complication Probability (NTCP) model. However, these models lack spatial accuracy, do not take into account deformations and may be inappropiate to explain toxicity events related with the distribution of the delivered dose. Producing voxel wise statistical models of toxicity might help to explain the risks linked to the dose spatial distribution but is challenging due to the difficulties lying on the mapping of organs and dose in a common template. In this paper we investigate the use of atlas based methods to perform the non-rigid mapping and segmentation of the individuals' organs at risk (OAR) from CT scans. To build a labeled atlas, 19 CT scans were selected from a population of patients treated for prostate cancer by radiotherapy. The prostate and the OAR (Rectum, Bladder, Bones) were then manually delineated by an expert and constituted the training data. After a number of affine and non rigid registration iterations, an average image (template) representing the whole population was obtained. The amount of consensus between labels was used to generate probabilistic maps for each organ. We validated the accuracy of the approach by segmenting the organs using the training data in a leave one out scheme. The agreement between the volumes after deformable registration and the manually segmented organs was on average above 60% for the organs at risk. The proposed methodology provides a way to map the organs from a whole population on a single template and sets the stage to perform further voxel wise analysis. With this method new and accurate predictive models of toxicity will be built.

Multi-object model-based multi-atlas segmentation for rodent brains using dense discrete correspondences

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Styner, Martin

2016-03-01

The delineation of rodent brain structures is challenging due to low-contrast multiple cortical and subcortical organs that are closely interfacing to each other. Atlas-based segmentation has been widely employed due to its ability to delineate multiple organs at the same time via image registration. The use of multiple atlases and subsequent label fusion techniques has further improved the robustness and accuracy of atlas-based segmentation. However, the accuracy of atlas-based segmentation is still prone to registration errors; for example, the segmentation of in vivo MR images can be less accurate and robust against image artifacts than the segmentation of post mortem images. In order to improve the accuracy and robustness of atlas-based segmentation, we propose a multi-object, model-based, multi-atlas segmentation method. We first establish spatial correspondences across atlases using a set of dense pseudo-landmark particles. We build a multi-object point distribution model using those particles in order to capture inter- and intra- subject variation among brain structures. The segmentation is obtained by fitting the model into a subject image, followed by label fusion process. Our result shows that the proposed method resulted in greater accuracy than comparable segmentation methods, including a widely used ANTs registration tool.

Implementation of the ATLAS trigger within the multi-threaded software framework AthenaMT

NASA Astrophysics Data System (ADS)

Wynne, Ben; ATLAS Collaboration

2017-10-01

We present an implementation of the ATLAS High Level Trigger, HLT, that provides parallel execution of trigger algorithms within the ATLAS multithreaded software framework, AthenaMT. This development will enable the ATLAS HLT to meet future challenges due to the evolution of computing hardware and upgrades of the Large Hadron Collider, LHC, and ATLAS Detector. During the LHC data-taking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further, to up to 7.5 times the design value, in 2026 following LHC and ATLAS upgrades. This includes an upgrade of the ATLAS trigger architecture that will result in an increase in the HLT input rate by a factor of 4 to 10 compared to the current maximum rate of 100 kHz. The current ATLAS multiprocess framework, AthenaMP, manages a number of processes that each execute algorithms sequentially for different events. AthenaMT will provide a fully multi-threaded environment that will additionally enable concurrent execution of algorithms within an event. This has the potential to significantly reduce the memory footprint on future manycore devices. An additional benefit of the HLT implementation within AthenaMT is that it facilitates the integration of offline code into the HLT. The trigger must retain high rejection in the face of increasing numbers of pileup collisions. This will be achieved by greater use of offline algorithms that are designed to maximize the discrimination of signal from background. Therefore a unification of the HLT and offline reconstruction software environment is required. This has been achieved while at the same time retaining important HLT-specific optimisations that minimize the computation performed to reach a trigger decision. Such optimizations include early event rejection and reconstruction within restricted geometrical regions. We report on an HLT prototype in which the need for HLT-specific components has been reduced to a minimum. Promising results have been obtained with a prototype that includes the key elements of trigger functionality including regional reconstruction and early event rejection. We report on the first experience of migrating trigger selections to this new framework and present the next steps towards a full implementation of the ATLAS trigger.

A Computer-Based Atlas of a Rat Dissection.

ERIC Educational Resources Information Center

Quentin-Baxter, Megan; Dewhurst, David

1990-01-01

A hypermedia computer program that uses text, graphics, sound, and animation with associative information linking techniques to teach the functional anatomy of a rat is described. The program includes a nonintimidating tutor, to which the student may turn. (KR)

EnviroAtlas - Big Game Hunting Recreation Demand by 12-Digit HUC in the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset includes the total number of recreational days per year demanded by people ages 18 and over for big game hunting by location in the contiguous United States. Big game includes deer, elk, bear, and wild turkey. These values are based on 2010 population distribution, 2011 U.S. Fish and Wildlife Service (FWS) Fish, Hunting, and Wildlife-Associated Recreation (FHWAR) survey data, and 2011 U.S. Department of Agriculture (USDA) Forest Service National Visitor Use Monitoring program data, and have been summarized by 12-digit hydrologic unit code (HUC). This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning.

PubMed

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-07

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-01

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

A Kalman Filtering Perspective for Multiatlas Segmentation*

PubMed Central

Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S.; Bouix, Sylvain; Tannenbaum, Allen

2016-01-01

In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity—neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy. PMID:26807162

Ticks: Geographic Distribution

MedlinePlus

... small and may be hard to identify. American dog tick ( Dermacentor variabilis ) Where found: Widely distributed east ... Atlas. Download this map [PDF – 1 page] Brown dog tick ( Rhipicephalus sanguineus ) Where found: Worldwide. Transmits: Rocky ...

Measurement of distributions sensitive to the underlying event in inclusive Z-boson production in [Formula: see text] collisions at [Formula: see text] TeV with the ATLAS detector.

PubMed

Aad, G; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimoto, G; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Alimonti, G; Alio, L; Alison, J; Allbrooke, B M M; Allison, L J; Allport, P P; Almond, J; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Altheimer, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoki, M; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Araque, J P; Arce, A T H; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Auerbach, B; Augsten, K; Aurousseau, M; Avolio, G; Azuelos, G; Azuma, Y; Baak, M A; Baas, A; Bacci, C; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Backus Mayes, J; Badescu, E; Bagiacchi, P; Bagnaia, P; Bai, Y; Bain, T; Baines, J T; Baker, O K; Balek, P; Balli, F; Banas, E; Banerjee, Sw; Bannoura, A A E; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnett, B M; Barnett, R M; Barnovska, Z; Baroncelli, A; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Bartoldus, R; Barton, A E; Bartos, P; Bartsch, V; Bassalat, A; Basye, A; Bates, R L; Batley, J R; Battaglia, M; Battistin, M; Bauer, F; Bawa, H S; Beattie, M D; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, K; Becker, S; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bedikian, S; Bednyakov, V A; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, K; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Bensinger, J R; Benslama, K; Bentvelsen, S; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Beringer, J; Bernard, C; Bernat, P; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertsche, C; Bertsche, D; Besana, M I; Besjes, G J; Bessidskaia, O; Bessner, M; Besson, N; Betancourt, C; Bethke, S; Bhimji, W; Bianchi, R M; Bianchini, L; Bianco, M; Biebel, O; Bieniek, S P; Bierwagen, K; Biesiada, J; Biglietti, M; Bilbao De Mendizabal, J; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Black, C W; Black, J E; Black, K M; Blackburn, D; Blair, R E; Blanchard, J-B; Blazek, T; Bloch, I; Blocker, C; Blum, W; Blumenschein, U; Bobbink, G J; Bobrovnikov, V S; Bocchetta, S S; Bocci, A; Bock, C; Boddy, C R; Boehler, M; Boek, J; Boek, J; Boek, T T; Bogaerts, J A; Bogdanchikov, A G; Bogouch, A; Bohm, C; Bohm, J; Boisvert, V; Bold, T; Boldea, V; Boldyrev, A S; Bomben, M; Bona, M; Boonekamp, M; Borisov, A; Borissov, G; Borri, M; Borroni, S; Bortfeldt, J; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Boterenbrood, H; Boudreau, J; Bouffard, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Bousson, N; Boutouil, S; Boveia, A; Boyd, J; Boyko, I R; Bracinik, J; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Brazzale, S F; Brelier, B; Brendlinger, K; Brennan, A J; Brenner, R; Bressler, S; Bristow, K; Bristow, T M; Britton, D; Brochu, F M; Brock, I; Brock, R; Bromberg, C; Bronner, J; Brooijmans, G; Brooks, T; Brooks, W K; Brosamer, J; Brost, E; Brown, J; Bruckman de Renstrom, P A; Bruncko, D; Bruneliere, R; Brunet, S; Bruni, A; Bruni, G; Bruschi, M; Bryngemark, L; Buanes, T; Buat, Q; Bucci, F; Buchholz, P; Buckingham, R M; Buckley, A G; Buda, S I; Budagov, I A; Buehrer, F; Bugge, L; Bugge, M K; Bulekov, O; Bundock, A C; Burckhart, H; Burdin, S; Burghgrave, B; Burke, S; Burmeister, I; Busato, E; Büscher, D; Büscher, V; Bussey, P; Buszello, C P; Butler, B; Butler, J M; Butt, A I; Buttar, C M; Butterworth, J M; Butti, P; Buttinger, W; Buzatu, A; Byszewski, M; Cabrera Urbán, S; Caforio, D; Cakir, O; Calafiura, P; Calandri, A; Calderini, G; Calfayan, P; Calkins, R; Caloba, L P; Calvet, D; Calvet, S; Camacho Toro, R; Camarda, S; Cameron, D; Caminada, L M; Caminal Armadans, R; Campana, S; Campanelli, M; Campoverde, A; Canale, V; Canepa, A; Cano Bret, M; Cantero, J; Cantrill, R; Cao, T; Capeans Garrido, M D M; Caprini, I; Caprini, M; Capua, M; Caputo, R; Cardarelli, R; Carli, T; Carlino, G; Carminati, L; Caron, S; Carquin, E; Carrillo-Montoya, G D; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Casolino, M; Castaneda-Miranda, E; Castelli, A; Castillo Gimenez, V; Castro, N F; Catastini, P; Catinaccio, A; Catmore, J R; Cattai, A; Cattani, G; Cavaliere, V; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Cerio, B; Cerny, K; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cerv, M; Cervelli, A; Cetin, S A; Chafaq, A; Chakraborty, D; Chalupkova, I; Chang, P; Chapleau, B; Chapman, J D; Charfeddine, D; Charlton, D G; Chau, C C; Chavez Barajas, C A; Cheatham, S; Chegwidden, A; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, K; Chen, L; Chen, S; Chen, X; Chen, Y; Chen, Y; Cheng, H C; Cheng, Y; Cheplakov, A; Cherkaoui El Moursli, R; Chernyatin, V; Cheu, E; Chevalier, L; Chiarella, V; Chiefari, G; 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A measurement of charged-particle distributions sensitive to the properties of the underlying event is presented for an inclusive sample of events containing a [Formula: see text]-boson, decaying to an electron or muon pair. The measurement is based on data collected using the ATLAS detector at the LHC in proton-proton collisions at a centre-of-mass energy of [Formula: see text] TeV with an integrated luminosity of [Formula: see text] fb[Formula: see text]. Distributions of the charged particle multiplicity and of the charged particle transverse momentum are measured in regions of azimuthal angle defined with respect to the [Formula: see text]-boson direction. The measured distributions are compared to similar distributions measured in jet events, and to the predictions of various Monte Carlo generators implementing different underlying event models.

Wind Energy Resource Atlas of the Dominican Republic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elliott, D.; Schwartz, M.; George, R.

2001-10-01

The Wind Energy Resource Atlas of the Dominican Republic identifies the wind characteristics and the distribution of the wind resource in this country. This major project is the first of its kind undertaken for the Dominican Republic. The information contained in the atlas is necessary to facilitate the use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications. A computerized wind mapping system developed by NREL generated detailed wind resource maps for the entire country. This technique uses Geographic Information Systems (GIS) to produce high-resolution (1-square kilometer) annual average wind resource maps.

The Center for Computational Biology: resources, achievements, and challenges

PubMed Central

Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

The Center for Computational Biology: resources, achievements, and challenges.

PubMed

Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2012-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

Distributed usability evaluation of the Pennsylvania Cancer Atlas

PubMed Central

Bhowmick, Tanuka; Robinson, Anthony C; Gruver, Adrienne; MacEachren, Alan M; Lengerich, Eugene J

2008-01-01

Background The Pennsylvania Cancer Atlas (PA-CA) is an interactive online atlas to help policy-makers, program managers, and epidemiologists with tasks related to cancer prevention and control. The PA-CA includes maps, graphs, tables, that are dynamically linked to support data exploration and decision-making with spatio-temporal cancer data. Our Atlas development process follows a user-centered design approach. To assess the usability of the initial versions of the PA-CA, we developed and applied a novel strategy for soliciting user feedback through multiple distributed focus groups and surveys. Our process of acquiring user feedback leverages an online web application (e-Delphi). In this paper we describe the PA-CA, detail how we have adapted e-Delphi web application to support usability and utility evaluation of the PA-CA, and present the results of our evaluation. Results We report results from four sets of users. Each group provided structured individual and group assessments of the PA-CA as well as input on the kinds of users and applications for which it is best suited. Overall reactions to the PA-CA are quite positive. Participants did, however, provide a range of useful suggestions. Key suggestions focused on improving interaction functions, enhancing methods of temporal analysis, addressing data issues, and providing additional data displays and help functions. These suggestions were incorporated in each design and implementation iteration for the PA-CA and used to inform a set of web-atlas design principles. Conclusion For the Atlas, we find that a design that utilizes linked map, graph, and table views is understandable to and perceived to be useful by the target audience of cancer prevention and control professionals. However, it is clear that considerable variation in experience using maps and graphics exists and for those with less experience, integrated tutorials and help features are needed. In relation to our usability assessment strategy, we find that our distributed, web-based method for soliciting user input is generally effective. Advantages include the ability to gather information from users distributed in time and space and the relative anonymity of the participants while disadvantages include less control over when and how often participants provide input and challenges for obtaining rich input. PMID:18620565

Atlas of United States Trees, Volume 2: Alaska Trees and Common Shrubs.

ERIC Educational Resources Information Center

Viereck, Leslie A.; Little, Elbert L., Jr.

This volume is the second in a series of atlases describing the natural distribution or range of native tree species in the United States. The 82 species maps include 32 of trees in Alaska, 6 of shrubs rarely reaching tree size, and 44 more of common shrubs. More than 20 additional maps summarize environmental factors and furnish general…

Semi-automated quantification and neuroanatomical mapping of heterogeneous cell populations.

PubMed

Mendez, Oscar A; Potter, Colin J; Valdez, Michael; Bello, Thomas; Trouard, Theodore P; Koshy, Anita A

2018-07-15

Our group studies the interactions between cells of the brain and the neurotropic parasite Toxoplasma gondii. Using an in vivo system that allows us to permanently mark and identify brain cells injected with Toxoplasma protein, we have identified that Toxoplasma-injected neurons (TINs) are heterogeneously distributed throughout the brain. Unfortunately, standard methods to quantify and map heterogeneous cell populations onto a reference brain atlas are time consuming and prone to user bias. We developed a novel MATLAB-based semi-automated quantification and mapping program to allow the rapid and consistent mapping of heterogeneously distributed cells on to the Allen Institute Mouse Brain Atlas. The system uses two-threshold background subtraction to identify and quantify cells of interest. We demonstrate that we reliably quantify and neuroanatomically localize TINs with low intra- or inter-observer variability. In a follow up experiment, we show that specific regions of the mouse brain are enriched with TINs. The procedure we use takes advantage of simple immunohistochemistry labeling techniques, use of a standard microscope with a motorized stage, and low cost computing that can be readily obtained at a research institute. To our knowledge there is no other program that uses such readily available techniques and equipment for mapping heterogeneous populations of cells across the whole mouse brain. The quantification method described here allows reliable visualization, quantification, and mapping of heterogeneous cell populations in immunolabeled sections across whole mouse brains. Copyright © 2018 Elsevier B.V. All rights reserved.

A mesoscale connectome of the mouse brain

PubMed Central

Oh, Seung Wook; Harris, Julie A.; Ng, Lydia; Winslow, Brent; Cain, Nicholas; Mihalas, Stefan; Wang, Quanxin; Lau, Chris; Kuan, Leonard; Henry, Alex M.; Mortrud, Marty T.; Ouellette, Benjamin; Nguyen, Thuc Nghi; Sorensen, Staci A.; Slaughterbeck, Clifford R.; Wakeman, Wayne; Li, Yang; Feng, David; Ho, Anh; Nicholas, Eric; Hirokawa, Karla E.; Bohn, Phillip; Joines, Kevin M.; Peng, Hanchuan; Hawrylycz, Michael J.; Phillips, John W.; Hohmann, John G.; Wohnoutka, Paul; Gerfen, Charles R.; Koch, Christof; Bernard, Amy; Dang, Chinh; Jones, Allan R.; Zeng, Hongkui

2016-01-01

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease. PMID:24695228

The ATLAS Tier-0: Overview and operational experience

NASA Astrophysics Data System (ADS)

Elsing, Markus; Goossens, Luc; Nairz, Armin; Negri, Guido

2010-04-01

Within the ATLAS hierarchical, multi-tier computing infrastructure, the Tier-0 centre at CERN is mainly responsible for prompt processing of the raw data coming from the online DAQ system, to archive the raw and derived data on tape, to register the data with the relevant catalogues and to distribute them to the associated Tier-1 centers. The Tier-0 is already fully functional. It has been successfully participating in all cosmic and commissioning data taking since May 2007, and was ramped up to its foreseen full size, performance and throughput for the cosmic (and short single-beam) run periods between July and October 2008. Data and work flows for collision data taking were exercised in several "Full Dress Rehearsals" (FDRs) in the course of 2008. The transition from an expert to a shifter-based system was successfully established in July 2008. This article will give an overview of the Tier-0 system, its data and work flows, and operations model. It will review the operational experience gained in cosmic, commissioning, and FDR exercises during the past year. And it will give an outlook on planned developments and the evolution of the system towards first collision data taking expected now in late Autumn 2009.

White matter atlas of the human spinal cord with estimation of partial volume effect.

PubMed

Lévy, S; Benhamou, M; Naaman, C; Rainville, P; Callot, V; Cohen-Adad, J

2015-10-01

Template-based analysis has proven to be an efficient, objective and reproducible way of extracting relevant information from multi-parametric MRI data. Using common atlases, it is possible to quantify MRI metrics within specific regions without the need for manual segmentation. This method is therefore free from user-bias and amenable to group studies. While template-based analysis is common procedure for the brain, there is currently no atlas of the white matter (WM) spinal pathways. The goals of this study were: (i) to create an atlas of the white matter tracts compatible with the MNI-Poly-AMU template and (ii) to propose methods to quantify metrics within the atlas that account for partial volume effect. The WM atlas was generated by: (i) digitalizing an existing WM atlas from a well-known source (Gray's Anatomy), (ii) registering this atlas to the MNI-Poly-AMU template at the corresponding slice (C4 vertebral level), (iii) propagating the atlas throughout all slices of the template (C1 to T6) using regularized diffeomorphic transformations and (iv) computing partial volume values for each voxel and each tract. Several approaches were implemented and validated to quantify metrics within the atlas, including weighted-average and Gaussian mixture models. Proof-of-concept application was done in five subjects for quantifying magnetization transfer ratio (MTR) in each tract of the atlas. The resulting WM atlas showed consistent topological organization and smooth transitions along the rostro-caudal axis. The median MTR across tracts was 26.2. Significant differences were detected across tracts, vertebral levels and subjects, but not across laterality (right-left). Among the different tested approaches to extract metrics, the maximum a posteriori showed highest performance with respect to noise, inter-tract variability, tract size and partial volume effect. This new WM atlas of the human spinal cord overcomes the biases associated with manual delineation and partial volume effect. Combined with multi-parametric data, the atlas can be applied to study demyelination and degeneration in diseases such as multiple sclerosis and will facilitate the conduction of longitudinal and multi-center studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Poster - 32: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mallawi, Abrar; Farrell, TomTom; Diamond, Kevin-Ro

2016-08-15

Atlas based-segmentation has recently been evaluated for use in prostate radiotherapy. In a typical approach, the essential step is the selection of an atlas from a database that the best matches of the target image. This work proposes an atlas selection strategy and evaluate it impacts on final segmentation accuracy. Several anatomical parameters were measured to indicate the overall prostate and body shape, all of these measurements obtained on CT images. A brute force procedure was first performed for a training dataset of 20 patients using image registration to pair subject with similar contours; each subject was served as amore » target image to which all reaming 19 images were affinity registered. The overlap between the prostate and femoral heads was quantified for each pair using the Dice Similarity Coefficient (DSC). Finally, an atlas selection procedure was designed; relying on the computation of a similarity score defined as a weighted sum of differences between the target and atlas subject anatomical measurement. The algorithm ability to predict the most similar atlas was excellent, achieving mean DSCs of 0.78 ± 0.07 and 0.90 ± 0.02 for the CTV and either femoral head. The proposed atlas selection yielded 0.72 ± 0.11 and 0.87 ± 0.03 for CTV and either femoral head. The DSC obtained with the proposed selection method were slightly lower than the maximum established using brute force, but this does not include potential improvements expected with deformable registration. The proposed atlas selection method provides reasonable segmentation accuracy.« less

What Is the Most Representative Parameter for Describing the Size of the Atlas? CT Morphometric Analysis of the Atlas with Special Reference to Atlas Hypoplasia.

PubMed

Yamahata, Hitoshi; Hirano, Hirofumi; Yamaguchi, Satoshi; Mori, Masanao; Niiro, Tadaaki; Tokimura, Hiroshi; Arita, Kazunori

2017-09-15

The spinal canal diameter (SCD) is one of the most studied factors for the assessment of cervical spinal canal stenosis. The inner anteroposterior diameter (IAP), the SCD, and the cross-sectional area (CSA) of the atlas have been used for the evaluation of the size of the atlas in patients with atlas hypoplasia, a rare form of developmental spinal canal stenosis, however, there is little information on their relationship. The aim of this study was to identify the most useful parameter for depicting the size of the atlas. The CSA, the IAP, and the SCD were measured on computed tomography (CT) images at the C1 level of 213 patients and compared in this retrospective study. These three parameters increased with increasing patient height and weight. There was a strong correlation between IAP and SCD (r = 0.853) or CSA (r = 0.822), while correlation between SCD and CSA (r = 0.695) was weaker than between IAP and CSA. Partial correlation analysis showed that IAP was positively correlated with SCD (r = 0.687) and CSA (r = 0.612) when CSA or SCD were controlled. SCD was negatively correlated with CSA when IAP was controlled (r = -0.21). The IAP can serve as the CSA for the evaluation of the size of the atlas ring, while the SCD does not correlate with the CSA. As the patient height and weight affect the size of the atlas, analysis of the spinal canal at the C1 level should take into account physiologic patient data.

Poster — Thur Eve — 59: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mallawi, A; Farrell, T; Diamond, K

2014-08-15

Automated atlas-based segmentation has recently been evaluated for use in planning prostate cancer radiotherapy. In the typical approach, the essential step is the selection of an atlas from a database that best matches the target image. This work proposes an atlas selection strategy and evaluates its impact on the final segmentation accuracy. Prostate length (PL), right femoral head diameter (RFHD), and left femoral head diameter (LFHD) were measured in CT images of 20 patients. Each subject was then taken as the target image to which all remaining 19 images were affinely registered. For each pair of registered images, the overlapmore » between prostate and femoral head contours was quantified using the Dice Similarity Coefficient (DSC). Finally, we designed an atlas selection strategy that computed the ratio of PL (prostate segmentation), RFHD (right femur segmentation), and LFHD (left femur segmentation) between the target subject and each subject in the atlas database. Five atlas subjects yielding ratios nearest to one were then selected for further analysis. RFHD and LFHD were excellent parameters for atlas selection, achieving a mean femoral head DSC of 0.82 ± 0.06. PL had a moderate ability to select the most similar prostate, with a mean DSC of 0.63 ± 0.18. The DSC obtained with the proposed selection method were slightly lower than the maximums established using brute force, but this does not include potential improvements expected with deformable registration. Atlas selection based on PL for prostate and femoral diameter for femoral heads provides reasonable segmentation accuracy.« less

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas

PubMed Central

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G.; Leergaard, Trygve B.; Kirlangic, Mehmet E.; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time. PMID:27199682

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas.

PubMed

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G; Leergaard, Trygve B; Kirlangic, Mehmet E; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time.

Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Strickland, Laura E.; Shafer, Sarah L.; Bartlein, Patrick J.; McFadden, Andrew K.

2015-01-01

This volume of the atlas provides numerous changes, updates, and enhancements from previous volumes. Its geographic coverage is now restricted to Canada and the continental United States, and the source and time period of the climatic data have changed. New variables were added, including monthly values for temperature and precipitation, and measures of interannual variability. The distribution maps for all previously published species were redigitized, some distribution maps were revised, and 148 new species were added from the arid and semiarid western United States. The graphical displays were expanded to illustrate the new climatic variables, and the data tables were modified to provide more detail on the population distributions of plant taxa relative to climatic variables.

From descriptive to predictive distribution models: a working example with Iberian amphibians and reptiles.

PubMed

Arntzen, J W

2006-05-04

Aim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance. I constructed distribution models for 17 amphibian and 21 reptile species in Portugal from atlas data and 13 selected ecological variables with stepwise logistic regression and a geographic information system. Models constructed for Portugal were extrapolated over Spain and tested against range maps and atlas data. Descriptive model precision ranged from 'fair' to 'very good' for 12 species showing a range border inside Portugal ('edge species', kappa (k) 0.35-0.89, average 0.57) and was at best 'moderate' for 26 species with a countrywide Portuguese distribution ('non-edge species', k = 0.03-0.54, average 0.29). The accuracy of the prediction for Spain was significantly related to the precision of the descriptive model for the group of edge species and not for the countrywide species. In the latter group data were consistently better captured with the single variable search-effort than by the panel of environmental data. Atlas data in presence-absence format are often inadequate to model the distribution of species if the considered area does not include part of the range border. Conversely, distribution models for edge-species, especially those displaying high precision, may help in the correct identification of parameters underlying the species range and assist with the informed choice of conservation measures.

Digital hand atlas for web-based bone age assessment: system design and implementation

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente

2000-04-01

A frequently used assessment method of skeletal age is atlas matching by a radiological examination of a hand image against a small set of Greulich-Pyle patterns of normal standards. The method however can lead to significant deviation in age assessment, due to a variety of observers with different levels of training. The Greulich-Pyle atlas based on middle upper class white populations in the 1950s, is also not fully applicable for children of today, especially regarding the standard development in other racial groups. In this paper, we present our system design and initial implementation of a digital hand atlas and computer-aided diagnostic (CAD) system for Web-based bone age assessment. The digital atlas will remove the disadvantages of the currently out-of-date one and allow the bone age assessment to be computerized and done conveniently via Web. The system consists of a hand atlas database, a CAD module and a Java-based Web user interface. The atlas database is based on a large set of clinically normal hand images of diverse ethnic groups. The Java-based Web user interface allows users to interact with the hand image database form browsers. Users can use a Web browser to push a clinical hand image to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, is then extracted and compared with patterns from the atlas database to assess the bone age.

The AMchip04 and the processing unit prototype for the FastTracker

NASA Astrophysics Data System (ADS)

Andreani, A.; Annovi, A.; Beretta, M.; Bogdan, M.; Citterio, M.; Alberti, F.; Giannetti, P.; Lanza, A.; Magalotti, D.; Piendibene, M.; Shochet, M.; Stabile, A.; Tang, J.; Tompkins, L.; Volpi, G.

2012-08-01

Modern experiments search for extremely rare processes hidden in much larger background levels. As the experiment`s complexity, the accelerator backgrounds and luminosity increase we need increasingly complex and exclusive event selection. We present the first prototype of a new Processing Unit (PU), the core of the FastTracker processor (FTK). FTK is a real time tracking device for the ATLAS experiment`s trigger upgrade. The computing power of the PU is such that a few hundred of them will be able to reconstruct all the tracks with transverse momentum above 1 GeV/c in ATLAS events up to Phase II instantaneous luminosities (3 × 1034 cm-2 s-1) with an event input rate of 100 kHz and a latency below a hundred microseconds. The PU provides massive computing power to minimize the online execution time of complex tracking algorithms. The time consuming pattern recognition problem, generally referred to as the ``combinatorial challenge'', is solved by the Associative Memory (AM) technology exploiting parallelism to the maximum extent; it compares the event to all pre-calculated ``expectations'' or ``patterns'' (pattern matching) simultaneously, looking for candidate tracks called ``roads''. This approach reduces to a linear behavior the typical exponential complexity of the CPU based algorithms. Pattern recognition is completed by the time data are loaded into the AM devices. We report on the design of the first Processing Unit prototypes. The design had to address the most challenging aspects of this technology: a huge number of detector clusters (``hits'') must be distributed at high rate with very large fan-out to all patterns (10 Million patterns will be located on 128 chips placed on a single board) and a huge number of roads must be collected and sent back to the FTK post-pattern-recognition functions. A network of high speed serial links is used to solve the data distribution problem.

Elective Clinical Target Volumes for Conformal Therapy in Anorectal Cancer: A Radiation Therapy Oncology Group Consensus Panel Contouring Atlas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myerson, Robert J.; Garofalo, Michael C.; El Naqa, Issam

2009-07-01

Purpose: To develop a Radiation Therapy Oncology Group (RTOG) atlas of the elective clinical target volume (CTV) definitions to be used for planning pelvic intensity-modulated radiotherapy (IMRT) for anal and rectal cancers. Methods and Materials: The Gastrointestinal Committee of the RTOG established a task group (the nine physician co-authors) to develop this atlas. They responded to a questionnaire concerning three elective CTVs (CTVA: internal iliac, presacral, and perirectal nodal regions for both anal and rectal case planning; CTVB: external iliac nodal region for anal case planning and for selected rectal cases; CTVC: inguinal nodal region for anal case planning andmore » for select rectal cases), and to outline these areas on individual computed tomographic images. The imaging files were shared via the Advanced Technology Consortium. A program developed by one of the co-authors (I.E.N.) used binomial maximum-likelihood estimates to generate a 95% group consensus contour. The computer-estimated consensus contours were then reviewed by the group and modified to provide a final contouring consensus atlas. Results: The panel achieved consensus CTV definitions to be used as guidelines for the adjuvant therapy of rectal cancer and definitive therapy for anal cancer. The most important difference from similar atlases for gynecologic or genitourinary cancer is mesorectal coverage. Detailed target volume contouring guidelines and images are discussed. Conclusion: This report serves as a template for the definition of the elective CTVs to be used in IMRT planning for anal and rectal cancers, as part of prospective RTOG trials.« less

Introduction to the Canadian Cardiovascular Outcomes Research Team's (CCORT) Canadian Cardiovascular Atlas project.

PubMed

Tu, Jack V; Brien, Susan E; Kennedy, Courtney C; Pilote, Louise; Ghali, William A

2003-03-15

The Canadian Cardiovascular Outcomes Research Team's (CCORT) Canadian Cardiovascular Atlas project was developed to provide Canadians with a national report on the state of cardiovascular health and health services in Canada. Written by a group of Canada's leading experts in cardiovascular outcomes research, the CCORT cardiac Atlas will cover a wide variety of topics ranging from cardiac risk factors and cardiac mortality rates to the treatment of patients with acute myocardial infarction and congestive heart failure and the outcomes of invasive cardiac procedures across Canada. Data in the Atlas will be presented at a national, provincial and health region level. The Atlas will be published as a series of 20 articles and chapters in future issues of The Canadian Journal of Cardiology and on CCORT's web site (www.ccort.ca). The journal version of the Atlas chapters will be written for a clinical audience and will include editorials written by invited experts, whereas the web-based version of each chapter will be written for a more general audience and will include additional supplemental information (for example, interactive colour maps and tables) that cannot be included in the journal version. Material from the Journal and the web will eventually be compiled into a book that will be distributed across Canada. This article serves as an introduction to the Atlas project and describes the rationale for and objectives of the CCORT national cardiac Atlas project.

EnviroAtlas - Phoenix, AZ - Domestic Water Demand per Day by U.S. Census Block Group

EPA Pesticide Factsheets

As included in this EnviroAtlas dataset, community level domestic water demand is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Within the EnviroAtlas Phoenix boundary, there are 53 service providers with 2000-2009 water use estimates ranging from 108 to 366 GPD.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Diagnostic workstation for digital hand atlas in bone age assessment

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente; Ominsky, Steven

1998-06-01

Bone age assessment by a radiological examination of a hand and wrist image is a procedure frequently performed in pediatric patients to evaluate growth disorders, determine growth potential in children and monitor therapy effects. The assessment method currently used in radiological diagnosis is based on atlas matching of the diagnosed hand image with the reference set of atlas patterns, which was developed in 1950s and is not fully applicable for children of today. We intent to implement a diagnostic workstation for creating a new reference set of clinically normal images which will serve as a digital atlas and can be used for a computer-assisted bone age assessment. In this paper, we present the initial data- collection and system setup phase of this five-year research program. We describe the system design, user interface implementation and software tool development for collection, visualization, management and processing of clinically normal hand and wrist images.

Event visualization in ATLAS

NASA Astrophysics Data System (ADS)

Bianchi, R. M.; Boudreau, J.; Konstantinidis, N.; Martyniuk, A. C.; Moyse, E.; Thomas, J.; Waugh, B. M.; Yallup, D. P.; ATLAS Collaboration

2017-10-01

At the beginning, HEP experiments made use of photographical images both to record and store experimental data and to illustrate their findings. Then the experiments evolved and needed to find ways to visualize their data. With the availability of computer graphics, software packages to display event data and the detector geometry started to be developed. Here, an overview of the usage of event display tools in HEP is presented. Then the case of the ATLAS experiment is considered in more detail and two widely used event display packages are presented, Atlantis and VP1, focusing on the software technologies they employ, as well as their strengths, differences and their usage in the experiment: from physics analysis to detector development, and from online monitoring to outreach and communication. Towards the end, the other ATLAS visualization tools will be briefly presented as well. Future development plans and improvements in the ATLAS event display packages will also be discussed.

The ATLAS Simulation Infrastructure

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2010-09-25

The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, andmore » the validation of the simulated output against known physics processes.« less

Géochimie et cadre géodynamique du volcanisme néoprotérozoïque terminal (vendien) du Haut Atlas occidental, Maroc(Geochemical features and tectonic setting of late Neoproterozoic Vendian volcanism in the western High Atlas, Morocco)

NASA Astrophysics Data System (ADS)

Jouhari, A.; El-Archi, A.; Aarab, M.; El-Attari, A.; Ennih, N.; Laduron, D.

2001-05-01

Late Neoproterozoic Vendian volcanic and volcaniclastic rocks are widely distributed in the western High Atlas. They are located north of the Tizi n'Test Fault, separating the West African Craton from a northerly adjacent craton. These volcanic rocks overlie a semipelitic formation, which represents the equivalent of the Tidilline and Anzi Formations of the Anti-Atlas. The geochemical characteristics of these volcanic rocks suggest a calc-alkaline active margine environment associated with the post Pan-African tectonics. They differ from those of the Anti-Atlas by their lower content of K 2O. The later rock type was generated by a melting process of the crust subducted beneath the northern craton. A carbonate-shale unit, which contains examples of interstratified calc-alkaline dacite, overlies the volcanic succession, demonstrating that the volcanic activity continued sporadically until Early Cambrian times.

RiceAtlas, a spatial database of global rice calendars and production.

PubMed

Laborte, Alice G; Gutierrez, Mary Anne; Balanza, Jane Girly; Saito, Kazuki; Zwart, Sander J; Boschetti, Mirco; Murty, M V R; Villano, Lorena; Aunario, Jorrel Khalil; Reinke, Russell; Koo, Jawoo; Hijmans, Robert J; Nelson, Andrew

2017-05-30

Knowing where, when, and how much rice is planted and harvested is crucial information for understanding the effects of policy, trade, and global and technological change on food security. We developed RiceAtlas, a spatial database on the seasonal distribution of the world's rice production. It consists of data on rice planting and harvesting dates by growing season and estimates of monthly production for all rice-producing countries. Sources used for planting and harvesting dates include global and regional databases, national publications, online reports, and expert knowledge. Monthly production data were estimated based on annual or seasonal production statistics, and planting and harvesting dates. RiceAtlas has 2,725 spatial units. Compared with available global crop calendars, RiceAtlas is nearly ten times more spatially detailed and has nearly seven times more spatial units, with at least two seasons of calendar data, making RiceAtlas the most comprehensive and detailed spatial database on rice calendar and production.

The Atlas of Natural Hazards and Risks of Austria: first results for fluvial and pluvial floods

NASA Astrophysics Data System (ADS)

Mergili, Martin; Tader, Andreas; Glade, Thomas; Neuhold, Clemens; Stiefelmeyer, Heinz

2015-04-01

Incoherent societal adaptation to natural processes results in significant losses every year. A better knowledge of the spatial and temporal distribution of hazards and risks, and of particular hot spots in a given region or period, is essential for reducing adverse impacts. Commonly, different hazard and risk estimations are performed within individual approaches based on tailor-made concepts. This works well as long as specific cases are considered. The advantage of such a procedure is that each individual hazard and risk is addressed in the best possible manner. The drawback, however, consists in the fact that the results differ significantly in terms of quality and accuracy and therefore cannot be compared. Hence, there is a need to develop a strategy and concept which uses similar data sources of equivalent quality in order to adequately analyze the different natural hazards and risks at broader scales. The present study is aiming to develop such a platform. The project Risk:ATlas focuses on the design of an atlas visualizing the most relevant natural hazards and, in particular, possible consequences for the entire territory of Austria. Available as a web-based tool and as a printed atlas, it is seen as a key tool to improve the basis for risk reduction, risk adaptation and risk transfer. The atlas is founded on those data sets available for the entire territory of Austria at a consistent resolution and quality. A 1 m resolution DEM and the official cadastre and building register represent the core, further data sets are employed according to the requirements for each natural hazard and risk. In this contribution, the methodology and the preliminary results for fluvial and pluvial floods and their consequences to buildings for three selected test areas in different types of landscapes (rural, urban and mountainous) are presented. Flooding depths expected for annualities of 30, 100 and 300 are derived from existing data sets for fluvial floods and are computed using the model FloodArea for pluvial floods. Land cover parameters necessary for flood routing are deduced from the official cadastre. The values exposed to each flood scenario are quantified on the basis of objects. In this study, the focus is on buildings, thus the official building register is employed as a major data source. The same register is used to derive the vulnerability of each building with regard to floods. Combining exposed values and vulnerability, the risk for each building, expressed as the expected damage per unit of time, is derived. Furthermore, a methodology to automatically regionalize the object-based hazards, exposures, vulnerabilities and risks to any spatial unit desired is presented. This enables us (i) to adapt the web-based atlas to different zooming levels and to flexibly react to (ii) the needs of the users of the atlas and (iii) the availability of reference data for validation of the analyses. The next steps will include (1) extending the analyses for fluvial and pluvial floods to the entire territory of Austria, employing advanced computational techniques such as the use of a cluster; (2) deriving hazards, exposures, vulnerabilities and risks related to a variety of other hazardous processes as well as to chains and combinations of processes (multi-hazard); (3) considering the consequences of hazardous processes not only for buildings, but also for infrastructures and even humans; and (4) elaborating future scenarios, based on possible environmental (including climatic) and socio-economic changes.

Three-dimensional stereotactic atlas of the adult human skull correlated with the brain, cranial nerves, and intracranial vasculature.

PubMed

Nowinski, Wieslaw L; Thaung, Thant Shoon Let; Chua, Beng Choon; Yi, Su Hnin Wut; Ngai, Vincent; Yang, Yili; Chrzan, Robert; Urbanik, Andrzej

2015-05-15

Although the adult human skull is a complex and multifunctional structure, its 3D, complete, realistic, and stereotactic atlas has not yet been created. This work addresses the construction of a 3D interactive atlas of the adult human skull spatially correlated with the brain, cranial nerves, and intracranial vasculature. The process of atlas construction included computed tomography (CT) high-resolution scan acquisition, skull extraction, skull parcellation, 3D disarticulated bone surface modeling, 3D model simplification, brain-skull registration, 3D surface editing, 3D surface naming and color-coding, integration of the CT-derived 3D bony models with the existing brain atlas, and validation. The virtual skull model created is complete with all 29 bones, including the auditory ossicles (being among the smallest bones). It contains all typical bony features and landmarks. The created skull model is superior to the existing skull models in terms of completeness, realism, and integration with the brain along with blood vessels and cranial nerves. This skull atlas is valuable for medical students and residents to easily get familiarized with the skull and surrounding anatomy with a few clicks. The atlas is also useful for educators to prepare teaching materials. It may potentially serve as a reference aid in the reading and operating rooms. Copyright © 2015 Elsevier B.V. All rights reserved.

Discovery through maps: Exploring real-world applications of ...

EPA Pesticide Factsheets

Background/Question/Methods U.S. EPA’s EnviroAtlas provides a collection of interactive tools and resources for exploring ecosystem goods and services. The purpose of EnviroAtlas is to provide better access to consistently derived ecosystems and socio-economic data to facilitate decision-making while also providing data for research and education. EnviroAtlas tools and resources are well-suited for educational use, as they encourage systems thinking, cover a broad range of topics, are freely available, and do not require specialized software to use. To use EnviroAtlas only requires a computer and an internet connection, making it a useful tool for community planning, education, and decision-making at multiple scales. To help users understand how EnviroAtlas resources may be used in different contexts, we provide example use cases. These use cases highlight a real-world issue which EnviroAtlas data, in conjunction with other available data or resources, may be used to address. Here we present three use cases that approach incorporating ecosystem services in decision-making in different decision contexts: 1) to minimize the negative impacts of excessive summer heat due to urbanization in Portland, Oregon 2) to explore selecting a pilot route for a community greenway, and 3) to reduce nutrient loading through a regional manure transport program. Results/Conclusions EnviroAtlas use cases provide step-by-step approaches for using maps and data to address real-wo

Dynamic updating atlas for heart segmentation with a nonlinear field-based model.

PubMed

Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng

2017-09-01

Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.

Event selection services in ATLAS

NASA Astrophysics Data System (ADS)

Cranshaw, J.; Cuhadar-Donszelmann, T.; Gallas, E.; Hrivnac, J.; Kenyon, M.; McGlone, H.; Malon, D.; Mambelli, M.; Nowak, M.; Viegas, F.; Vinek, E.; Zhang, Q.

2010-04-01

ATLAS has developed and deployed event-level selection services based upon event metadata records ("TAGS") and supporting file and database technology. These services allow physicists to extract events that satisfy their selection predicates from any stage of data processing and use them as input to later analyses. One component of these services is a web-based Event-Level Selection Service Interface (ELSSI). ELSSI supports event selection by integrating run-level metadata, luminosity-block-level metadata (e.g., detector status and quality information), and event-by-event information (e.g., triggers passed and physics content). The list of events that survive after some selection criterion is returned in a form that can be used directly as input to local or distributed analysis; indeed, it is possible to submit a skimming job directly from the ELSSI interface using grid proxy credential delegation. ELSSI allows physicists to explore ATLAS event metadata as a means to understand, qualitatively and quantitatively, the distributional characteristics of ATLAS data. In fact, the ELSSI service provides an easy interface to see the highest missing ET events or the events with the most leptons, to count how many events passed a given set of triggers, or to find events that failed a given trigger but nonetheless look relevant to an analysis based upon the results of offline reconstruction, and more. This work provides an overview of ATLAS event-level selection services, with an emphasis upon the interactive Event-Level Selection Service Interface.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peressutti, D; Schipaanboord, B; Kadir, T

Purpose: To investigate the effectiveness of atlas selection methods for improving atlas-based auto-contouring in radiotherapy planning. Methods: 275 H&N clinically delineated cases were employed as an atlas database from which atlases would be selected. A further 40 previously contoured cases were used as test patients against which atlas selection could be performed and evaluated. 26 variations of selection methods proposed in the literature and used in commercial systems were investigated. Atlas selection methods comprised either global or local image similarity measures, computed after rigid or deformable registration, combined with direct atlas search or with an intermediate template image. Workflow Boxmore » (Mirada-Medical, Oxford, UK) was used for all auto-contouring. Results on brain, brainstem, parotids and spinal cord were compared to random selection, a fixed set of 10 “good” atlases, and optimal selection by an “oracle” with knowledge of the ground truth. The Dice score and the average ranking with respect to the “oracle” were employed to assess the performance of the top 10 atlases selected by each method. Results: The fixed set of “good” atlases outperformed all of the atlas-patient image similarity-based selection methods (mean Dice 0.715 c.f. 0.603 to 0.677). In general, methods based on exhaustive comparison of local similarity measures showed better average Dice scores (0.658 to 0.677) compared to the use of either template image (0.655 to 0.672) or global similarity measures (0.603 to 0.666). The performance of image-based selection methods was found to be only slightly better than a random (0.645). Dice scores given relate to the left parotid, but similar results patterns were observed for all organs. Conclusion: Intuitively, atlas selection based on the patient CT is expected to improve auto-contouring performance. However, it was found that published approaches performed marginally better than random and use of a fixed set of representative atlases showed favourable performance. This research was funded via InnovateUK Grant 600277 as part of Eurostars Grant E!9297. DP,BS,MG,TK are employees of Mirada Medical Ltd.« less

Automated compromised right lung segmentation method using a robust atlas-based active volume model with sparse shape composition prior in CT.

PubMed

Zhou, Jinghao; Yan, Zhennan; Lasio, Giovanni; Huang, Junzhou; Zhang, Baoshe; Sharma, Navesh; Prado, Karl; D'Souza, Warren

2015-12-01

To resolve challenges in image segmentation in oncologic patients with severely compromised lung, we propose an automated right lung segmentation framework that uses a robust, atlas-based active volume model with a sparse shape composition prior. The robust atlas is achieved by combining the atlas with the output of sparse shape composition. Thoracic computed tomography images (n=38) from patients with lung tumors were collected. The right lung in each scan was manually segmented to build a reference training dataset against which the performance of the automated segmentation method was assessed. The quantitative results of this proposed segmentation method with sparse shape composition achieved mean Dice similarity coefficient (DSC) of (0.72, 0.81) with 95% CI, mean accuracy (ACC) of (0.97, 0.98) with 95% CI, and mean relative error (RE) of (0.46, 0.74) with 95% CI. Both qualitative and quantitative comparisons suggest that this proposed method can achieve better segmentation accuracy with less variance than other atlas-based segmentation methods in the compromised lung segmentation. Published by Elsevier Ltd.

Improving vertebra segmentation through joint vertebra-rib atlases

NASA Astrophysics Data System (ADS)

Wang, Yinong; Yao, Jianhua; Roth, Holger R.; Burns, Joseph E.; Summers, Ronald M.

2016-03-01

Accurate spine segmentation allows for improved identification and quantitative characterization of abnormalities of the vertebra, such as vertebral fractures. However, in existing automated vertebra segmentation methods on computed tomography (CT) images, leakage into nearby bones such as ribs occurs due to the close proximity of these visibly intense structures in a 3D CT volume. To reduce this error, we propose the use of joint vertebra-rib atlases to improve the segmentation of vertebrae via multi-atlas joint label fusion. Segmentation was performed and evaluated on CTs containing 106 thoracic and lumbar vertebrae from 10 pathological and traumatic spine patients on an individual vertebra level basis. Vertebra atlases produced errors where the segmentation leaked into the ribs. The use of joint vertebra-rib atlases produced a statistically significant increase in the Dice coefficient from 92.5 +/- 3.1% to 93.8 +/- 2.1% for the left and right transverse processes and a decrease in the mean and max surface distance from 0.75 +/- 0.60mm and 8.63 +/- 4.44mm to 0.30 +/- 0.27mm and 3.65 +/- 2.87mm, respectively.

An atlas of the prenatal mouse brain: gestational day 14.

PubMed

Schambra, U B; Silver, J; Lauder, J M

1991-11-01

A prenatal atlas of the mouse brain is presently unavailable and is needed for studies of normal and abnormal development, using techniques including immunocytochemistry and in situ hybridization. This atlas will be especially useful for researchers studying transgenic and mutant mice. This collection of photomicrographs and corresponding drawings of Gestational Day (GD) 14 mouse brain sections is an excerpt from a larger atlas encompassing GD 12-18. In composing this atlas, available published studies on the developing rodent brain were consulted to aid in the detailed labeling of embryonic brain structures. C57Bl/6J mice were mated for 1 h, and the presence of a copulation plug was designated as GD 0. GD 14 embryos were perfused transcardially with 4% paraformaldehyde in 0.1 M phosphate buffer and embedded in paraffin. Serial sections (10 microns thickness) were cut through whole heads in sagittal and horizontal planes. They were stained with hematoxylin and eosin and photographed. Magnifications were 43X and 31X for the horizontal and sagittal sections, respectively. Photographs were traced and line drawings prepared using an Adobe Illustrator on a Macintosh computer.

Computer Vision Evidence Supporting Craniometric Alignment of Rat Brain Atlases to Streamline Expert-Guided, First-Order Migration of Hypothalamic Spatial Datasets Related to Behavioral Control

PubMed Central

Khan, Arshad M.; Perez, Jose G.; Wells, Claire E.; Fuentes, Olac

2018-01-01

The rat has arguably the most widely studied brain among all animals, with numerous reference atlases for rat brain having been published since 1946. For example, many neuroscientists have used the atlases of Paxinos and Watson (PW, first published in 1982) or Swanson (S, first published in 1992) as guides to probe or map specific rat brain structures and their connections. Despite nearly three decades of contemporaneous publication, no independent attempt has been made to establish a basic framework that allows data mapped in PW to be placed in register with S, or vice versa. Such data migration would allow scientists to accurately contextualize neuroanatomical data mapped exclusively in only one atlas with data mapped in the other. Here, we provide a tool that allows levels from any of the seven published editions of atlases comprising three distinct PW reference spaces to be aligned to atlas levels from any of the four published editions representing S reference space. This alignment is based on registration of the anteroposterior stereotaxic coordinate (z) measured from the skull landmark, Bregma (β). Atlas level alignments performed along the z axis using one-dimensional Cleveland dot plots were in general agreement with alignments obtained independently using a custom-made computer vision application that utilized the scale-invariant feature transform (SIFT) and Random Sample Consensus (RANSAC) operation to compare regions of interest in photomicrographs of Nissl-stained tissue sections from the PW and S reference spaces. We show that z-aligned point source data (unpublished hypothalamic microinjection sites) can be migrated from PW to S space to a first-order approximation in the mediolateral and dorsoventral dimensions using anisotropic scaling of the vector-formatted atlas templates, together with expert-guided relocation of obvious outliers in the migrated datasets. The migrated data can be contextualized with other datasets mapped in S space, including neuronal cell bodies, axons, and chemoarchitecture; to generate data-constrained hypotheses difficult to formulate otherwise. The alignment strategies provided in this study constitute a basic starting point for first-order, user-guided data migration between PW and S reference spaces along three dimensions that is potentially extensible to other spatial reference systems for the rat brain. PMID:29765309

Development of a computerized atlas of neonatal surgery

NASA Astrophysics Data System (ADS)

Gill, Brijesh S.; Hardin, William D., Jr.

1995-05-01

Digital imaging is an evolving technology with significant potential for enhancing medical education and practice. Current teaching methodologies still rely on the time-honored traditions of group lectures, small group discussions, and clinical preceptorships. Educational content and value are variable. Utilization of electronic media is in its infancy but offers significant potential for enhancing if not replacing current teaching methodologies. This report details our experience with the creation of an interactive atlas on neonatal surgical conditions. The photographic atlas has been one of the classic tools of practice, reference, and especially of education in surgery. The major limitations on current atlases all stem from the fact that they are produced in book form. The limiting factors in the inclusion of large numbers of images in these volumes include the desire to limit the physical size of the book and the costs associated with high quality color reproduction of print images. The structure of the atlases usually makes them reference tools, rather than teaching tools. We have digitized a large number of clinical images dealing with the diagnosis and surgical management of all of the most common neonatal surgical conditions. The flexibility of the computer presentation environment allows the images to be organized in a number of different ways. In addition to a standard captioned atlas, the user may choose to review case histories of several of the more common conditions in neonates, complete with presenting conditions, imaging studies, surgery and pathology. Use of the computer offers the ability to choose multiple views of the images, including comparison views and transparent overlays that point out important anatomical and histopathological structures, and the ability to perform user self-tests. This atlas thus takes advantage of several aspects of data management unique to computerized digital imaging, particularly the ability to combine all aspects of medical imaging related to a single case for easy retrieval. This facet unique to digital imaging makes it the obvious choice for new methods of teaching such complex subjects as the clinical management of neonatal surgical conditions. We anticipate that many more subjects in the surgical, pathologic, and radiologic realms will eventually be presented in a similar manner.

HammerCloud: A Stress Testing System for Distributed Analysis

NASA Astrophysics Data System (ADS)

van der Ster, Daniel C.; Elmsheuser, Johannes; Úbeda García, Mario; Paladin, Massimo

2011-12-01

Distributed analysis of LHC data is an I/O-intensive activity which places large demands on the internal network, storage, and local disks at remote computing facilities. Commissioning and maintaining a site to provide an efficient distributed analysis service is therefore a challenge which can be aided by tools to help evaluate a variety of infrastructure designs and configurations. HammerCloud is one such tool; it is a stress testing service which is used by central operations teams, regional coordinators, and local site admins to (a) submit arbitrary number of analysis jobs to a number of sites, (b) maintain at a steady-state a predefined number of jobs running at the sites under test, (c) produce web-based reports summarizing the efficiency and performance of the sites under test, and (d) present a web-interface for historical test results to both evaluate progress and compare sites. HammerCloud was built around the distributed analysis framework Ganga, exploiting its API for grid job management. HammerCloud has been employed by the ATLAS experiment for continuous testing of many sites worldwide, and also during large scale computing challenges such as STEP'09 and UAT'09, where the scale of the tests exceeded 10,000 concurrently running and 1,000,000 total jobs over multi-day periods. In addition, HammerCloud is being adopted by the CMS experiment; the plugin structure of HammerCloud allows the execution of CMS jobs using their official tool (CRAB).

Distributed Data Collection for the ATLAS EventIndex

NASA Astrophysics Data System (ADS)

Sánchez, J.; Fernández Casaní, A.; González de la Hoz, S.

2015-12-01

The ATLAS EventIndex contains records of all events processed by ATLAS, in all processing stages. These records include the references to the files containing each event (the GUID of the file) and the internal pointer to each event in the file. This information is collected by all jobs that run at Tier-0 or on the Grid and process ATLAS events. Each job produces a snippet of information for each permanent output file. This information is packed and transferred to a central broker at CERN using an ActiveMQ messaging system, and then is unpacked, sorted and reformatted in order to be stored and catalogued into a central Hadoop server. This contribution describes in detail the Producer/Consumer architecture to convey this information from the running jobs through the messaging system to the Hadoop server.

Empirical Performance Model-Driven Data Layout Optimization and Library Call Selection for Tensor Contraction Expressions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Qingda; Gao, Xiaoyang; Krishnamoorthy, Sriram

Empirical optimizers like ATLAS have been very effective in optimizing computational kernels in libraries. The best choice of parameters such as tile size and degree of loop unrolling is determined by executing different versions of the computation. In contrast, optimizing compilers use a model-driven approach to program transformation. While the model-driven approach of optimizing compilers is generally orders of magnitude faster than ATLAS-like library generators, its effectiveness can be limited by the accuracy of the performance models used. In this paper, we describe an approach where a class of computations is modeled in terms of constituent operations that are empiricallymore » measured, thereby allowing modeling of the overall execution time. The performance model with empirically determined cost components is used to perform data layout optimization together with the selection of library calls and layout transformations in the context of the Tensor Contraction Engine, a compiler for a high-level domain-specific language for expressing computational models in quantum chemistry. The effectiveness of the approach is demonstrated through experimental measurements on representative computations from quantum chemistry.« less

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87. Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Distributed analysis functional testing using GangaRobot in the ATLAS experiment

NASA Astrophysics Data System (ADS)

Legger, Federica; ATLAS Collaboration

2011-12-01

Automated distributed analysis tests are necessary to ensure smooth operations of the ATLAS grid resources. The HammerCloud framework allows for easy definition, submission and monitoring of grid test applications. Both functional and stress test applications can be defined in HammerCloud. Stress tests are large-scale tests meant to verify the behaviour of sites under heavy load. Functional tests are light user applications running at each site with high frequency, to ensure that the site functionalities are available at all times. Success or failure rates of these tests jobs are individually monitored. Test definitions and results are stored in a database and made available to users and site administrators through a web interface. In this work we present the recent developments of the GangaRobot framework. GangaRobot monitors the outcome of functional tests, creates a blacklist of sites failing the tests, and exports the results to the ATLAS Site Status Board (SSB) and to the Service Availability Monitor (SAM), providing on the one hand a fast way to identify systematic or temporary site failures, and on the other hand allowing for an effective distribution of the work load on the available resources.

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners.

PubMed

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this "Atlas-T1w-DUTE" approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the "silver standard"; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally.

Development and Validation of a Heart Atlas to Study Cardiac Exposure to Radiation Following Treatment for Breast Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Mary, E-mail: maryfeng@umich.ed; Moran, Jean M.; Koelling, Todd

2011-01-01

Purpose: Cardiac toxicity is an important sequela of breast radiotherapy. However, the relationship between dose to cardiac structures and subsequent toxicity has not been well defined, partially due to variations in substructure delineation, which can lead to inconsistent dose reporting and the failure to detect potential correlations. Here we have developed a heart atlas and evaluated its effect on contour accuracy and concordance. Methods and Materials: A detailed cardiac computed tomography scan atlas was developed jointly by cardiology, cardiac radiology, and radiation oncology. Seven radiation oncologists were recruited to delineate the whole heart, left main and left anterior descending interventricularmore » branches, and right coronary arteries on four cases before and after studying the atlas. Contour accuracy was assessed by percent overlap with gold standard atlas volumes. The concordance index was also calculated. Standard radiation fields were applied. Doses to observer-contoured cardiac structures were calculated and compared with gold standard contour doses. Pre- and post-atlas values were analyzed using a paired t test. Results: The cardiac atlas significantly improved contour accuracy and concordance. Percent overlap and concordance index of observer-contoured cardiac and gold standard volumes were 2.3-fold improved for all structures (p < 0.002). After application of the atlas, reported mean doses to the whole heart, left main artery, left anterior descending interventricular branch, and right coronary artery were within 0.1, 0.9, 2.6, and 0.6 Gy, respectively, of gold standard doses. Conclusions: This validated University of Michigan cardiac atlas may serve as a useful tool in future studies assessing cardiac toxicity and in clinical trials which include dose volume constraints to the heart.« less

Discriminative confidence estimation for probabilistic multi-atlas label fusion.

PubMed

Benkarim, Oualid M; Piella, Gemma; González Ballester, Miguel Angel; Sanroma, Gerard

2017-12-01

Quantitative neuroimaging analyses often rely on the accurate segmentation of anatomical brain structures. In contrast to manual segmentation, automatic methods offer reproducible outputs and provide scalability to study large databases. Among existing approaches, multi-atlas segmentation has recently shown to yield state-of-the-art performance in automatic segmentation of brain images. It consists in propagating the labelmaps from a set of atlases to the anatomy of a target image using image registration, and then fusing these multiple warped labelmaps into a consensus segmentation on the target image. Accurately estimating the contribution of each atlas labelmap to the final segmentation is a critical step for the success of multi-atlas segmentation. Common approaches to label fusion either rely on local patch similarity, probabilistic statistical frameworks or a combination of both. In this work, we propose a probabilistic label fusion framework based on atlas label confidences computed at each voxel of the structure of interest. Maximum likelihood atlas confidences are estimated using a supervised approach, explicitly modeling the relationship between local image appearances and segmentation errors produced by each of the atlases. We evaluate different spatial pooling strategies for modeling local segmentation errors. We also present a novel type of label-dependent appearance features based on atlas labelmaps that are used during confidence estimation to increase the accuracy of our label fusion. Our approach is evaluated on the segmentation of seven subcortical brain structures from the MICCAI 2013 SATA Challenge dataset and the hippocampi from the ADNI dataset. Overall, our results indicate that the proposed label fusion framework achieves superior performance to state-of-the-art approaches in the majority of the evaluated brain structures and shows more robustness to registration errors. Copyright © 2017 Elsevier B.V. All rights reserved.

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Guangkai; Gao, Yaozong; Wu, Guorong

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features canmore » be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature.« less

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

PubMed Central

Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

2016-01-01

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature. PMID:26843260

How to keep the Grid full and working with ATLAS production and physics jobs

NASA Astrophysics Data System (ADS)

Pacheco Pagés, A.; Barreiro Megino, F. H.; Cameron, D.; Fassi, F.; Filipcic, A.; Di Girolamo, A.; González de la Hoz, S.; Glushkov, I.; Maeno, T.; Walker, R.; Yang, W.; ATLAS Collaboration

2017-10-01

The ATLAS production system provides the infrastructure to process millions of events collected during the LHC Run 1 and the first two years of Run 2 using grid, clouds and high performance computing. We address in this contribution the strategies and improvements that have been implemented to the production system for optimal performance and to achieve the highest efficiency of available resources from operational perspective. We focus on the recent developments.

CAVEman: Standardized anatomical context for biomedical data mapping.

PubMed

Turinsky, Andrei L; Fanea, Elena; Trinh, Quang; Wat, Stephen; Hallgrímsson, Benedikt; Dong, Xiaoli; Shu, Xueling; Stromer, Julie N; Hill, Jonathan W; Edwards, Carol; Grosenick, Brenda; Yajima, Masumi; Sensen, Christoph W

2008-01-01

The authors have created a software system called the CAVEman, for the visual integration and exploration of heterogeneous anatomical and biomedical data. The CAVEman can be applied for both education and research tasks. The main component of the system is a three-dimensional digital atlas of the adult male human anatomy, structured according to the nomenclature of Terminologia Anatomica. The underlying data-indexing mechanism uses standard ontologies to map a range of biomedical data types onto the atlas. The CAVEman system is now used to visualize genetic processes in the context of the human anatomy and to facilitate visual exploration of the data. Through the use of Javatrade mark software, the atlas-based system is portable to virtually any computer environment, including personal computers and workstations. Existing Java tools for biomedical data analysis have been incorporated into the system. The affordability of virtual-reality installations has increased dramatically over the last several years. This creates new opportunities for educational scenarios that model important processes in a patient's body, including gene expression patterns, metabolic activity, the effects of interventions such as drug treatments, and eventually surgical simulations.

Measurement of distributions sensitive to the underlying event in inclusive Z-boson production in pp collisions at √s = 7 TeV with the ATLAS detector

DOE PAGES

Aad, G.

2014-12-10

A measurement of charged-particle distributions sensitive to the properties of the underlying event is presented for an inclusive sample of events containing a \\(Z\\)-boson, decaying to an electron or muon pair. The measurement is based on data collected using the ATLAS detector at the LHC in proton–proton collisions at a centre-of-mass energy of \\(7\\) TeV with an integrated luminosity of \\(4.6\\) fb\\(^{-1}\\). Distributions of the charged particle multiplicity and of the charged particle transverse momentum are measured in regions of azimuthal angle defined with respect to the \\(Z\\)-boson direction. As a result, the measured distributions are compared to similar distributionsmore » measured in jet events, and to the predictions of various Monte Carlo generators implementing different underlying event models.« less

Measurement of colour flow with the jet pull angle in tt-bar events using the ATLAS detector at √s = 8 TeV

DOE PAGES

Aad, G.

2015-09-26

The distribution and orientation of energy inside jets is predicted to be an experimental handle on colour connections between the hard-scatter quarks and gluons initiating the jets. This Letter presents a measurement of the distribution of one such variable, the jet pull angle. The pull angle is measured for jets produced in tt-bar events with one W boson decaying leptonically and the other decaying to jets using 20.3 fb –1 of data recorded with the ATLAS detector at a centre-of-mass energy of √s=8 TeV at the LHC. The jet pull angle distribution is corrected for detector resolution and acceptance effectsmore » and is compared to various models.« less

Comparison of the Frontier Distributed Database Caching System to NoSQL Databases

NASA Astrophysics Data System (ADS)

Dykstra, Dave

2012-12-01

One of the main attractions of non-relational “NoSQL” databases is their ability to scale to large numbers of readers, including readers spread over a wide area. The Frontier distributed database caching system, used in production by the Large Hadron Collider CMS and ATLAS detector projects for Conditions data, is based on traditional SQL databases but also adds high scalability and the ability to be distributed over a wide-area for an important subset of applications. This paper compares the major characteristics of the two different approaches and identifies the criteria for choosing which approach to prefer over the other. It also compares in some detail the NoSQL databases used by CMS and ATLAS: MongoDB, CouchDB, HBase, and Cassandra.

Comparison of the Frontier Distributed Database Caching System to NoSQL Databases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykstra, Dave

One of the main attractions of non-relational NoSQL databases is their ability to scale to large numbers of readers, including readers spread over a wide area. The Frontier distributed database caching system, used in production by the Large Hadron Collider CMS and ATLAS detector projects for Conditions data, is based on traditional SQL databases but also adds high scalability and the ability to be distributed over a wide-area for an important subset of applications. This paper compares the major characteristics of the two different approaches and identifies the criteria for choosing which approach to prefer over the other. It alsomore » compares in some detail the NoSQL databases used by CMS and ATLAS: MongoDB, CouchDB, HBase, and Cassandra.« less

Measurement of colour flow with the jet pull angle in tt-bar events using the ATLAS detector at √s = 8 TeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.

The distribution and orientation of energy inside jets is predicted to be an experimental handle on colour connections between the hard-scatter quarks and gluons initiating the jets. This Letter presents a measurement of the distribution of one such variable, the jet pull angle. The pull angle is measured for jets produced in tt-bar events with one W boson decaying leptonically and the other decaying to jets using 20.3 fb –1 of data recorded with the ATLAS detector at a centre-of-mass energy of √s=8 TeV at the LHC. The jet pull angle distribution is corrected for detector resolution and acceptance effectsmore » and is compared to various models.« less

The ATLAS Tier-3 in Geneva and the Trigger Development Facility

NASA Astrophysics Data System (ADS)

Gadomski, S.; Meunier, Y.; Pasche, P.; Baud, J.-P.; ATLAS Collaboration

2011-12-01

The ATLAS Tier-3 farm at the University of Geneva provides storage and processing power for analysis of ATLAS data. In addition the facility is used for development, validation and commissioning of the High Level Trigger of ATLAS [1]. The latter purpose leads to additional requirements on the availability of latest software and data, which will be presented. The farm is also a part of the WLCG [2], and is available to all members of the ATLAS Virtual Organization. The farm currently provides 268 CPU cores and 177 TB of storage space. A grid Storage Element, implemented with the Disk Pool Manager software [3], is available and integrated with the ATLAS Distributed Data Management system [4]. The batch system can be used directly by local users, or with a grid interface provided by NorduGrid ARC middleware [5]. In this article we will present the use cases that we support, as well as the experience with the software and the hardware we are using. Results of I/O benchmarking tests, which were done for our DPM Storage Element and for the NFS servers we are using, will also be presented.

Contour-Driven Atlas-Based Segmentation

PubMed Central

Wachinger, Christian; Fritscher, Karl; Sharp, Greg; Golland, Polina

2016-01-01

We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images. PMID:26068202

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

[The brain in stereotaxic coordinates (a textbook for colleges)].

PubMed

Budantsev, A Iu; Kisliuk, O S; Shul'govskiĭ, V V; Rykunov, D S; Iarkov, A V

1993-01-01

The present textbook is directed forward students of universities and medical colleges, young scientists and practicing doctors dealing with stereotaxic method. The Paxinos and Watson stereotaxic rat brain atlas (1982) is the basis of the textbook. The atlas has been transformed into computer educational program and seven laboratory works: insertion of the electrode into brain, microelectrophoresis, microinjection of drugs into brain, electrolytic destruction in the brain structures, local brain superfusion. The laboratory works are compiled so that they allow not only to study practical use of the stereotaxic method but to model simple problems involving stereotaxic surgery in the deep structures of brain. The textbook is intended for carrying by IBM PC/AT computers. The volume of the textbook is 1.7 Mbytes.

EnviroAtlas - Austin, TX - Domestic Water Use per Day by U.S. Census Block Group

EPA Pesticide Factsheets

As included in this EnviroAtlas dataset, the community level domestic water use is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Residential water use reporting in the EnviroAtlas-defined study area is available through the Texas Water Development Board. Within the Austin study area, there are thirteen community estimates from 2012 ranging from 65 to 303 GPD. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-f

The “Common Solutions” Strategy of the Experiment Support group at CERN for the LHC Experiments

NASA Astrophysics Data System (ADS)

Girone, M.; Andreeva, J.; Barreiro Megino, F. H.; Campana, S.; Cinquilli, M.; Di Girolamo, A.; Dimou, M.; Giordano, D.; Karavakis, E.; Kenyon, M. J.; Kokozkiewicz, L.; Lanciotti, E.; Litmaath, M.; Magini, N.; Negri, G.; Roiser, S.; Saiz, P.; Saiz Santos, M. D.; Schovancova, J.; Sciabà, A.; Spiga, D.; Trentadue, R.; Tuckett, D.; Valassi, A.; Van der Ster, D. C.; Shiers, J. D.

2012-12-01

After two years of LHC data taking, processing and analysis and with numerous changes in computing technology, a number of aspects of the experiments’ computing, as well as WLCG deployment and operations, need to evolve. As part of the activities of the Experiment Support group in CERN's IT department, and reinforced by effort from the EGI-InSPIRE project, we present work aimed at common solutions across all LHC experiments. Such solutions allow us not only to optimize development manpower but also offer lower long-term maintenance and support costs. The main areas cover Distributed Data Management, Data Analysis, Monitoring and the LCG Persistency Framework. Specific tools have been developed including the HammerCloud framework, automated services for data placement, data cleaning and data integrity (such as the data popularity service for CMS, the common Victor cleaning agent for ATLAS and CMS and tools for catalogue/storage consistency), the Dashboard Monitoring framework (job monitoring, data management monitoring, File Transfer monitoring) and the Site Status Board. This talk focuses primarily on the strategic aspects of providing such common solutions and how this relates to the overall goals of long-term sustainability and the relationship to the various WLCG Technical Evolution Groups. The success of the service components has given us confidence in the process, and has developed the trust of the stakeholders. We are now attempting to expand the development of common solutions into the more critical workflows. The first is a feasibility study of common analysis workflow execution elements between ATLAS and CMS. We look forward to additional common development in the future.

Atlas of optimal coil orientation and position for TMS: A computational study.

PubMed

Gomez-Tames, Jose; Hamasaka, Atsushi; Laakso, Ilkka; Hirata, Akimasa; Ugawa, Yoshikazu

2018-04-17

Transcranial magnetic stimulation (TMS) activates target brain structures in a non-invasive manner. The optimal orientation of the TMS coil for the motor cortex is well known and can be estimated using motor evoked potentials. However, there are no easily measurable responses for activation of other cortical areas and the optimal orientation for these areas is currently unknown. This study investigated the electric field strength, optimal coil orientation, and relative locations to optimally stimulate the target cortex based on computed electric field distributions. A total of 518,616 stimulation scenarios were studied using realistic head models (2401 coil locations × 12 coil angles × 18 head models). Inter-subject registration methods were used to generate an atlas of optimized TMS coil orientations on locations on the standard brain. We found that the maximum electric field strength is greater in primary somatosensory cortex and primary motor cortex than in other cortical areas. Additionally, a universal optimal coil orientation applicable to most subjects is more feasible at the primary somatosensory cortex and primary motor cortex. We confirmed that optimal coil angle follows the anatomical shape of the hand motor area to realize personalized optimization of TMS. Finally, on average, the optimal coil positions for TMS on the scalp deviated 5.5 mm from the scalp points with minimum cortex-scalp distance. This deviation was minimal at the premotor cortex and primary motor cortex. Personalized optimal coil orientation is preferable for obtaining the most effective stimulation. Copyright © 2018. Published by Elsevier Inc.

Crustal and lithospheric imaging of the Atlas Mountains of Morocco inferred from magnetotelluric data

NASA Astrophysics Data System (ADS)

Kiyan, D.; Jones, A. G.; Fullea, J.; Hogg, C.; Ledo, J.; Sinischalchi, A.; Campanya, J.; Picasso Phase II Team

2010-12-01

The Atlas System of Morocco is an intra-continental mountain belt extending for more than 2,000 km along the NW African plate with a predominant NE-SW trend. The System comprises three main branches: the High Atlas, the Middle Atlas, and the Anti Atlas. We present the results of a very recent multi-institutional magnetotelluric (MT) experiment across the Atlas Mountains region that started in September, 2009 and ended in February, 2010, comprising acquisition of broadband and long-period MT data. The experiment consisted of two profiles: (1) a N-S oriented profile crossing the Middle Atlas through the Central High Atlas to the east and (2) a NE-SW profile crossing the western High Atlas towards the Anti Atlas to the west. The MT measurements are part of the PICASSO (Program to Investigate Convective Alboran Sea System Overturn) and the concomitant TopoMed (Plate re-organization in the western Mediterranean: Lithospheric causes and topographic consequences - an ESF EUROCORES TOPO-EUROPE project) projects, to develop a better understanding of the internal structure and evolution of the crust and lithosphere of the Atlas Mountains. The MT data have been processed with robust remote reference methods and submitted to comprehensive strike and dimensionality analysis. Two clearly depth-differentiated strike directions are apparent for crustal (5-35 km) and lithospheric (50-150 km) depth ranges. These two orientations are roughly consistent with the NW-SE Africa-Eurasia convergence acting since the late Cretaceous, and the NNE-SSW Middle Atlas, where Miocene to recent Alkaline volcanism is present. Two-dimensional (2-D) smooth electrical resistivity models were computed independently for both 50 degrees and 20 degrees E of N strike directions. At the crustal scale, our preliminary results reveal a middle to lower-crustal conductive layer stretching from the Middle Atlas southward towards the High Moulouya basin. The most resistive (and therefore potentially thickest) lithosphere is found beneath the Central High Atlas. The inversion results are to be tested against other geophysical observables (i.e. topography, geoid and gravity anomalies, surface heat flow and seismic velocities) using the software package LitMod. This software combines petrological and geophysical modelling of the lithosphere and sub-lithospheric upper mantle within an internally consistent thermodynamic-geophysical framework, where all relevant properties are functions of temperature, pressure and composition.

Self-designed posterior atlas polyaxial lateral mass screw-plate fixation for unstable atlas fracture.

PubMed

He, Baorong; Yan, Liang; Zhao, Qinpeng; Chang, Zhen; Hao, Dingjun

2014-12-01

Most atlas fractures can be effectively treated nonoperatively with external immobilization unless there is an injury to the transverse atlantal ligament. Surgical stabilization is most commonly achieved using a posterior approach with fixation of C1-C2 or C0-C2, but these treatments usually result in loss of the normal motion of the C1-C2 and C0-C1 joints. To clinically validate feasibility, safety, and value of open reduction and fixation using an atlas polyaxial lateral mass screw-plate construct in unstable atlas fractures. Retrospective review of patients who sustained unstable atlas fractures treated with polyaxial lateral mass screw-plate construct. Twenty-two patients with unstable atlas fractures who underwent posterior atlas polyaxial lateral mass screw-plate fixation were analyzed. Visual analog scale, neurologic status, and radiographs for fusion. From January 2011 to September 2012, 22 patients with unstable atlas fractures were treated with this technique. Patients' charts and radiographs were reviewed. Bone fusion, internal fixation placement, and integrity of spinal cord and vertebral arteries were assessed via intraoperative and follow-up imaging. Neurologic function, range of motion, and pain levels were assessed clinically on follow-up. All patients were followed up from 12 to 32 months, with an average of 22.5±18.0 months. A total of 22 plates were placed, and all 44 screws were inserted into the atlas lateral masses. The mean duration of the procedure was 86 minutes, and the average estimated blood loss was 120 mL. Computed tomography scans 9 months after surgery confirmed that fusion was achieved in all cases. There was no screw or plate loosening or breakage in any patient. All patients had well-preserved range of motion. No vascular or neurologic complication was noted, and all patients had a good clinical outcome. An open reduction and posterior internal fixation with atlas polyaxial lateral mass screw-plate is a safe and effective surgical option in the treatment of unstable atlas fractures. This technique can provide immediate reduction and preserve C1-C2 motion. Copyright © 2014 Elsevier Inc. All rights reserved.

Accuracy of patient specific organ-dose estimates obtained using an automated image segmentation algorithm

NASA Astrophysics Data System (ADS)

Gilat-Schmidt, Taly; Wang, Adam; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-03-01

The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multiatlas approach was also investigated. We hypothesize that the auto-segmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.

Evaluating Alignment of Shapes by Ensemble Visualization

PubMed Central

Raj, Mukund; Mirzargar, Mahsa; Preston, J. Samuel; Kirby, Robert M.; Whitaker, Ross T.

2016-01-01

The visualization of variability in surfaces embedded in 3D, which is a type of ensemble uncertainty visualization, provides a means of understanding the underlying distribution of a collection or ensemble of surfaces. Although ensemble visualization for isosurfaces has been described in the literature, we conduct an expert-based evaluation of various ensemble visualization techniques in a particular medical imaging application: the construction of atlases or templates from a population of images. In this work, we extend contour boxplot to 3D, allowing us to evaluate it against an enumeration-style visualization of the ensemble members and other conventional visualizations used by atlas builders, namely examining the atlas image and the corresponding images/data provided as part of the construction process. We present feedback from domain experts on the efficacy of contour boxplot compared to other modalities when used as part of the atlas construction and analysis stages of their work. PMID:26186768

EnviroAtlas - Pittsburgh, PA - Domestic Water Use per Day by U.S. Census Block Group

EPA Pesticide Factsheets

As included in this EnviroAtlas dataset, the community level domestic water use was calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Domestic water demand was calculated and applied using the Pennsylvania Department of Environmental Protection (PADEP) PWS Service Areas layer, population served per provider, and average water use per provider. Within the EnviroAtlas study area, there are 43 service providers with 2010-2013 estimates ranging from 34 to 102 GPD.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can

EnviroAtlas - Domestic Water Demand by 12-Digit HUC for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset includes domestic water demand attributes which provide insight into the amount of water currently used for indoor and outdoor residential purposes in the contiguous United States. The values are based on 2010 water demand and 2010 population distribution, and have been summarized by subwatershed, or 12-digit hydrologic unit code (HUC12). For the purposes of this metric, domestic water use includes residential uses, such as for drinking, bathing, cleaning, landscaping, and pools. Depending on the location, domestic water can be self-supplied, such as by private wells, or publicly-supplied, such as by municipalities. Sources include surface water and groundwater. Estimates are for primary residences only (i.e., excluding second homes and tourism rentals). This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Atlas of albedo and absorbed solar radiation derived from Nimbus 7 earth radiation budget data set, November 1985 to October 1987

NASA Technical Reports Server (NTRS)

Smith, G. Louis; Rutan, David; Bess, T. Dale

1992-01-01

An atlas of monthly mean global contour maps of albedo and absorbed solar radiation is presented for 21 months from Nov. 1985 to Oct. 1987. These data were retrieved from measurements made by the shortwave wide-field-of-view radiometer of the Earth Radiation Budget (ERB) instrument aboard the Nimbus 7 spacecraft. Profiles of zonal mean albedos and absorbed solar radiation were tabulated. These geographical distributions are provided as a resource for researchers studying the radiation budget of the Earth. The El Nino/Southern Oscillation event of 1986-1987 is included in this data set. This atlas of albedo and absorbed solar radiation extends to 12 years the period covered by two similar atlases: NASA RP-1230 (Jul. 1975 - Oct. 1978) and NASA RP-1231 (Nov. 1978 - Oct. 1985). These three compilations complement the atlases of outgoing longwave radiation by Bess and Smith in NASA RP-1185, RP-1186, and RP-1261, which were also based on the Nimbus 6 and 7 ERB data.

Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases

PubMed Central

Zaslavsky, Ilya; Baldock, Richard A.; Boline, Jyl

2014-01-01

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today's data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems (SRSs) and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project. PMID:25309417

Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases.

PubMed

Zaslavsky, Ilya; Baldock, Richard A; Boline, Jyl

2014-01-01

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today's data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems (SRSs) and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project.

ATLAS tile calorimeter cesium calibration control and analysis software

NASA Astrophysics Data System (ADS)

Solovyanov, O.; Solodkov, A.; Starchenko, E.; Karyukhin, A.; Isaev, A.; Shalanda, N.

2008-07-01

An online control system to calibrate and monitor ATLAS Barrel hadronic calorimeter (TileCal) with a movable radioactive source, driven by liquid flow, is described. To read out and control the system an online software has been developed, using ATLAS TDAQ components like DVS (Diagnostic and Verification System) to verify the hardware before running, IS (Information Server) for data and status exchange between networked computers, and other components like DDC (DCS to DAQ Connection), to connect to PVSS-based slow control systems of Tile Calorimeter, high voltage and low voltage. A system of scripting facilities, based on Python language, is used to handle all the calibration and monitoring processes from hardware perspective to final data storage, including various abnormal situations. A QT based graphical user interface to display the status of the calibration system during the cesium source scan is described. The software for analysis of the detector response, using online data, is discussed. Performance of the system and first experience from the ATLAS pit are presented.

Object-color-signal prediction using wraparound Gaussian metamers.

PubMed

Mirzaei, Hamidreza; Funt, Brian

2014-07-01

Alexander Logvinenko introduced an object-color atlas based on idealized reflectances called rectangular metamers in 2009. For a given color signal, the atlas specifies a unique reflectance that is metameric to it under the given illuminant. The atlas is complete and illuminant invariant, but not possible to implement in practice. He later introduced a parametric representation of the object-color atlas based on smoother "wraparound Gaussian" functions. In this paper, these wraparound Gaussians are used in predicting illuminant-induced color signal changes. The method proposed in this paper is based on computationally "relighting" that reflectance to determine what its color signal would be under any other illuminant. Since that reflectance is in the metamer set the prediction is also physically realizable, which cannot be guaranteed for predictions obtained via von Kries scaling. Testing on Munsell spectra and a multispectral image shows that the proposed method outperforms the predictions of both those based on von Kries scaling and those based on the Bradford transform.

Measurement of W boson angular distributions in events with high transverse momentum jets at √{ s} = 8 TeV using the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao de Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Chr. Dudder, A.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. 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R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shirabe, S.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spannowsky, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, M.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-02-01

The W boson angular distribution in events with high transverse momentum jets is measured using data collected by the ATLAS experiment from proton-proton collisions at a centre-of-mass energy √{ s} = 8 TeV at the Large Hadron Collider, corresponding to an integrated luminosity of 20.3 fb-1. The focus is on the contributions to W +jets processes from real W emission, which is achieved by studying events where a muon is observed close to a high transverse momentum jet. At small angular separations, these contributions are expected to be large. Various theoretical models of this process are compared to the data in terms of the absolute cross-section and the angular distributions of the muon from the leptonic W decay.

Scalable and fail-safe deployment of the ATLAS Distributed Data Management system Rucio

NASA Astrophysics Data System (ADS)

Lassnig, M.; Vigne, R.; Beermann, T.; Barisits, M.; Garonne, V.; Serfon, C.

2015-12-01

This contribution details the deployment of Rucio, the ATLAS Distributed Data Management system. The main complication is that Rucio interacts with a wide variety of external services, and connects globally distributed data centres under different technological and administrative control, at an unprecedented data volume. It is therefore not possible to create a duplicate instance of Rucio for testing or integration. Every software upgrade or configuration change is thus potentially disruptive and requires fail-safe software and automatic error recovery. Rucio uses a three-layer scaling and mitigation strategy based on quasi-realtime monitoring. This strategy mainly employs independent stateless services, automatic failover, and service migration. The technologies used for deployment and mitigation include OpenStack, Puppet, Graphite, HAProxy and Apache. In this contribution, the interplay between these components, their deployment, software mitigation, and the monitoring strategy are discussed.

Operating Dedicated Data Centers - Is It Cost-Effective?

NASA Astrophysics Data System (ADS)

Ernst, M.; Hogue, R.; Hollowell, C.; Strecker-Kellog, W.; Wong, A.; Zaytsev, A.

2014-06-01

The advent of cloud computing centres such as Amazon's EC2 and Google's Computing Engine has elicited comparisons with dedicated computing clusters. Discussions on appropriate usage of cloud resources (both academic and commercial) and costs have ensued. This presentation discusses a detailed analysis of the costs of operating and maintaining the RACF (RHIC and ATLAS Computing Facility) compute cluster at Brookhaven National Lab and compares them with the cost of cloud computing resources under various usage scenarios. An extrapolation of likely future cost effectiveness of dedicated computing resources is also presented.

Catalog and Atlas from a Sensitive 1.5 GHz Radio Survey Around the North Ecliptic Pole

DTIC Science & Technology

1994-02-28

Physik D T 17(C Garching, Germany F ’, F P. REICH R. WIELEBINSKI Max-Planck-Institutfiir Radioastronomie Bonn, Germany 94-09976 February 28, 1994 11...lnstitut fur Radioastronomie , Bonn, Germany 12a. DISTRIBUTION/AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for public release; distribution

System-of-Systems Technology-Portfolio-Analysis Tool

NASA Technical Reports Server (NTRS)

O'Neil, Daniel; Mankins, John; Feingold, Harvey; Johnson, Wayne

2012-01-01

Advanced Technology Life-cycle Analysis System (ATLAS) is a system-of-systems technology-portfolio-analysis software tool. ATLAS affords capabilities to (1) compare estimates of the mass and cost of an engineering system based on competing technological concepts; (2) estimate life-cycle costs of an outer-space-exploration architecture for a specified technology portfolio; (3) collect data on state-of-the-art and forecasted technology performance, and on operations and programs; and (4) calculate an index of the relative programmatic value of a technology portfolio. ATLAS facilitates analysis by providing a library of analytical spreadsheet models for a variety of systems. A single analyst can assemble a representation of a system of systems from the models and build a technology portfolio. Each system model estimates mass, and life-cycle costs are estimated by a common set of cost models. Other components of ATLAS include graphical-user-interface (GUI) software, algorithms for calculating the aforementioned index, a technology database, a report generator, and a form generator for creating the GUI for the system models. At the time of this reporting, ATLAS is a prototype, embodied in Microsoft Excel and several thousand lines of Visual Basic for Applications that run on both Windows and Macintosh computers.

The EPTN consensus-based atlas for CT- and MR-based contouring in neuro-oncology.

PubMed

Eekers, Daniëlle Bp; In 't Ven, Lieke; Roelofs, Erik; Postma, Alida; Alapetite, Claire; Burnet, Neil G; Calugaru, Valentin; Compter, Inge; Coremans, Ida E M; Høyer, Morton; Lambrecht, Maarten; Nyström, Petra Witt; Romero, Alejandra Méndez; Paulsen, Frank; Perpar, Ana; de Ruysscher, Dirk; Renard, Laurette; Timmermann, Beate; Vitek, Pavel; Weber, Damien C; van der Weide, Hiske L; Whitfield, Gillian A; Wiggenraad, Ruud; Troost, Esther G C

2018-03-13

To create a digital, online atlas for organs at risk (OAR) delineation in neuro-oncology based on high-quality computed tomography (CT) and magnetic resonance (MR) imaging. CT and 3 Tesla (3T) MR images (slice thickness 1 mm with intravenous contrast agent) were obtained from the same patient and subsequently fused. In addition, a 7T MR without intravenous contrast agent was obtained from a healthy volunteer. Based on discussion between experienced radiation oncologists, the clinically relevant organs at risk (OARs) to be included in the atlas for neuro-oncology were determined, excluding typical head and neck OARs previously published. The draft atlas was delineated by a senior radiation oncologist, 2 residents in radiation oncology, and a senior neuro-radiologist incorporating relevant available literature. The proposed atlas was then critically reviewed and discussed by European radiation oncologists until consensus was reached. The online atlas includes one CT-scan at two different window settings and one MR scan (3T) showing the OARs in axial, coronal and sagittal view. This manuscript presents the three-dimensional descriptions of the fifteen consensus OARs for neuro-oncology. Among these is a new OAR relevant for neuro-cognition, the posterior cerebellum (illustrated on 7T MR images). In order to decrease inter- and intra-observer variability in delineating OARs relevant for neuro-oncology and thus derive consistent dosimetric data, we propose this atlas to be used in photon and particle therapy. The atlas is available online at www.cancerdata.org and will be updated whenever required. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease. PMID:26023913

Lunar Orbiter II - Photographic Mission Summary

NASA Technical Reports Server (NTRS)

1967-01-01

Lunar Orbiter II photography of landing sites, and spacecraft systems performance. The second of five Lunar Orbiter spacecraft was successfully launched from Launch Complex 13 at the Air Force Eastern Test Range by an Atlas-Agena launch vehicle at 23:21 GMT on November 6, 1966. Tracking data from the Cape Kennedy and Grand Bahama tracking stations were used to control and guide the launch vehicle during Atlas powered flight. The Agena spacecraft combination was maneuvered into a 100-nautical-mile-altitude Earth orbit by the preset on-board Agena computer. In addition, the Agena computer determined the maneuver 1 and engine-bum period required to inject the spacecraft on the cislunar trajectory 20 minutes after launch. Tracking data from the downrange stations and the Johannesburg, South Africa station were used to monitor the entire boost trajectory.

Ionization ratios and elemental abundances in the atmosphere of 68 Tauri

NASA Astrophysics Data System (ADS)

Aouina, A.; Monier, R.

2017-12-01

We have derived the ionization ratios of twelve elements in the atmosphere of the star 68 Tauri (HD 27962) using an ATLAS9 model atmosphere with 72 layers computed for the effective temperature and surface gravity of the star. We then computed a grid of synthetic spectra generated by SYNSPEC49 based on an ATLAS9 model atmosphere in order to model one high resolution spectrum secured by one of us (RM) with the échelle spectrograph SOPHIE at Observatoire de Haute Provence. We could determine the abundances of several elements in their dominant ionization stage, including those defining the Am phenomenon. We thus provide new abundance determinations for 68 Tauri using updated accurate atomic data retrieved from the NIST database which extend previous abundance works.

The Ocean Gene Atlas: exploring the biogeography of plankton genes online.

PubMed

Villar, Emilie; Vannier, Thomas; Vernette, Caroline; Lescot, Magali; Cuenca, Miguelangel; Alexandre, Aurélien; Bachelerie, Paul; Rosnet, Thomas; Pelletier, Eric; Sunagawa, Shinichi; Hingamp, Pascal

2018-05-21

The Ocean Gene Atlas is a web service to explore the biogeography of genes from marine planktonic organisms. It allows users to query protein or nucleotide sequences against global ocean reference gene catalogs. With just one click, the abundance and location of target sequences are visualized on world maps as well as their taxonomic distribution. Interactive results panels allow for adjusting cutoffs for alignment quality and displaying the abundances of genes in the context of environmental features (temperature, nutrients, etc.) measured at the time of sampling. The ease of use enables non-bioinformaticians to explore quantitative and contextualized information on genes of interest in the global ocean ecosystem. Currently the Ocean Gene Atlas is deployed with (i) the Ocean Microbial Reference Gene Catalog (OM-RGC) comprising 40 million non-redundant mostly prokaryotic gene sequences associated with both Tara Oceans and Global Ocean Sampling (GOS) gene abundances and (ii) the Marine Atlas of Tara Ocean Unigenes (MATOU) composed of >116 million eukaryote unigenes. Additional datasets will be added upon availability of further marine environmental datasets that provide the required complement of sequence assemblies, raw reads and contextual environmental parameters. Ocean Gene Atlas is a freely-available web service at: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/.

ATLAS Metadata Infrastructure Evolution for Run 2 and Beyond

NASA Astrophysics Data System (ADS)

van Gemmeren, P.; Cranshaw, J.; Malon, D.; Vaniachine, A.

2015-12-01

ATLAS developed and employed for Run 1 of the Large Hadron Collider a sophisticated infrastructure for metadata handling in event processing jobs. This infrastructure profits from a rich feature set provided by the ATLAS execution control framework, including standardized interfaces and invocation mechanisms for tools and services, segregation of transient data stores with concomitant object lifetime management, and mechanisms for handling occurrences asynchronous to the control framework's state machine transitions. This metadata infrastructure is evolving and being extended for Run 2 to allow its use and reuse in downstream physics analyses, analyses that may or may not utilize the ATLAS control framework. At the same time, multiprocessing versions of the control framework and the requirements of future multithreaded frameworks are leading to redesign of components that use an incident-handling approach to asynchrony. The increased use of scatter-gather architectures, both local and distributed, requires further enhancement of metadata infrastructure in order to ensure semantic coherence and robust bookkeeping. This paper describes the evolution of ATLAS metadata infrastructure for Run 2 and beyond, including the transition to dual-use tools—tools that can operate inside or outside the ATLAS control framework—and the implications thereof. It further examines how the design of this infrastructure is changing to accommodate the requirements of future frameworks and emerging event processing architectures.

EnviroAtlas Connects Urban Ecosystem Services and Human ...

EPA Pesticide Factsheets

Ecosystem services in urban areas can improve public health and well-being by mitigating natural and anthropogenic pollution, and by promoting healthy lifestyles that include engagement with nature and enhanced opportunities for physical activity and social interaction. EPA’s EnviroAtlas online mapping tool identifies urban environmental features linked in the scientific and medical literature to specific aspects of public health and well-being. EnviroAtlas researchers have synthesized newly-generated one-meter resolution landcover data, downscaled census population data, and other existing datasets such as roads and parks. Resulting geospatial metrics represent health-related indicators of urban ecosystem services supply and demand by census block-group and finer scales. EnviroAtlas maps include percent of the population with limited window views of trees, tree cover along walkable roads, overall neighborhood green space, and proximity to parks. Demographic data can be overlaid to perform analyses of disproportionate distribution of urban ecosystem services across population groups. Together with the Eco-Health Relationship Browser, EnviroAtlas data can be linked to numerous aspects of public health and well-being including school performance, physical fitness, social capital, and longevity. EnviroAtlas maps have been developed using consistent methods to allow for comparisons between neighborhoods and across multiple U.S. communities. To feature eco-heal

Probabilistic atlas based labeling of the cerebral vessel tree

NASA Astrophysics Data System (ADS)

Van de Giessen, Martijn; Janssen, Jasper P.; Brouwer, Patrick A.; Reiber, Johan H. C.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2015-03-01

Preoperative imaging of the cerebral vessel tree is essential for planning therapy on intracranial stenoses and aneurysms. Usually, a magnetic resonance angiography (MRA) or computed tomography angiography (CTA) is acquired from which the cerebral vessel tree is segmented. Accurate analysis is helped by the labeling of the cerebral vessels, but labeling is non-trivial due to anatomical topological variability and missing branches due to acquisition issues. In recent literature, labeling the cerebral vasculature around the Circle of Willis has mainly been approached as a graph-based problem. The most successful method, however, requires the definition of all possible permutations of missing vessels, which limits application to subsets of the tree and ignores spatial information about the vessel locations. This research aims to perform labeling using probabilistic atlases that model spatial vessel and label likelihoods. A cerebral vessel tree is aligned to a probabilistic atlas and subsequently each vessel is labeled by computing the maximum label likelihood per segment from label-specific atlases. The proposed method was validated on 25 segmented cerebral vessel trees. Labeling accuracies were close to 100% for large vessels, but dropped to 50-60% for small vessels that were only present in less than 50% of the set. With this work we showed that using solely spatial information of the vessel labels, vessel segments from stable vessels (>50% presence) were reliably classified. This spatial information will form the basis for a future labeling strategy with a very loose topological model.

The informatics of a C57BL/6J mouse brain atlas.

PubMed

MacKenzie-Graham, Allan; Jones, Eagle S; Shattuck, David W; Dinov, Ivo D; Bota, Mihail; Toga, Arthur W

2003-01-01

The Mouse Atlas Project (MAP) aims to produce a framework for organizing and analyzing the large volumes of neuroscientific data produced by the proliferation of genetically modified animals. Atlases provide an invaluable aid in understanding the impact of genetic manipulations by providing a standard for comparison. We use a digital atlas as the hub of an informatics network, correlating imaging data, such as structural imaging and histology, with text-based data, such as nomenclature, connections, and references. We generated brain volumes using magnetic resonance microscopy (MRM), classical histology, and immunohistochemistry, and registered them into a common and defined coordinate system. Specially designed viewers were developed in order to visualize multiple datasets simultaneously and to coordinate between textual and image data. Researchers can navigate through the brain interchangeably, in either a text-based or image-based representation that automatically updates information as they move. The atlas also allows the independent entry of other types of data, the facile retrieval of information, and the straight-forward display of images. In conjunction with centralized servers, image and text data can be kept current and can decrease the burden on individual researchers' computers. A comprehensive framework that encompasses many forms of information in the context of anatomic imaging holds tremendous promise for producing new insights. The atlas and associated tools can be found at http://www.loni.ucla.edu/MAP.

Developing an educational curriculum for EnviroAtlas ...

EPA Pesticide Factsheets

EnviroAtlas is a web-based tool developed by the EPA and its partners, which provides interactive tools and resources for users to explore the benefits that people receive from nature, often referred to as ecosystem goods and services.Ecosystem goods and services are important to human health and well-being. Using EnviroAtlas, users can access, view, and analyze diverse information to better understand the potential impacts of decisions. EnviroAtlas provides two primary tools, the Interactive Map and the Eco-Health Relationship Browser. EnviroAtlas integrates geospatial data from a variety of sources so that users can visualize the impacts of decision-making on ecosystems. The Interactive Map allows users to investigate various ecosystem elements (i.e. land cover, pollution, and community development) and compare them across localities in the United States. The best part of the Interactive Map is that it does not require specialized software for map application; rather, it requires only a computer and an internet connection. As such, it can be used as a powerful educational tool. The Eco-Health Relationship Browser is also a web-based, highly interactive tool that uses existing scientific literature to visually demonstrate the connections between the environment and human health.As an ASPPH/EPA Fellow with a background in environmental science and secondary science education, I am currently developing an educational curriculum to support the EnviroAtlas to

An automatic approach for 3D registration of CT scans

NASA Astrophysics Data System (ADS)

Hu, Yang; Saber, Eli; Dianat, Sohail; Vantaram, Sreenath Rao; Abhyankar, Vishwas

2012-03-01

CT (Computed tomography) is a widely employed imaging modality in the medical field. Normally, a volume of CT scans is prescribed by a doctor when a specific region of the body (typically neck to groin) is suspected of being abnormal. The doctors are required to make professional diagnoses based upon the obtained datasets. In this paper, we propose an automatic registration algorithm that helps healthcare personnel to automatically align corresponding scans from 'Study' to 'Atlas'. The proposed algorithm is capable of aligning both 'Atlas' and 'Study' into the same resolution through 3D interpolation. After retrieving the scanned slice volume in the 'Study' and the corresponding volume in the original 'Atlas' dataset, a 3D cross correlation method is used to identify and register various body parts.

New experimental results in atlas-based brain morphometry

NASA Astrophysics Data System (ADS)

Gee, James C.; Fabella, Brian A.; Fernandes, Siddharth E.; Turetsky, Bruce I.; Gur, Ruben C.; Gur, Raquel E.

1999-05-01

In a previous meeting, we described a computational approach to MRI morphometry, in which a spatial warp mapping a reference or atlas image into anatomic alignment with the subject is first inferred. Shape differences with respect to the atlas are then studied by calculating the pointwise Jacobian determinant for the warp, which provides a measure of the change in differential volume about a point in the reference as it transforms to its corresponding position in the subject. In this paper, the method is used to analyze sex differences in the shape and size of the corpus callosum in an ongoing study of a large population of normal controls. The preliminary results of the current analysis support findings in the literature that have observed the splenium to be larger in females than in males.

Data mining for average images in a digital hand atlas

NASA Astrophysics Data System (ADS)

Zhang, Aifeng; Cao, Fei; Pietka, Ewa; Liu, Brent J.; Huang, H. K.

2004-04-01

Bone age assessment is a procedure performed in pediatric patients to quickly evaluate parameters of maturation and growth from a left hand and wrist radiograph. Pietka and Cao have developed a Computer-aided diagnosis (CAD) method of bone age assessment based on a digital hand atlas. The aim of this paper is to extend their work by automatically select the best representative image from a group of normal children based on specific bony features that reflect skeletal maturity. The group can be of any ethnic origin and gender from one year to 18 year old in the digital atlas. This best representative image is defined as the "average" image of the group that can be augmented to Piekta and Cao's method to facilitate in the bone age assessment process.

Research on Spectroscopy, Opacity, and Atmospheres

NASA Technical Reports Server (NTRS)

Oliversen, Ronald (Technical Monitor); Kurucz, Robert L.

2004-01-01

I propose to continue providing observers with basic data for interpreting spectra from stars, novas, supernovas, clusters, and galaxies. These data will include allowed forbidden line lists both laboratory and computed, for the first five to ten ions of all atoms and for all relevant diatomic molecules. I will eventually expend to all ions of the first thirty elements to treat far UV end X-ray spectra, and for envelope opacities. I also include triatomic molecules providing by other researchers. I have made CDs with Partridge and Schwanke's water data for work on M stars.The luna data also serve as input to my model atmosphere and synthesis programs that generated energy distributions, photometry, limb darkening, and spectra that can be used for planning observations and for fitting observed spectra. The spectrum synthesis programs produce detailed plots with the line identified. Grids of stellar spectra can be used for radial velocity-, rotation-, or abundance templates and for population synthesis. I am fitting spectra of bright stars to test the data and to produce atlases to guide observer. For each star the whole spectrum is computed from the UV to the far IR. The line data, opacities, models, spectra, and programs are freely distributed on CDs and on my web site and represent a unique resource for many NASA programs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, T; Ruan, D

Purpose: The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi-atlas-based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi-atlas-based image segmentation. Methods: We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non-decreasing function with additive random perturbations. Subsequently, a surrogate’s ability to prognosticate the oracle order for atlas subset selectionmore » is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images. Results: The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly-used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation. Conclusion: This work has developed an efficacious probabilistic model to characterize the image-based surrogate metric on atlas selection. Analytical insights lead to valid guiding principles on fusion set size design.« less

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners

PubMed Central

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this “Atlas-T1w-DUTE” approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the “silver standard”; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally. PMID:24753982

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

Is Greulich and Pyle atlas still a good reference for bone age assessment?

NASA Astrophysics Data System (ADS)

Zhang, Aifeng; Tsao, Sinchai; Sayre, James W.; Gertych, Arkadiusz; Liu, Brent J.; Huang, H. K.

2007-03-01

The most commonly used method for bone age assessment in clinical practice is the book atlas matching method developed by Greulich and Pyle in the 1950s. Due to changes in both population diversity and nutrition in the United States, this atlas may no longer be a good reference. An updated data set becomes crucial to improve the bone age assessment process. Therefore, a digital hand atlas was built with 1,100 children hand images, along with patient information and radiologists' readings, of normal Caucasian (CAU), African American (BLK), Hispanic (HIS), and Asian (ASI) males (M) and females (F) with ages ranging from 0 - 18 years. This data was collected from Childrens' Hospital Los Angeles. A computer-aided-diagnosis (CAD) method has been developed based on features extracted from phalangeal regions of interest (ROIs) and carpal bone ROIs from this digital hand atlas. Using the data collected along with the Greulich and Pyle Atlas-based readings and CAD results, this paper addresses this question: "Do different ethnicities and gender have different bone growth patterns?" To help with data analysis, a novel web-based visualization tool was developed to demonstrate bone growth diversity amongst differing gender and ethnic groups using data collected from the Digital Atlas. The application effectively demonstrates a discrepancy of bone growth pattern amongst different populations based on race and gender. It also has the capability of helping a radiologist determine the normality of skeletal development of a particular patient by visualizing his or her chronological age, radiologist reading, and CAD assessed bone age relative to the accuracy of the P&G method.

Distribution of prostate nodes: a PET/CT-derived anatomic atlas of prostate cancer patients before and after surgical treatment.

PubMed

Hegemann, Nina-Sophie; Wenter, Vera; Spath, Sonja; Kusumo, Nadia; Li, Minglun; Bartenstein, Peter; Fendler, Wolfgang P; Stief, Christian; Belka, Claus; Ganswindt, Ute

2016-03-11

In order to define adequate radiation portals in nodal positive prostate cancer a detailed knowledge of the anatomic lymph-node distribution is mandatory. We therefore systematically analyzed the localization of Choline PET/CT positive lymph nodes and compared it to the RTOG recommendation of pelvic CTV, as well as to previous work, the SPECT sentinel lymph node atlas. Thirty-two patients being mostly high risk patients with a PSA of 12.5 ng/ml (median) received PET/CT before any treatment. Eighty-seven patients received PET/CT for staging due to biochemical failure with a median PSA of 3.12 ng/ml. Each single PET-positive lymph node was manually contoured in a "virtual" patient dataset to achieve a 3-D visualization, resulting in an atlas of the cumulative PET positive lymph node distribution. Further the PET-positive lymph node location in each patient was assessed with regard to the existence of a potential geographic miss (i.e. PET-positive lymph nodes that would not have been treated adequately by the RTOG consensus on CTV definition of pelvic lymph nodes). Seventy-eight and 209 PET positive lymph nodes were detected in patients with no prior treatment and in postoperative patients, respectively. The most common sites of PET positive lymph nodes in patients with no prior treatment were external iliac (32.1 %), followed by common iliac (23.1 %) and para-aortic (19.2 %). In postoperative patients the most common sites of PET positive lymph nodes were common iliac (24.9 %), followed by external iliac (23.0 %) and para-aortic (20.1 %). In patients with no prior treatment there were 34 (43.6 %) and in postoperative patients there were 77 (36.8 %) of all detected lymph nodes that would not have been treated adequately using the RTOG CTV. We compared the distribution of lymph nodes gained by Choline PET/CT to the preexisting SPECT sentinel lymph node atlas and saw an overall good congruence. Choline PET/CT and SPECT sentinel lymph node atlas are comparable to each other. More than one-third of the PET positive lymph nodes in patients with no prior treatment and in postoperative patients would not have been treated adequately using the RTOG CTV. To reduce geographical miss, image based definition of an individual target volume is necessary.

Context-aware distributed cloud computing using CloudScheduler

NASA Astrophysics Data System (ADS)

Seuster, R.; Leavett-Brown, CR; Casteels, K.; Driemel, C.; Paterson, M.; Ring, D.; Sobie, RJ; Taylor, RP; Weldon, J.

2017-10-01

The distributed cloud using the CloudScheduler VM provisioning service is one of the longest running systems for HEP workloads. It has run millions of jobs for ATLAS and Belle II over the past few years using private and commercial clouds around the world. Our goal is to scale the distributed cloud to the 10,000-core level, with the ability to run any type of application (low I/O, high I/O and high memory) on any cloud. To achieve this goal, we have been implementing changes that utilize context-aware computing designs that are currently employed in the mobile communication industry. Context-awareness makes use of real-time and archived data to respond to user or system requirements. In our distributed cloud, we have many opportunistic clouds with no local HEP services, software or storage repositories. A context-aware design significantly improves the reliability and performance of our system by locating the nearest location of the required services. We describe how we are collecting and managing contextual information from our workload management systems, the clouds, the virtual machines and our services. This information is used not only to monitor the system but also to carry out automated corrective actions. We are incrementally adding new alerting and response services to our distributed cloud. This will enable us to scale the number of clouds and virtual machines. Further, a context-aware design will enable us to run analysis or high I/O application on opportunistic clouds. We envisage an open-source HTTP data federation (for example, the DynaFed system at CERN) as a service that would provide us access to existing storage elements used by the HEP experiments.

Possibilities of GIS for Plant Introduction

USDA-ARS?s Scientific Manuscript database

The Ecological Atlas of Russia and Neighboring Countries was used to predict the distribution of introduced species. Acer negundo was used as an example and an ecological model was developed using the natural distribution of the species in North America and some American ecological variables: namely...

Pinning down the large- x gluon with NNLO top-quark pair differential distributions

NASA Astrophysics Data System (ADS)

Czakon, Michał; Hartland, Nathan P.; Mitov, Alexander; Nocera, Emanuele R.; Rojo, Juan

2017-04-01

Top-quark pair production at the LHC is directly sensitive to the gluon PDF at large x. While total cross-section data is already included in several PDF determinations, differential distributions are not, because the corresponding NNLO calculations have become available only recently. In this work we study the impact on the large- x gluon of top-quark pair differential distributions measured by ATLAS and CMS at √{s}=8 TeV. Our analysis, performed in the NNPDF3.0 framework at NNLO accuracy, allows us to identify the optimal combination of LHC top-quark pair measurements that maximize the constraints on the gluon, as well as to assess the compatibility between ATLAS and CMS data. We find that differential distributions from top-quark pair production provide significant constraints on the large- x gluon, comparable to those obtained from inclusive jet production data, and thus should become an important ingredient for the next generation of global PDF fits.

The Geogenomic Mutational Atlas of Pathogens (GoMAP) Web System

PubMed Central

Sargeant, David P.; Hedden, Michael W.; Deverasetty, Sandeep; Strong, Christy L.; Alaniz, Izua J.; Bartlett, Alexandria N.; Brandon, Nicholas R.; Brooks, Steven B.; Brown, Frederick A.; Bufi, Flaviona; Chakarova, Monika; David, Roxanne P.; Dobritch, Karlyn M.; Guerra, Horacio P.; Levit, Kelvy S.; Mathew, Kiran R.; Matti, Ray; Maza, Dorothea Q.; Mistry, Sabyasachy; Novakovic, Nemanja; Pomerantz, Austin; Rafalski, Timothy F.; Rathnayake, Viraj; Rezapour, Noura; Ross, Christian A.; Schooler, Steve G.; Songao, Sarah; Tuggle, Sean L.; Wing, Helen J.; Yousif, Sandy; Schiller, Martin R.

2014-01-01

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/ PMID:24675726

The Geogenomic Mutational Atlas of Pathogens (GoMAP) web system.

PubMed

Sargeant, David P; Hedden, Michael W; Deverasetty, Sandeep; Strong, Christy L; Alaniz, Izua J; Bartlett, Alexandria N; Brandon, Nicholas R; Brooks, Steven B; Brown, Frederick A; Bufi, Flaviona; Chakarova, Monika; David, Roxanne P; Dobritch, Karlyn M; Guerra, Horacio P; Levit, Kelvy S; Mathew, Kiran R; Matti, Ray; Maza, Dorothea Q; Mistry, Sabyasachy; Novakovic, Nemanja; Pomerantz, Austin; Rafalski, Timothy F; Rathnayake, Viraj; Rezapour, Noura; Ross, Christian A; Schooler, Steve G; Songao, Sarah; Tuggle, Sean L; Wing, Helen J; Yousif, Sandy; Schiller, Martin R

2014-01-01

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Alaska Species and Ecoregions

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Strickland, Laura E.; Shafer, Sarah L.; Pelltier, Richard T.; Bartlein, Patrick J.

2006-01-01

Climate is the primary factor in controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges is only now beginning to be quantified. Preceding volumes of this atlas explored the continental-scale relations between climatic parameters and the distributions of woody plant species across all of the continent of North America. This volume presents similar information for important woody species, groups of species, and ecoregions in more detail for the State of Alaska. For these analyses, we constructed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America from instrumental weather records. We obtained a digital representation of the geographic distribution of each species or ecoregion, either from a published source or by digitizing the published distributions ourselves. The presence or absence of each species or ecoregion was then determined for each point on the 25-kilometer grid, thus providing a basis for comparison of the climatic data with the geographic distribution of each species or ecoregion. The relations between climate and these distributions are presented in graphical and tabular form.

Measuring charged particle multiplicity with early ATLAS public data

NASA Astrophysics Data System (ADS)

Üstün, G.; Barut, E.; Bektaş, E.; Özcan, V. E.

2017-07-01

We study 100 images of early LHC collisions that were recorded by the ATLAS experiment and made public for outreach purposes, and extract the charged particle multiplicity as a function of momentum for proton-proton collisions at a centre-of-mass energy of 7 TeV. As these collisions have already been pre-processed by the ATLAS Collaboration, the particle tracks are visible, but are available to the public only in the form of low-resolution bitmaps. We describe two separate image processing methods, one based on the industry-standard OpenCV library and C++, another based on self-developed algorithms in Python. We present our analysis of the transverse momentum and azimuthal angle distributions of the particles, in agreement with the literature.

ATLAS Data Management Accounting with Hadoop Pig and HBase

NASA Astrophysics Data System (ADS)

Lassnig, Mario; Garonne, Vincent; Dimitrov, Gancho; Canali, Luca

2012-12-01

The ATLAS Distributed Data Management system requires accounting of its contents at the metadata layer. This presents a hard problem due to the large scale of the system, the high dimensionality of attributes, and the high rate of concurrent modifications of data. The system must efficiently account more than 90PB of disk and tape that store upwards of 500 million files across 100 sites globally. In this work a generic accounting system is presented, which is able to scale to the requirements of ATLAS. The design and architecture is presented, and the implementation is discussed. An emphasis is placed on the design choices such that the underlying data models are generally applicable to different kinds of accounting, reporting and monitoring.

Determination of the strange-quark density of the proton from ATLAS measurements of the W→ℓν and Z→ℓℓ cross sections.

PubMed

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Stark, J; Staroba, P; Starovoitov, P; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stevenson, K; Stewart, G A; Stillings, J A; Stockton, M C; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Strube, J; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Soh, D A; Su, D; Subramania, H S; Succurro, A; Sugaya, Y; Sugimoto, T; Suhr, C; Suita, K; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Sushkov, S; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Sviridov, Yu M; Swedish, S; Sykora, I; Sykora, T; Szeless, B; Sánchez, J; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tamsett, M C; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanaka, Y; Tanasijczuk, A J; Tani, K; Tannoury, N; Tappern, G P; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tatarkhanov, M; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Thadome, J; Therhaag, J; Theveneaux-Pelzer, T; Thioye, M; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tipton, P; Tique Aires Viegas, F J; Tisserant, S; Toczek, B; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokunaga, K; Tokushuku, K; Tollefson, K; Tomoto, M; Tompkins, L; Toms, K; Tong, G; Tonoyan, A; Topfel, C; Topilin, N D; Torchiani, I; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Trinh, T N; Tripiana, M F; Trischuk, W; Trivedi, A; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiakiris, M; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Turala, M; Turecek, D; Turk Cakir, I; Turlay, E; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Tzanakos, G; Uchida, K; Ueda, I; Ueno, R; Ugland, M; Uhlenbrock, M; Uhrmacher, M; Ukegawa, F; Unal, G; Underwood, D G; Undrus, A; Unel, G; Unno, Y; Urbaniec, D; Usai, G; Uslenghi, M; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valenta, J; Valente, P; Valentinetti, S; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; van der Graaf, H; van der Kraaij, E; Van Der Leeuw, R; van der Poel, E; van der Ster, D; van Eldik, N; van Gemmeren, P; van Kesteren, Z; van Vulpen, I; Vanadia, M; Vandelli, W; Vandoni, G; Vaniachine, A; Vankov, P; Vannucci, F; Varela Rodriguez, F; Vari, R; Varnes, E W; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Vegni, G; Veillet, J J; Vellidis, C; Veloso, F; Veness, R; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinek, E; Vinogradov, V B; Virchaux, M; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vlasov, N; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Loeben, J; von Radziewski, H; von Toerne, E; Vorobel, V; Vorobiev, A P; Vorwerk, V; Vos, M; Voss, R; Voss, T T; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vu Anh, T; Vuillermet, R; Vukotic, I; Wagner, W; Wagner, P; Wahlen, H; Wakabayashi, J; Walbersloh, J; Walch, S; Walder, J; Walker, R; Walkowiak, W; Wall, R; Waller, P; Wang, C; Wang, H; Wang, H; Wang, J; Wang, J; Wang, J C; Wang, R; Wang, S M; Warburton, A; Ward, C P; Warsinsky, M; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, A T; Waugh, B M; Weber, M; Weber, M S; Weber, P; Weidberg, A R; Weigell, P; Weingarten, J; Weiser, C; Wellenstein, H; Wells, P S; Wenaus, T; Wendland, D; Wendler, S; Weng, Z; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Werth, M; Wessels, M; Weydert, C; Whalen, K; Wheeler-Ellis, S J; Whitaker, S P; White, A; White, M J; Whitehead, S R; Whiteson, D; Whittington, D; Wicek, F; Wicke, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wijeratne, P A; Wildauer, A; Wildt, M A; Wilhelm, I; Wilkens, H G; Will, J Z; Williams, E; Williams, H H; Willis, W; Willocq, S; Wilson, J A; Wilson, M G; Wilson, A; Wingerter-Seez, I; Winkelmann, S; Winklmeier, F; Wittgen, M; Wolter, M W; Wolters, H; Wong, W C; Wooden, G; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wraight, K; Wright, C; Wright, M; Wrona, B; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wunstorf, R; Wynne, B M; Xella, S; Xiao, M; Xie, S; Xie, Y; Xu, C; Xu, D; Xu, G; Yabsley, B; Yacoob, S; Yamada, M; Yamaguchi, H; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamaoka, J; Yamazaki, T; Yamazaki, Y; Yan, Z; Yang, H; Yang, U K; Yang, Y; Yang, Y; Yang, Z; Yanush, S; Yao, Y; Yasu, Y; Ybeles Smit, G V; Ye, J; Ye, S; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Young, C; Youssef, S; Yu, D; Yu, J; Yu, J; Yuan, L; Yurkewicz, A; Zabinski, B; Zaets, V G; Zaidan, R; Zaitsev, A M; Zajacova, Z; Zanello, L; Zaytsev, A; Zeitnitz, C; Zeller, M; Zeman, M; Zemla, A; Zendler, C; Zenin, O; Zeniš, T; Zinonos, Z; Zenz, S; Zerwas, D; Zevi della Porta, G; Zhan, Z; Zhang, D; Zhang, H; Zhang, J; Zhang, X; Zhang, Z; Zhao, L; Zhao, T; Zhao, Z; Zhemchugov, A; Zheng, S; Zhong, J; Zhou, B; Zhou, N; Zhou, Y; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhuravlov, V; Zieminska, D; Zimmermann, R; Zimmermann, S; Zimmermann, S; Ziolkowski, M; Zitoun, R; Zivković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; Zolnierowski, Y; Zsenei, A; zur Nedden, M; Zutshi, V; Zwalinski, L

2012-07-06

A QCD analysis is reported of ATLAS data on inclusive W(±) and Z boson production in pp collisions at the LHC, jointly with ep deep-inelastic scattering data from HERA. The ATLAS data exhibit sensitivity to the light quark sea composition and magnitude at Bjorken x∼0.01. Specifically, the data support the hypothesis of a symmetric composition of the light quark sea at low x. The ratio of the strange-to-down sea quark distributions is determined to be 1.00(-0.28)(+0.25) at absolute four-momentum transfer squared Q(2)=1.9  GeV(2) and x=0.023.

Mechanisms Controlling Hypoxia Data Atlas: High-resolution hydrographic and chemical observations from 2003-2014

NASA Astrophysics Data System (ADS)

Zimmerle, H.; DiMarco, S. F.

2016-02-01

The Mechanisms Controlling Hypoxia (MCH) project consisted of 31 cruises from 2003-2014 with an objective to investigate the physical and biogeochemical processes that control the hypoxic zone on the Texas-Louisiana shelf in the northern Gulf of Mexico. The known seasonal low oxygen conditions in this region are the result of river-derived nutrients, freshwater input, and wind. The MCH Data Atlas showcases in situ data and subsequent products produced during the duration of the project, focusing on oceanographic observations from 2010-2014. The Atlas features 230 high-resolution vertical sections from nine cruises using the Acrobat undulating towed vehicle that contained a CTD along with sensors measuring oxygen, fluorescence, and turbidity. Vertical profiles along the 20-meter isobaths section feature temperature, salinity, chlorophyll, and dissolved oxygen from the Acrobat towfish and CTD rosette as well as separate selected profiles from the CTD. Surface planview maps show the horizontal distribution of temperature, salinity, chlorophyll, beam transmission, and CDOM observed by the shipboard flow-through system. Bottom planview maps present the horizontal distribution of dissolved oxygen as well as temperature and salinity from the CTD rosette and Acrobat towfish along the shelf's seafloor. Informational basemaps display the GPS cruise track as well as individual CTD stations for each cruise. The shelf concentrations of CTD rosette bottle nutrients, including nitrate, nitrite, phosphate, ammonia, and silicate are displayed in select plots. Shipboard ADCP current velocity fields are also represented. MCH datasets and additional products are featured as an electronic version to compliment the published atlas. The MCH Data Atlas provides a showcase for the spatial and temporal variability of the environmental parameters associated with the annual hypoxic event and will be a useful tool in the continued monitoring and assessment of Gulf coastal hypoxia.

A cross-validated cytoarchitectonic atlas of the human ventral visual stream.

PubMed

Rosenke, Mona; Weiner, Kevin S; Barnett, Michael A; Zilles, Karl; Amunts, Katrin; Goebel, Rainer; Grill-Spector, Kalanit

2018-04-15

The human ventral visual stream consists of several areas that are considered processing stages essential for perception and recognition. A fundamental microanatomical feature differentiating areas is cytoarchitecture, which refers to the distribution, size, and density of cells across cortical layers. Because cytoarchitectonic structure is measured in 20-micron-thick histological slices of postmortem tissue, it is difficult to assess (a) how anatomically consistent these areas are across brains and (b) how they relate to brain parcellations obtained with prevalent neuroimaging methods, acquired at the millimeter and centimeter scale. Therefore, the goal of this study was to (a) generate a cross-validated cytoarchitectonic atlas of the human ventral visual stream on a whole brain template that is commonly used in neuroimaging studies and (b) to compare this atlas to a recently published retinotopic parcellation of visual cortex (Wang et al., 2014). To achieve this goal, we generated an atlas of eight cytoarchitectonic areas: four areas in the occipital lobe (hOc1-hOc4v) and four in the fusiform gyrus (FG1-FG4), then we tested how the different alignment techniques affect the accuracy of the resulting atlas. Results show that both cortex-based alignment (CBA) and nonlinear volumetric alignment (NVA) generate an atlas with better cross-validation performance than affine volumetric alignment (AVA). Additionally, CBA outperformed NVA in 6/8 of the cytoarchitectonic areas. Finally, the comparison of the cytoarchitectonic atlas to a retinotopic atlas shows a clear correspondence between cytoarchitectonic and retinotopic areas in the ventral visual stream. The successful performance of CBA suggests a coupling between cytoarchitectonic areas and macroanatomical landmarks in the human ventral visual stream, and furthermore, that this coupling can be utilized for generating an accurate group atlas. In addition, the coupling between cytoarchitecture and retinotopy highlights the potential use of this atlas in understanding how anatomical features contribute to brain function. We make this cytoarchitectonic atlas freely available in both BrainVoyager and FreeSurfer formats (http://vpnl.stanford.edu/vcAtlas). The availability of this atlas will enable future studies to link cytoarchitectonic organization to other parcellations of the human ventral visual stream with potential to advance the understanding of this pathway in typical and atypical populations. Copyright © 2017 Elsevier Inc. All rights reserved.

Search for new phenomena in dijet angular distributions in proton-proton collisions at s = 8 TeV measured with the ATLAS detector

DOE PAGES

Aad, G.

2015-06-04

In this study, a search for new phenomena in LHC proton-proton collisions at a center-of-mass energy of √s=8 TeV was performed with the ATLAS detector using an integrated luminosity of 17.3 fb -1. The angular distributions are studied in events with at least two jets; the highest dijet mass observed is 5.5 TeV. All angular distributions are consistent with the predictions of the standard model. In a benchmark model of quark contact interactions, a compositeness scale below 8.1 TeV in a destructive interference scenario and 12.0 TeV in a constructive interference scenario is excluded at 95% C.L.; median expected limitsmore » are 8.9 TeV for the destructive interference scenario and 14.1 TeV for the constructive interference scenario.« less

Measurement of W boson angular distributions in events with high transverse momentum jets at s = 8   TeV using the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

The W boson angular distribution in events with high transverse momentum jets is measured using data collected by the ATLAS experiment from proton–proton collisions at a centre-of-mass energy √s=8 TeV at the Large Hadron Collider, corresponding to an integrated luminosity of 20.3 fb -1 . The focus is on the contributions to W+jets processes from real W emission, which is achieved by studying events where a muon is observed close to a high transverse momentum jet. At small angular separations, these contributions are expected to be large. Various theoretical models of this process are compared to the data inmore » terms of the absolute cross-section and the angular distributions of the muon from the leptonic W decay.« less

The ATLAS TAGS database distribution and management - Operational challenges of a multi-terabyte distributed database

NASA Astrophysics Data System (ADS)

Viegas, F.; Malon, D.; Cranshaw, J.; Dimitrov, G.; Nowak, M.; Nairz, A.; Goossens, L.; Gallas, E.; Gamboa, C.; Wong, A.; Vinek, E.

2010-04-01

The TAG files store summary event quantities that allow a quick selection of interesting events. This data will be produced at a nominal rate of 200 Hz, and is uploaded into a relational database for access from websites and other tools. The estimated database volume is 6TB per year, making it the largest application running on the ATLAS relational databases, at CERN and at other voluntary sites. The sheer volume and high rate of production makes this application a challenge to data and resource management, in many aspects. This paper will focus on the operational challenges of this system. These include: uploading the data from files to the CERN's and remote sites' databases; distributing the TAG metadata that is essential to guide the user through event selection; controlling resource usage of the database, from the user query load to the strategy of cleaning and archiving of old TAG data.

Charged-particle distributions in pp interactions at √s=8TeV measured with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2016-07-15

This study presents measurements of distributions of charged particles which are produced in proton–proton collisions at a centre-of-mass energy of √s=8TeV and recorded by the ATLAS detector at the LHC. A special dataset recorded in 2012 with a small number of interactions per beam crossing (below 0.004) and corresponding to an integrated luminosity of 160 μb -1 was used. A minimum-bias trigger was utilised to select a data sample of more than 9 million collision events. The multiplicity, pseudorapidity, and transverse momentum distributions of charged particles are shown in different regions of kinematics and charged-particle multiplicity, including measurements of finalmore » states at high multiplicity. Finally, the results are corrected for detector effects and are compared to the predictions of various Monte Carlo event generator models which simulate the full hadronic final state.« less

Measurement of the transverse momentum distribution of W bosons in p p collisions at s = 7 TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2012-01-18

This study describes a measurement of the W boson transverse momentum distribution using ATLAS pp collision data from the 2010 run of the LHC at √s = 7 TeV, corresponding to an integrated luminosity of about 31 pb –1. Events form both W→eν and W→μν are used, and the transverse momentum of the W candidates is measured through the energy deposition in the calorimeter from the recoil of the W. The resulting distributions are unfolded to obtain the normalized differential cross sections as a function of the W boson transverse momentum. We present results for p W T < 300more » GeV in the electron and muon channels as well as for their combination, and compare the combined results to the predictions of perturbative QCD and a selection of event generators.« less

Measurement of W boson angular distributions in events with high transverse momentum jets at s = 8   TeV using the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2016-12-06

The W boson angular distribution in events with high transverse momentum jets is measured using data collected by the ATLAS experiment from proton–proton collisions at a centre-of-mass energy √s=8 TeV at the Large Hadron Collider, corresponding to an integrated luminosity of 20.3 fb -1 . The focus is on the contributions to W+jets processes from real W emission, which is achieved by studying events where a muon is observed close to a high transverse momentum jet. At small angular separations, these contributions are expected to be large. Various theoretical models of this process are compared to the data inmore » terms of the absolute cross-section and the angular distributions of the muon from the leptonic W decay.« less

Charged-particle distributions in pp interactions at √{s}=8 { TeV} measured with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Basye, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benitez Garcia, J. 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Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ueno, R.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zwalinski, L.

2016-07-01

This paper presents measurements of distributions of charged particles which are produced in proton-proton collisions at a centre-of-mass energy of √{s} = 8 TeV and recorded by the ATLAS detector at the LHC. A special dataset recorded in 2012 with a small number of interactions per beam crossing (below 0.004) and corresponding to an integrated luminosity of 160 μ b^{-1} was used. A minimum-bias trigger was utilised to select a data sample of more than 9 million collision events. The multiplicity, pseudorapidity, and transverse momentum distributions of charged particles are shown in different regions of kinematics and charged-particle multiplicity, including measurements of final states at high multiplicity. The results are corrected for detector effects and are compared to the predictions of various Monte Carlo event generator models which simulate the full hadronic final state.

Automatic Atlas Based Electron Density and Structure Contouring for MRI-based Prostate Radiation Therapy on the Cloud

NASA Astrophysics Data System (ADS)

Dowling, J. A.; Burdett, N.; Greer, P. B.; Sun, J.; Parker, J.; Pichler, P.; Stanwell, P.; Chandra, S.; Rivest-Hénault, D.; Ghose, S.; Salvado, O.; Fripp, J.

2014-03-01

Our group have been developing methods for MRI-alone prostate cancer radiation therapy treatment planning. To assist with clinical validation of the workflow we are investigating a cloud platform solution for research purposes. Benefits of cloud computing can include increased scalability, performance and extensibility while reducing total cost of ownership. In this paper we demonstrate the generation of DICOM-RT directories containing an automatic average atlas based electron density image and fast pelvic organ contouring from whole pelvis MR scans.

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas. | Office of Cancer Genomics

Cancer.gov

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified.

Limb and gravity-darkening coefficients for the TESS satellite at several metallicities, surface gravities, and microturbulent velocities

NASA Astrophysics Data System (ADS)

Claret, A.

2017-04-01

Aims: We present new gravity and limb-darkening coefficients for a wide range of effective temperatures, gravities, metallicities, and microturbulent velocities. These coefficients can be used in many different fields of stellar physics as synthetic light curves of eclipsing binaries and planetary transits, stellar diameters, line profiles in rotating stars, and others. Methods: The limb-darkening coefficients were computed specifically for the photometric system of the space mission tess and were performed by adopting the least-square method. In addition, the linear and bi-parametric coefficients, by adopting the flux conservation method, are also available. On the other hand, to take into account the effects of tidal and rotational distortions, we computed the passband gravity-darkening coefficients y(λ) using a general differential equation in which we consider the effects of convection and of the partial derivative (∂lnI(λ) /∂lng)Teff. Results: To generate the limb-darkening coefficients we adopt two stellar atmosphere models: atlas (plane-parallel) and phoenix (spherical, quasi-spherical, and r-method). The specific intensity distribution was fitted using five approaches: linear, quadratic, square root, logarithmic, and a more general one with four terms. These grids cover together 19 metallicities ranging from 10-5 up to 10+1 solar abundances, 0 ≤ log g ≤ 6.0 and 1500 K ≤Teff ≤ 50 000 K. The calculations of the gravity-darkening coefficients were performed for all plane-parallel ATLAS models. Tables 2-29 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/600/A30

An atlas of ShakeMaps for selected global earthquakes

USGS Publications Warehouse

Allen, Trevor I.; Wald, David J.; Hotovec, Alicia J.; Lin, Kuo-Wan; Earle, Paul S.; Marano, Kristin D.

2008-01-01

An atlas of maps of peak ground motions and intensity 'ShakeMaps' has been developed for almost 5,000 recent and historical global earthquakes. These maps are produced using established ShakeMap methodology (Wald and others, 1999c; Wald and others, 2005) and constraints from macroseismic intensity data, instrumental ground motions, regional topographically-based site amplifications, and published earthquake-rupture models. Applying the ShakeMap methodology allows a consistent approach to combine point observations with ground-motion predictions to produce descriptions of peak ground motions and intensity for each event. We also calculate an estimated ground-motion uncertainty grid for each earthquake. The Atlas of ShakeMaps provides a consistent and quantitative description of the distribution and intensity of shaking for recent global earthquakes (1973-2007) as well as selected historic events. As such, the Atlas was developed specifically for calibrating global earthquake loss estimation methodologies to be used in the U.S. Geological Survey Prompt Assessment of Global Earthquakes for Response (PAGER) Project. PAGER will employ these loss models to rapidly estimate the impact of global earthquakes as part of the USGS National Earthquake Information Center's earthquake-response protocol. The development of the Atlas of ShakeMaps has also led to several key improvements to the Global ShakeMap system. The key upgrades include: addition of uncertainties in the ground motion mapping, introduction of modern ground-motion prediction equations, improved estimates of global seismic-site conditions (VS30), and improved definition of stable continental region polygons. Finally, we have merged all of the ShakeMaps in the Atlas to provide a global perspective of earthquake ground shaking for the past 35 years, allowing comparison with probabilistic hazard maps. The online Atlas and supporting databases can be found at http://earthquake.usgs.gov/eqcenter/shakemap/atlas.php/.

Unconventional Signal Processing Using the Cone Kernel Time-Frequency Representation.

DTIC Science & Technology

1992-10-30

Wigner - Ville distribution ( WVD ), the Choi- Williams distribution , and the cone kernel distribution were compared with the spectrograms. Results were...ambiguity function. Figures A-18(c) and (d) are the Wigner - Ville Distribution ( WVD ) and CK-TFR Doppler maps. In this noiseless case all three exhibit...kernel is the basis for the well known Wigner - Ville distribution . In A-9(2), the cone kernel defined by Zhao, Atlas and Marks [21 is described

Review of the Cambrian volcanic activity in Morocco: geochemical fingerprints and geotectonic implications for the rifting of West Gondwana

NASA Astrophysics Data System (ADS)

Pouclet, André; El Hadi, Hassan; Álvaro, J. Javier; Bardintzeff, Jacques-Marie; Benharref, Mohammed; Fekkak, Abdelilah

2018-03-01

Volcanic activities related to the opening of a Cambrian rift in Morocco were widespread from the Fortunian to the Cambrian Epoch 3. Numerous data are available from northwestern volcanic sites, particularly in the western High Atlas, but they are scarce from the southeastern sites. New data are documented here from the volcanic formations exposed in the Jbel Tazoult n'Ouzina of the Tafilalt Province, eastern Anti-Atlas and dated to Cambrian Epoch 2-3. The Cambrian volcanic activities recorded in the High Atlas, Anti-Atlas, and Coastal Meseta are synthesized to refine their stratigraphic setting and to characterize their magmatic affinities and fingerprints. Six volcanic pulses are determined as tholeiitic, transitional, and alkaline suites. The tholeiitic and transitional magmas originated from primitive mantle and E-MORB-type sources with a spinel- and garnet-bearing lherzolite composition. Some of them were modified by assimilation-fractional crystallisation processes during crust-mantle interactions. The alkaline magmas fit with an OIB-type and a garnet-bearing lherzolite source. The palaeogeographic distribution of the magmatic suites was controlled by the lithospheric thinning of the Cambrian Atlas Rift and lithospheric constraints of the Pan-African metacraton and West African craton.

From the European indoor radon map towards an atlas of natural radiation.

PubMed

Tollefsen, T; Cinelli, G; Bossew, P; Gruber, V; De Cort, M

2014-11-01

In 2006, the Joint Research Centre of the European Commission launched a project to map radon at the European level, as part of a planned European Atlas of Natural Radiation. It started with a map of indoor radon concentrations. As of May 2014, this map includes data from 24 countries, covering a fair part of Europe. Next, a European map of geogenic radon, intended to show 'what earth delivers' in terms of radon potential (RP), was started in 2008. A first trial map has been created, and a database was established to collect all available data relevant to the RP. The Atlas should eventually display the geographical distribution of physical quantities related to natural radiation. In addition to radon, it will comprise maps of quantities such as cosmic rays and terrestrial gamma radiation. In this paper, the authors present the current state of the radon maps and the Atlas. © The Author 2014. Published by Oxford University Press.

Craniocervical junction in dogs revisited--new ligaments and confirmed presence of enthesis fibrocartilage.

PubMed

Kupczynska, M; Wieladek, A; Janczyk, P

2012-06-01

The study was performed to investigate and to describe features of gross and microscopic morphology of craniocervical junction (CCJ) in dogs. Seventy mature dogs (38 females, 32 males) of different body weight, representing small, medium and large breeds of dolicho-, mesati-, and brachycephalic morphotype were dissected. Morphological details were localised using an operating microscope with integrated video channel. Occurrence and distribution of fibrocartilage in the ligaments from 10 dogs was analysed histologically. Three new pairs of ligaments were described and named: dorsal ligaments of atlas, cranial internal collateral ligaments of atlas, and caudal internal collateral ligaments of atlas. Several new findings in the course of the known ligaments were found relating to breed and body weight. For the first time enthesis fibrocartilage was identified in ligaments of CCJ in dogs. Sesamoidal fibrocartilage was identified in the transversal ligament of atlas in large dogs. The findings are discussed for clinical importance. Copyright © 2011 Elsevier Ltd. All rights reserved.

[Book review] Massachusetts breeding bird atlas

USGS Publications Warehouse

Robbins, Chandler S.

2005-01-01

A glance at the dust jacket of this handsome volume drives home the conservation message that breeding bird atlases are designed to promote—that bird populations are changing over vast areas and, unless we become aware of changes in status and take remedial action, some species will disappear from our neighborhoods and even our county or state. A case in point involves the closely related Golden-winged Warbler (Vermivora chrysoptera) and Blue- winged Warbler (Vermivora pinus). The males are shown in the atlas with their breeding distribution maps. When I was an active birder in the Boston suburbs in the 1930s, the Golden-winged Warbler was a common breeder and it was a treat to find a Blue-winged Warbler. The atlas map 40 years later (1974–1979) shows only five confirmed records statewide for the Golden-winged Warbler, compared with 73 for the Blue-winged Warbler, and the Golden-winged Warbler is now listed as endangered by the Massachusetts Division of Fisheries and Wildlife. Nationally, it is a species of management concern.

JAtlasView: a Java atlas-viewer for browsing biomedical 3D images and atlases.

PubMed

Feng, Guangjie; Burton, Nick; Hill, Bill; Davidson, Duncan; Kerwin, Janet; Scott, Mark; Lindsay, Susan; Baldock, Richard

2005-03-09

Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. We report the development of a freely available Java based viewer for 3D image data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily.

An Example-Based Multi-Atlas Approach to Automatic Labeling of White Matter Tracts

PubMed Central

Yoo, Sang Wook; Guevara, Pamela; Jeong, Yong; Yoo, Kwangsun; Shin, Joseph S.; Mangin, Jean-Francois; Seong, Joon-Kyung

2015-01-01

We present an example-based multi-atlas approach for classifying white matter (WM) tracts into anatomic bundles. Our approach exploits expert-provided example data to automatically classify the WM tracts of a subject. Multiple atlases are constructed to model the example data from multiple subjects in order to reflect the individual variability of bundle shapes and trajectories over subjects. For each example subject, an atlas is maintained to allow the example data of a subject to be added or deleted flexibly. A voting scheme is proposed to facilitate the multi-atlas exploitation of example data. For conceptual simplicity, we adopt the same metrics in both example data construction and WM tract labeling. Due to the huge number of WM tracts in a subject, it is time-consuming to label each WM tract individually. Thus, the WM tracts are grouped according to their shape similarity, and WM tracts within each group are labeled simultaneously. To further enhance the computational efficiency, we implemented our approach on the graphics processing unit (GPU). Through nested cross-validation we demonstrated that our approach yielded high classification performance. The average sensitivities for bundles in the left and right hemispheres were 89.5% and 91.0%, respectively, and their average false discovery rates were 14.9% and 14.2%, respectively. PMID:26225419

An Example-Based Multi-Atlas Approach to Automatic Labeling of White Matter Tracts.

PubMed

Yoo, Sang Wook; Guevara, Pamela; Jeong, Yong; Yoo, Kwangsun; Shin, Joseph S; Mangin, Jean-Francois; Seong, Joon-Kyung

2015-01-01

We present an example-based multi-atlas approach for classifying white matter (WM) tracts into anatomic bundles. Our approach exploits expert-provided example data to automatically classify the WM tracts of a subject. Multiple atlases are constructed to model the example data from multiple subjects in order to reflect the individual variability of bundle shapes and trajectories over subjects. For each example subject, an atlas is maintained to allow the example data of a subject to be added or deleted flexibly. A voting scheme is proposed to facilitate the multi-atlas exploitation of example data. For conceptual simplicity, we adopt the same metrics in both example data construction and WM tract labeling. Due to the huge number of WM tracts in a subject, it is time-consuming to label each WM tract individually. Thus, the WM tracts are grouped according to their shape similarity, and WM tracts within each group are labeled simultaneously. To further enhance the computational efficiency, we implemented our approach on the graphics processing unit (GPU). Through nested cross-validation we demonstrated that our approach yielded high classification performance. The average sensitivities for bundles in the left and right hemispheres were 89.5% and 91.0%, respectively, and their average false discovery rates were 14.9% and 14.2%, respectively.

A digital rat atlas of sectional anatomy

NASA Astrophysics Data System (ADS)

Yu, Li; Liu, Qian; Bai, Xueling; Liao, Yinping; Luo, Qingming; Gong, Hui

2006-09-01

This paper describes a digital rat alias of sectional anatomy made by milling. Two healthy Sprague-Dawley (SD) rat weighing 160-180 g were used for the generation of this atlas. The rats were depilated completely, then euthanized by Co II. One was via vascular perfusion, the other was directly frozen at -85 °C over 24 hour. After that, the frozen specimens were transferred into iron molds for embedding. A 3% gelatin solution colored blue was used to fill the molds and then frozen at -85 °C for one or two days. The frozen specimen-blocks were subsequently sectioned on the cryosection-milling machine in a plane oriented approximately transverse to the long axis of the body. The surface of specimen-blocks were imaged by a scanner and digitalized into 4,600 x2,580 x 24 bit array through a computer. Finally 9,475 sectional images (arterial vessel were not perfused) and 1,646 sectional images (arterial vessel were perfused) were captured, which made the volume of the digital atlas up to 369.35 Gbyte. This digital rat atlas is aimed at the whole rat and the rat arterial vessels are also presented. We have reconstructed this atlas. The information from the two-dimensional (2-D) images of serial sections and three-dimensional (3-D) surface model all shows that the digital rat atlas we constructed is high quality. This work lays the foundation for a deeper study of digital rat.

Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Berglund, Judith

2000-01-01

The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

Fast Simulation of Electromagnetic Showers in the ATLAS Calorimeter: Frozen Showers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barberio, E.; /Melbourne U.; Boudreau, J.

2011-11-29

One of the most time consuming process simulating pp interactions in the ATLAS detector at LHC is the simulation of electromagnetic showers in the calorimeter. In order to speed up the event simulation several parametrisation methods are available in ATLAS. In this paper we present a short description of a frozen shower technique, together with some recent benchmarks and comparison with full simulation. An expected high rate of proton-proton collisions in ATLAS detector at LHC requires large samples of simulated events (Monte Carlo) to study various physics processes. A detailed simulation of particle reactions ('full simulation') in the ATLAS detectormore » is based on GEANT4 and is very accurate. However, due to complexity of the detector, high particle multiplicity and GEANT4 itself, the average CPU time spend to simulate typical QCD event in pp collision is 20 or more minutes for modern computers. During detector simulation the largest time is spend in the calorimeters (up to 70%) most of which is required for electromagnetic particles in the electromagnetic (EM) part of the calorimeters. This is the motivation for fast simulation approaches which reduce the simulation time without affecting the accuracy. Several of fast simulation methods available within the ATLAS simulation framework (standard Athena based simulation program) are discussed here with the focus on the novel frozen shower library (FS) technique. The results obtained with FS are presented here as well.« less

Benchmarking the ATLAS software through the Kit Validation engine

NASA Astrophysics Data System (ADS)

De Salvo, Alessandro; Brasolin, Franco

2010-04-01

The measurement of the experiment software performance is a very important metric in order to choose the most effective resources to be used and to discover the bottlenecks of the code implementation. In this work we present the benchmark techniques used to measure the ATLAS software performance through the ATLAS offline testing engine Kit Validation and the online portal Global Kit Validation. The performance measurements, the data collection, the online analysis and display of the results will be presented. The results of the measurement on different platforms and architectures will be shown, giving a full report on the CPU power and memory consumption of the Monte Carlo generation, simulation, digitization and reconstruction of the most CPU-intensive channels. The impact of the multi-core computing on the ATLAS software performance will also be presented, comparing the behavior of different architectures when increasing the number of concurrent processes. The benchmark techniques described in this paper have been used in the HEPiX group since the beginning of 2008 to help defining the performance metrics for the High Energy Physics applications, based on the real experiment software.

Agenda 21 goes electronic.

PubMed

Carter, D

1996-01-01

The Canada Center for Remote Sensing, in collaboration with the International Development Research Center, is developing an electronic atlas of Agenda 21, the Earth Summit action plan. This initiative promises to ease access for researchers and practitioners to implement the Agenda 21-action plan, which in its pilot study will focus on biological diversity. Known as the Biodiversity Volume of the Electronic Atlas of Agenda 21 (ELADA 21), this computer software technology will contain information and data on biodiversity, genetics, species, ecosystems, and ecosystem services. Specifically, it includes several country studies, documentation, as well as interactive scenarios linking biodiversity to socioeconomic issues. ELADA 21 will empower countries and agencies to report on and better manage biodiversity and related information. The atlas can be used to develop and test various scenarios and to exchange information within the South and with industrialized countries. At present, ELADA 21 has generated interest and becomes more available in the market. The challenge confronting the project team, however, is to find the atlas a permanent home, a country or agency willing to assume responsibility for maintaining, upgrading, and updating the software.

Efficient Multi-Atlas Registration using an Intermediate Template Image

PubMed Central

Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

2017-01-01

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3–4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects. PMID:28943702

Efficient multi-atlas registration using an intermediate template image

NASA Astrophysics Data System (ADS)

Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

2017-03-01

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3-4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects.

Model-based segmentation in orbital volume measurement with cone beam computed tomography and evaluation against current concepts.

PubMed

Wagner, Maximilian E H; Gellrich, Nils-Claudius; Friese, Karl-Ingo; Becker, Matthias; Wolter, Franz-Erich; Lichtenstein, Juergen T; Stoetzer, Marcus; Rana, Majeed; Essig, Harald

2016-01-01

Objective determination of the orbital volume is important in the diagnostic process and in evaluating the efficacy of medical and/or surgical treatment of orbital diseases. Tools designed to measure orbital volume with computed tomography (CT) often cannot be used with cone beam CT (CBCT) because of inferior tissue representation, although CBCT has the benefit of greater availability and lower patient radiation exposure. Therefore, a model-based segmentation technique is presented as a new method for measuring orbital volume and compared to alternative techniques. Both eyes from thirty subjects with no known orbital pathology who had undergone CBCT as a part of routine care were evaluated (n = 60 eyes). Orbital volume was measured with manual, atlas-based, and model-based segmentation methods. Volume measurements, volume determination time, and usability were compared between the three methods. Differences in means were tested for statistical significance using two-tailed Student's t tests. Neither atlas-based (26.63 ± 3.15 mm(3)) nor model-based (26.87 ± 2.99 mm(3)) measurements were significantly different from manual volume measurements (26.65 ± 4.0 mm(3)). However, the time required to determine orbital volume was significantly longer for manual measurements (10.24 ± 1.21 min) than for atlas-based (6.96 ± 2.62 min, p < 0.001) or model-based (5.73 ± 1.12 min, p < 0.001) measurements. All three orbital volume measurement methods examined can accurately measure orbital volume, although atlas-based and model-based methods seem to be more user-friendly and less time-consuming. The new model-based technique achieves fully automated segmentation results, whereas all atlas-based segmentations at least required manipulations to the anterior closing. Additionally, model-based segmentation can provide reliable orbital volume measurements when CT image quality is poor.

Design, Results, Evolution and Status of the ATLAS Simulation at Point1 Project

NASA Astrophysics Data System (ADS)

Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Fazio, D.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Sedov, A.; Twomey, M. S.; Wang, F.; Zaytsev, A.

2015-12-01

During the LHC Long Shutdown 1 (LSI) period, that started in 2013, the Simulation at Point1 (Sim@P1) project takes advantage, in an opportunistic way, of the TDAQ (Trigger and Data Acquisition) HLT (High-Level Trigger) farm of the ATLAS experiment. This farm provides more than 1300 compute nodes, which are particularly suited for running event generation and Monte Carlo production jobs that are mostly CPU and not I/O bound. It is capable of running up to 2700 Virtual Machines (VMs) each with 8 CPU cores, for a total of up to 22000 parallel jobs. This contribution gives a review of the design, the results, and the evolution of the Sim@P1 project, operating a large scale OpenStack based virtualized platform deployed on top of the ATLAS TDAQ HLT farm computing resources. During LS1, Sim@P1 was one of the most productive ATLAS sites: it delivered more than 33 million CPU-hours and it generated more than 1.1 billion Monte Carlo events. The design aspects are presented: the virtualization platform exploited by Sim@P1 avoids interferences with TDAQ operations and it guarantees the security and the usability of the ATLAS private network. The cloud mechanism allows the separation of the needed support on both infrastructural (hardware, virtualization layer) and logical (Grid site support) levels. This paper focuses on the operational aspects of such a large system during the upcoming LHC Run 2 period: simple, reliable, and efficient tools are needed to quickly switch from Sim@P1 to TDAQ mode and back, to exploit the resources when they are not used for the data acquisition, even for short periods. The evolution of the central OpenStack infrastructure is described, as it was upgraded from Folsom to the Icehouse release, including the scalability issues addressed.

Robust multi-atlas label propagation by deep sparse representation

PubMed Central

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2016-01-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer (label-specific dictionaries) consists of groups of representative atlas patches and the subsequent layers (residual dictionaries) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods. PMID:27942077

Robust multi-atlas label propagation by deep sparse representation.

PubMed

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2017-03-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer ( label-specific dictionaries ) consists of groups of representative atlas patches and the subsequent layers ( residual dictionaries ) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods.

Evolution of the ATLAS PanDA Production and Distributed Analysis System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maeno, T.; De, K.; Wenaus, T.

2012-12-13

Evolution of the ATLAS PanDA Production and Distributed Analysis System T Maeno1,5, K De2, T Wenaus1, P Nilsson2, R Walker3, A Stradling2, V Fine1, M Potekhin1, S Panitkin1 and G Compostella4 Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 396, Part 3 Article PDF References Citations Metrics 101 Total downloads Cited by 8 articles Turn on MathJax Share this article Article information Abstract The PanDA (Production and Distributed Analysis) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at LHC data processing scale. PanDAmore » has performed well with high reliability and robustness during the two years of LHC data-taking, while being actively evolved to meet the rapidly changing requirements for analysis use cases. We will present an overview of system evolution including automatic rebrokerage and reattempt for analysis jobs, adaptation for the CernVM File System, support for the multi-cloud model through which Tier-2 sites act as members of multiple clouds, pledged resource management and preferential brokerage, and monitoring improvements. We will also describe results from the analysis of two years of PanDA usage statistics, current issues, and plans for the future.« less

Design and implementation of the web Linguistic and Ethnographic Atlas of Colombia

NASA Astrophysics Data System (ADS)

Rocha S., Luz Angela; Bonilla, Johnatan; Bernal, Julio; Duarte, Catherine; Rodriguez, Alejandro

2018-05-01

The Atlas Lingüístico y Etnográfico de Colombia (Linguistic and Ethnographic Atlas of Colombia), known by "ALEC" is a compilation of popular speaking Spanish of the populations of Colombia; such research was carried out for more than fifty years. The result of this work is a collection of thematic maps organized in six volumes and its supplements in analog format. In that sense was created the project entitles "Interactive ALEC" which main objective is to develop a digital and interactive web version of the ethnographic and Linguistic Atlas of Colombia (1983) and its supplements. In this way the Corpus linguistics research group belonging to the Institute Caro y Cuervo and the research group NIDE of the Universidad Distrital "Francisco José de Caldas" have been working together in the design and development of the Atlas Web, that allows the visualization and consulting of the spatial information contained in the volume III of the analog ALEC Atlas, applying concepts of Geographical Information Systems and web cartography. Therefore, the objective of this paper is to show the process of design and development of the web prototype of the ALEC as a collection of static and dynamic maps, which show spatial information, combined with multimedia content, taking into account that in addition to all maps, the total compendium includes images, illustrations, photographs, audio and text comments. Likewise, the interactive ALEC is a good example of how to use geo-technology tools nowadays, because they are essential for the dissemination of geo linguistic information through internet, achieving more access and distribution of the Atlas web.

A generative probabilistic model and discriminative extensions for brain lesion segmentation – with application to tumor and stroke

PubMed Central

Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-André; Székely, Gabor; Ayache, Nicholas; Golland, Polina

2016-01-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM) to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as “tumor core” or “fluid-filled structure”, but without a one-to-one correspondence to the hypo-or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the generative-discriminative model to be one of the top ranking methods in the BRATS evaluation. PMID:26599702

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation--With Application to Tumor and Stroke.

PubMed

Menze, Bjoern H; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-Andre; Szekely, Gabor; Ayache, Nicholas; Golland, Polina

2016-04-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM), to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as "tumor core" or "fluid-filled structure", but without a one-to-one correspondence to the hypo- or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the extended discriminative -discriminative model to be one of the top ranking methods in the BRATS evaluation.

Producing an Infrared Multiwavelength Galactic Plane Atlas Using Montage, Pegasus, and Amazon Web Services

NASA Astrophysics Data System (ADS)

Rynge, M.; Juve, G.; Kinney, J.; Good, J.; Berriman, B.; Merrihew, A.; Deelman, E.

2014-05-01

In this paper, we describe how to leverage cloud resources to generate large-scale mosaics of the galactic plane in multiple wavelengths. Our goal is to generate a 16-wavelength infrared Atlas of the Galactic Plane at a common spatial sampling of 1 arcsec, processed so that they appear to have been measured with a single instrument. This will be achieved by using the Montage image mosaic engine process observations from the 2MASS, GLIMPSE, MIPSGAL, MSX and WISE datasets, over a wavelength range of 1 μm to 24 μm, and by using the Pegasus Workflow Management System for managing the workload. When complete, the Atlas will be made available to the community as a data product. We are generating images that cover ±180° in Galactic longitude and ±20° in Galactic latitude, to the extent permitted by the spatial coverage of each dataset. Each image will be 5°x5° in size (including an overlap of 1° with neighboring tiles), resulting in an atlas of 1,001 images. The final size will be about 50 TBs. This paper will focus on the computational challenges, solutions, and lessons learned in producing the Atlas. To manage the computation we are using the Pegasus Workflow Management System, a mature, highly fault-tolerant system now in release 4.2.2 that has found wide applicability across many science disciplines. A scientific workflow describes the dependencies between the tasks and in most cases the workflow is described as a directed acyclic graph, where the nodes are tasks and the edges denote the task dependencies. A defining property for a scientific workflow is that it manages data flow between tasks. Applied to the galactic plane project, each 5 by 5 mosaic is a Pegasus workflow. Pegasus is used to fetch the source images, execute the image mosaicking steps of Montage, and store the final outputs in a storage system. As these workflows are very I/O intensive, care has to be taken when choosing what infrastructure to execute the workflow on. In our setup, we choose to use dynamically provisioned compute clusters running on the Amazon Elastic Compute Cloud (EC2). All our instances are using the same base image, which is configured to come up as a master node by default. The master node is a central instance from where the workflow can be managed. Additional worker instances are provisioned and configured to accept work assignments from the master node. The system allows for adding/removing workers in an ad hoc fashion, and could be run in large configurations. To-date we have performed 245,000 CPU hours of computing and generated 7,029 images and totaling 30 TB. With the current set up our runtime would be 340,000 CPU hours for the whole project. Using spot m2.4xlarge instances, the cost would be approximately $5,950. Using faster AWS instances, such as cc2.8xlarge could potentially decrease the total CPU hours and further reduce the compute costs. The paper will explore these tradeoffs.

A comprehensive guide for designing more efficient irrigation systems with respect to application control

NASA Astrophysics Data System (ADS)

Khaddam, Issam; Schuetze, Niels

2017-04-01

The worldwide water scarcity problems are expected to aggravate due to the increasing population and the need to produce more food. Irrigated agriculture is considered the highest consumer of fresh water resources with a rate exceeds 70% of global consumption. Consequently, an improvement in the efficiency of all irrigation methods, such as furrow or drip irrigation, becomes more necessary and urgent. Therefore, a more precise knowledge about soil water distribution in the root zone and the water balance components is required. For this purpose and as a part of the SAPHIR project (Saxonian Platform for high Performance Irrigation), a 2D simulation- based study was performed with virtual field conditions. The study investigates the most important design parameters of many irrigation systems, such as irrigation intensity and duration, and shows there influence on the water distribution efficiency. Furthermore, three main soil textures are used to test the impact of the soil hydraulic properties on irrigation effectiveness. A numerous number of irrigation scenarios of each irrigation system was simulated using HYDRUS 2D. Thereafter, the results were digitally calculated, compiled and made available online in the so called "Irrigation Atlases". The irrigation atlases provide graphical results of the soil moisture and pressure head distributions in the root zone. Moreover, they contain detailed information of the water balance for all simulated scenarios. The most studies evaluate the irrigation water demands on local, regional or global scales and for that an efficient water distribution is required. In this context, the irrigation atlases can serve as a valuable tool for the implementation of planned irrigation measures.

Methodology to study the three-dimensional spatial distribution of prostate cancer and their dependence on clinical parameters

PubMed Central

Rojas, Kristians Diaz; Montero, Maria L.; Yao, Jorge; Messing, Edward; Fazili, Anees; Joseph, Jean; Ou, Yangming; Rubens, Deborah J.; Parker, Kevin J.; Davatzikos, Christos; Castaneda, Benjamin

2015-01-01

Abstract. A methodology to study the relationship between clinical variables [e.g., prostate specific antigen (PSA) or Gleason score] and cancer spatial distribution is described. Three-dimensional (3-D) models of 216 glands are reconstructed from digital images of whole mount histopathological slices. The models are deformed into one prostate model selected as an atlas using a combination of rigid, affine, and B-spline deformable registration techniques. Spatial cancer distribution is assessed by counting the number of tumor occurrences among all glands in a given position of the 3-D registered atlas. Finally, a difference between proportions is used to compare different spatial distributions. As a proof of concept, we compare spatial distributions from patients with PSA greater and less than 5  ng/ml and from patients older and younger than 60 years. Results suggest that prostate cancer has a significant difference in the right zone of the prostate between populations with PSA greater and less than 5  ng/ml. Age does not have any impact in the spatial distribution of the disease. The proposed methodology can help to comprehend prostate cancer by understanding its spatial distribution and how it changes according to clinical parameters. Finally, this methodology can be easily adapted to other organs and pathologies. PMID:26236756

Atlas of neuroanatomy with radiologic correlation and pathologic illustration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dublin, A.B.; Dublin, W.B.

1982-01-01

This atlas correlates gross neuroanatomic specimens with radiographs and computed tomographic scans. Pathologic specimens and radiographs are displayed in a similar manner. The first chapter, on embryology, shows the development of the telencephalon, diencephalon, mesencephalon, and metencephalon through a series of overlays. The anatomical section shows the surface of the brain, the ventricles and their adjacent structures, and the vascular system. CT anatomy is demonstrated by correlating CT scans with pathologic brain specimens cut in the axial plane. Pathologic changes associated with congenital malformations, injections, injuries, tumors, and other causes are demonstrated in the last six chapters.

The Extrapolar SWIFT model (version 1.0): fast stratospheric ozone chemistry for global climate models

NASA Astrophysics Data System (ADS)

Kreyling, Daniel; Wohltmann, Ingo; Lehmann, Ralph; Rex, Markus

2018-03-01

The Extrapolar SWIFT model is a fast ozone chemistry scheme for interactive calculation of the extrapolar stratospheric ozone layer in coupled general circulation models (GCMs). In contrast to the widely used prescribed ozone, the SWIFT ozone layer interacts with the model dynamics and can respond to atmospheric variability or climatological trends.The Extrapolar SWIFT model employs a repro-modelling approach, in which algebraic functions are used to approximate the numerical output of a full stratospheric chemistry and transport model (ATLAS). The full model solves a coupled chemical differential equation system with 55 initial and boundary conditions (mixing ratio of various chemical species and atmospheric parameters). Hence the rate of change of ozone over 24 h is a function of 55 variables. Using covariances between these variables, we can find linear combinations in order to reduce the parameter space to the following nine basic variables: latitude, pressure altitude, temperature, overhead ozone column and the mixing ratio of ozone and of the ozone-depleting families (Cly, Bry, NOy and HOy). We will show that these nine variables are sufficient to characterize the rate of change of ozone. An automated procedure fits a polynomial function of fourth degree to the rate of change of ozone obtained from several simulations with the ATLAS model. One polynomial function is determined per month, which yields the rate of change of ozone over 24 h. A key aspect for the robustness of the Extrapolar SWIFT model is to include a wide range of stratospheric variability in the numerical output of the ATLAS model, also covering atmospheric states that will occur in a future climate (e.g. temperature and meridional circulation changes or reduction of stratospheric chlorine loading).For validation purposes, the Extrapolar SWIFT model has been integrated into the ATLAS model, replacing the full stratospheric chemistry scheme. Simulations with SWIFT in ATLAS have proven that the systematic error is small and does not accumulate during the course of a simulation. In the context of a 10-year simulation, the ozone layer simulated by SWIFT shows a stable annual cycle, with inter-annual variations comparable to the ATLAS model. The application of Extrapolar SWIFT requires the evaluation of polynomial functions with 30-100 terms. Computers can currently calculate such polynomial functions at thousands of model grid points in seconds. SWIFT provides the desired numerical efficiency and computes the ozone layer 104 times faster than the chemistry scheme in the ATLAS CTM.

Atlas of solar hidden photon emission

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redondo, Javier, E-mail: redondo@mpp.mpg.de

2015-07-01

Hidden photons, gauge bosons of a U(1) symmetry of a hidden sector, can constitute the dark matter of the universe and a smoking gun for large volume compactifications of string theory. In the sub-eV mass range, a possible discovery experiment consists on searching the copious flux of these particles emitted from the Sun in a helioscope setup à la Sikivie. In this paper, we compute in great detail the flux of HPs from the Sun, a necessary ingredient for interpreting such experiments. We provide a detailed exposition of transverse photon-HP oscillations in inhomogenous media, with special focus on resonance oscillations,more » which play a leading role in many cases. The region of the Sun emitting HPs resonantly is a thin spherical shell for which we justify an averaged-emission formula and which implies a distinctive morphology of the angular distribution of HPs on Earth in many cases. Low mass HPs with energies in the visible and IR have resonances very close to the photosphere where the solar plasma is not fully ionised and requires building a detailed model of solar refraction and absorption. We present results for a broad range of HP masses (from 0–1 keV) and energies (from the IR to the X-ray range), the most complete atlas of solar HP emission to date.« less

Atlas of solar hidden photon emission

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redondo, Javier; Max-Planck-Institut für Physik, Werner-Heisenberg-Institut,Föhringer Ring 6, 80805 München

2015-07-20

Hidden photons, gauge bosons of a U(1) symmetry of a hidden sector, can constitute the dark matter of the universe and a smoking gun for large volume compactifications of string theory. In the sub-eV mass range, a possible discovery experiment consists on searching the copious flux of these particles emitted from the Sun in a helioscope setup à la Sikivie. In this paper, we compute in great detail the flux of HPs from the Sun, a necessary ingredient for interpreting such experiments. We provide a detailed exposition of transverse photon-HP oscillations in inhomogenous media, with special focus on resonance oscillations,more » which play a leading role in many cases. The region of the Sun emitting HPs resonantly is a thin spherical shell for which we justify an averaged-emission formula and which implies a distinctive morphology of the angular distribution of HPs on Earth in many cases. Low mass HPs with energies in the visible and IR have resonances very close to the photosphere where the solar plasma is not fully ionised and requires building a detailed model of solar refraction and absorption. We present results for a broad range of HP masses (from 0–1 keV) and energies (from the IR to the X-ray range), the most complete atlas of solar HP emission to date.« less

The new world atlas of artificial night sky brightness

PubMed Central

Falchi, Fabio; Cinzano, Pierantonio; Duriscoe, Dan; Kyba, Christopher C. M.; Elvidge, Christopher D.; Baugh, Kimberly; Portnov, Boris A.; Rybnikova, Nataliya A.; Furgoni, Riccardo

2016-01-01

Artificial lights raise night sky luminance, creating the most visible effect of light pollution—artificial skyglow. Despite the increasing interest among scientists in fields such as ecology, astronomy, health care, and land-use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, we present the world atlas of artificial sky luminance, computed with our light pollution propagation software using new high-resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the world and more than 99% of the U.S. and European populations live under light-polluted skies. The Milky Way is hidden from more than one-third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of the world’s land surfaces between 75°N and 60°S, 88% of Europe, and almost half of the United States experience light-polluted nights. PMID:27386582

Splash: a software tool for stereotactic planning of recording chamber placement and electrode trajectories.

PubMed

Sperka, Daniel J; Ditterich, Jochen

2011-01-01

While computer-aided planning of human neurosurgeries is becoming more and more common, animal researchers still largely rely on paper atlases for planning their approach before implanting recording chambers to perform invasive recordings of neural activity, which makes this planning process tedious and error-prone. Here we present SPLASh (Stereotactic PLAnning Software), an interactive software tool for the stereotactic planning of recording chamber placement and electrode trajectories. SPLASh has been developed for monkey cortical recordings and relies on a combination of structural MRIs and electronic brain atlases. Since SPLASh is based on the neuroanatomy software Caret, it should also be possible to use it for other parts of the brain or other species for which Caret atlases are available. The tool allows the user to interactively evaluate different possible placements of recording chambers and to simulate electrode trajectories.

Splash: A Software Tool for Stereotactic Planning of Recording Chamber Placement and Electrode Trajectories

PubMed Central

Sperka, Daniel J.; Ditterich, Jochen

2011-01-01

While computer-aided planning of human neurosurgeries is becoming more and more common, animal researchers still largely rely on paper atlases for planning their approach before implanting recording chambers to perform invasive recordings of neural activity, which makes this planning process tedious and error-prone. Here we present SPLASh (Stereotactic PLAnning Software), an interactive software tool for the stereotactic planning of recording chamber placement and electrode trajectories. SPLASh has been developed for monkey cortical recordings and relies on a combination of structural MRIs and electronic brain atlases. Since SPLASh is based on the neuroanatomy software Caret, it should also be possible to use it for other parts of the brain or other species for which Caret atlases are available. The tool allows the user to interactively evaluate different possible placements of recording chambers and to simulate electrode trajectories. PMID:21472085

The new world atlas of artificial night sky brightness.

PubMed

Falchi, Fabio; Cinzano, Pierantonio; Duriscoe, Dan; Kyba, Christopher C M; Elvidge, Christopher D; Baugh, Kimberly; Portnov, Boris A; Rybnikova, Nataliya A; Furgoni, Riccardo

2016-06-01

Artificial lights raise night sky luminance, creating the most visible effect of light pollution-artificial skyglow. Despite the increasing interest among scientists in fields such as ecology, astronomy, health care, and land-use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, we present the world atlas of artificial sky luminance, computed with our light pollution propagation software using new high-resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the world and more than 99% of the U.S. and European populations live under light-polluted skies. The Milky Way is hidden from more than one-third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of the world's land surfaces between 75°N and 60°S, 88% of Europe, and almost half of the United States experience light-polluted nights.

Faceted Visualization of Three Dimensional Neuroanatomy By Combining Ontology with Faceted Search

PubMed Central

Veeraraghavan, Harini; Miller, James V.

2013-01-01

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset. PMID:24006207

Faceted visualization of three dimensional neuroanatomy by combining ontology with faceted search.

PubMed

Veeraraghavan, Harini; Miller, James V

2014-04-01

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset.

Ossification of transverse ligament of atlas causing cervical myelopathy: a case report and review of the literature.

PubMed

Sasaji, Tatsuro; Kawahara, Chikashi; Matsumoto, Fujio

2011-01-01

A case of ossification of transverse ligament of atlas (TLA) is reported. A 76-year-old female suffered from a transverse type myelopathy was successfully treated by posterior decompression. Dynamic lateral plain radiographs showed irreducible atlantoaxial subluxation (AAS). A computed tomogram revealed ossified mass compatible to ossification of TLA. Coalition of the atlantooccipital joints and osteoarthritis of the atlantoaxial joints with degenerated dens was also revealed. Magnetic resonance imaging showed compressed spinal cord at C1 level by the ossification of TLA and AAS. We suggest a mechanism of ossification of TLA as follows: hypertrophied dens and stress to the atlantoaxial joints caused by coalition of atlantooccipital joints could make forward shift of atlas leading to irreducible AAS, and continuous tension given to TLA from irreducible AAS would result in hypertrophied and ossification of TLA.

An atlas of synthetic line profiles of Planetary Nebulae

NASA Astrophysics Data System (ADS)

Morisset, C.; Stasinska, G.

2008-04-01

We have constructed a grid of photoionization models of spherical, elliptical and bipolar planetary nebulae. Assuming different velocity fields, we have computed line profiles corresponding to different orientations, slit sizes and positions. The atlas is meant both for didactic purposes and for the interpretation of data on real nebulae. As an application, we have shown that line profiles are often degenerate, and that recovering the geometry and velocity field from observations requires lines from ions with different masses and different ionization potentials. We have also shown that the empirical way to measure mass-weighted expansion velocities from observed line widths is reasonably accurate if considering the HWHM. For distant nebulae, entirely covered by the slit, the unknown geometry and orientation do not alter the measured velocities statistically. The atlas is freely accessible from internet. The Cloudy_3D suite and the associated VISNEB tool are available on request.

A comparison of NNLO QCD predictions with 7 TeV ATLAS and CMS data for V+jet processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boughezal, Radja; Liu, Xiaohui; Petriello, Frank

2016-06-17

Here, we perform a detailed comparison of next-to-next-to-leading order (NNLO) QCD predictions for the W+jet and Z+jet processes with 7 TeV experimental data from ATLAS and CMS. We observe excellent agreement between theory and data for most studied observables, which span several orders of magnitude in both cross section and energy. For some observables, such as the HT distribution, the NNLO QCD corrections are essential for resolving existing discrepancies between theory and data.

Multi-atlas attenuation correction supports full quantification of static and dynamic brain PET data in PET-MR

NASA Astrophysics Data System (ADS)

Mérida, Inés; Reilhac, Anthonin; Redouté, Jérôme; Heckemann, Rolf A.; Costes, Nicolas; Hammers, Alexander

2017-04-01

In simultaneous PET-MR, attenuation maps are not directly available. Essential for absolute radioactivity quantification, they need to be derived from MR or PET data to correct for gamma photon attenuation by the imaged object. We evaluate a multi-atlas attenuation correction method for brain imaging (MaxProb) on static [18F]FDG PET and, for the first time, on dynamic PET, using the serotoninergic tracer [18F]MPPF. A database of 40 MR/CT image pairs (atlases) was used. The MaxProb method synthesises subject-specific pseudo-CTs by registering each atlas to the target subject space. Atlas CT intensities are then fused via label propagation and majority voting. Here, we compared these pseudo-CTs with the real CTs in a leave-one-out design, contrasting the MaxProb approach with a simplified single-atlas method (SingleAtlas). We evaluated the impact of pseudo-CT accuracy on reconstructed PET images, compared to PET data reconstructed with real CT, at the regional and voxel levels for the following: radioactivity images; time-activity curves; and kinetic parameters (non-displaceable binding potential, BPND). On static [18F]FDG, the mean bias for MaxProb ranged between 0 and 1% for 73 out of 84 regions assessed, and exceptionally peaked at 2.5% for only one region. Statistical parametric map analysis of MaxProb-corrected PET data showed significant differences in less than 0.02% of the brain volume, whereas SingleAtlas-corrected data showed significant differences in 20% of the brain volume. On dynamic [18F]MPPF, most regional errors on BPND ranged from -1 to  +3% (maximum bias 5%) for the MaxProb method. With SingleAtlas, errors were larger and had higher variability in most regions. PET quantification bias increased over the duration of the dynamic scan for SingleAtlas, but not for MaxProb. We show that this effect is due to the interaction of the spatial tracer-distribution heterogeneity variation over time with the degree of accuracy of the attenuation maps. This work demonstrates that inaccuracies in attenuation maps can induce bias in dynamic brain PET studies. Multi-atlas attenuation correction with MaxProb enables quantification on hybrid PET-MR scanners, eschewing the need for CT.

Multi-atlas attenuation correction supports full quantification of static and dynamic brain PET data in PET-MR.

PubMed

Mérida, Inés; Reilhac, Anthonin; Redouté, Jérôme; Heckemann, Rolf A; Costes, Nicolas; Hammers, Alexander

2017-04-07

In simultaneous PET-MR, attenuation maps are not directly available. Essential for absolute radioactivity quantification, they need to be derived from MR or PET data to correct for gamma photon attenuation by the imaged object. We evaluate a multi-atlas attenuation correction method for brain imaging (MaxProb) on static [ 18 F]FDG PET and, for the first time, on dynamic PET, using the serotoninergic tracer [ 18 F]MPPF. A database of 40 MR/CT image pairs (atlases) was used. The MaxProb method synthesises subject-specific pseudo-CTs by registering each atlas to the target subject space. Atlas CT intensities are then fused via label propagation and majority voting. Here, we compared these pseudo-CTs with the real CTs in a leave-one-out design, contrasting the MaxProb approach with a simplified single-atlas method (SingleAtlas). We evaluated the impact of pseudo-CT accuracy on reconstructed PET images, compared to PET data reconstructed with real CT, at the regional and voxel levels for the following: radioactivity images; time-activity curves; and kinetic parameters (non-displaceable binding potential, BP ND ). On static [ 18 F]FDG, the mean bias for MaxProb ranged between 0 and 1% for 73 out of 84 regions assessed, and exceptionally peaked at 2.5% for only one region. Statistical parametric map analysis of MaxProb-corrected PET data showed significant differences in less than 0.02% of the brain volume, whereas SingleAtlas-corrected data showed significant differences in 20% of the brain volume. On dynamic [ 18 F]MPPF, most regional errors on BP ND ranged from -1 to  +3% (maximum bias 5%) for the MaxProb method. With SingleAtlas, errors were larger and had higher variability in most regions. PET quantification bias increased over the duration of the dynamic scan for SingleAtlas, but not for MaxProb. We show that this effect is due to the interaction of the spatial tracer-distribution heterogeneity variation over time with the degree of accuracy of the attenuation maps. This work demonstrates that inaccuracies in attenuation maps can induce bias in dynamic brain PET studies. Multi-atlas attenuation correction with MaxProb enables quantification on hybrid PET-MR scanners, eschewing the need for CT.

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Measurement of lepton differential distributions and the top quark mass in t\\bar{t} production in pp collisions at √{s}=8 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Betti, A.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozson, A. J.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casha, A. F.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Dodsworth, D.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubinin, F.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dulsen, C.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duperrin, A.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Ennis, J. S.; Epland, M. B.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. 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V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Pokharel, I.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Portillo Quintero, D. M.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potti, H.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rangel-Smith, C.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Rüttinger, E. M.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. 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M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Sottocornola, S.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, T. J.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeda, K.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Thais, S. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tian, Y.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. 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Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2017-11-01

This paper presents single lepton and dilepton kinematic distributions measured in dileptonic t\\bar{t} events produced in 20.2fb^{-1} of √{s}=8 TeV pp collisions recorded by the ATLAS experiment at the LHC. Both absolute and normalised differential cross-sections are measured, using events with an opposite-charge eμ pair and one or two b-tagged jets. The cross-sections are measured in a fiducial region corresponding to the detector acceptance for leptons, and are compared to the predictions from a variety of Monte Carlo event generators, as well as fixed-order QCD calculations, exploring the sensitivity of the cross-sections to the gluon parton distribution function. Some of the distributions are also sensitive to the top quark pole mass; a combined fit of NLO fixed-order predictions to all the measured distributions yields a top quark mass value of {m_t^{pole}}=173.2± 0.9± 0.8± 1.2 GeV, where the three uncertainties arise from data statistics, experimental systematics, and theoretical sources.

Measurement of lepton differential distributions and the top quark mass in $$t\\bar{t}$$ production in pp collisions at $$\\sqrt{s}=8$$  TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-11-25

We present single lepton and dilepton kinematic distributions measured in dileptonic tmore » $$\\bar{t}$$ events produced in 20.2fb - 1 of √s=8 TeV pp collisions recorded by the ATLAS experiment at the LHC. Both absolute and normalised differential cross-sections are measured, using events with an opposite-charge eμ pair and one or two b-tagged jets. Furthermore, the cross-sections are measured in a fiducial region corresponding to the detector acceptance for leptons, and are compared to the predictions from a variety of Monte Carlo event generators, as well as fixed-order QCD calculations, exploring the sensitivity of the cross-sections to the gluon parton distribution function. Some of the distributions are also sensitive to the top quark pole mass; a combined fit of NLO fixed-order predictions to all the measured distributions yields a top quark mass value of m$$pole\\atop{t}$$=173.2±0.9±0.8±1.2 GeV, where the three uncertainties arise from data statistics, experimental systematics, and theoretical sources.« less

WatAA: Atlas of Protein Hydration. Exploring synergies between data mining and ab initio calculations.

PubMed

Černý, Jiří; Schneider, Bohdan; Biedermannová, Lada

2017-07-14

Water molecules represent an integral part of proteins and a key determinant of protein structure, dynamics and function. WatAA is a newly developed, web-based atlas of amino-acid hydration in proteins. The atlas provides information about the ordered first hydration shell of the most populated amino-acid conformers in proteins. The data presented in the atlas are drawn from two sources: experimental data and ab initio quantum-mechanics calculations. The experimental part is based on a data-mining study of a large set of high-resolution protein crystal structures. The crystal-derived data include 3D maps of water distribution around amino-acids and probability of occurrence of each of the identified hydration sites. The quantum mechanics calculations validate and extend this primary description by optimizing the water position for each hydration site, by providing hydrogen atom positions and by quantifying the interaction energy that stabilizes the water molecule at the particular hydration site position. The calculations show that the majority of experimentally derived hydration sites are positioned near local energy minima for water, and the calculated interaction energies help to assess the preference of water for the individual hydration sites. We propose that the atlas can be used to validate water placement in electron density maps in crystallographic refinement, to locate water molecules mediating protein-ligand interactions in drug design, and to prepare and evaluate molecular dynamics simulations. WatAA: Atlas of Protein Hydration is freely available without login at .

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

WLCG Transfers Dashboard: a Unified Monitoring Tool for Heterogeneous Data Transfers

NASA Astrophysics Data System (ADS)

Andreeva, J.; Beche, A.; Belov, S.; Kadochnikov, I.; Saiz, P.; Tuckett, D.

2014-06-01

The Worldwide LHC Computing Grid provides resources for the four main virtual organizations. Along with data processing, data distribution is the key computing activity on the WLCG infrastructure. The scale of this activity is very large, the ATLAS virtual organization (VO) alone generates and distributes more than 40 PB of data in 100 million files per year. Another challenge is the heterogeneity of data transfer technologies. Currently there are two main alternatives for data transfers on the WLCG: File Transfer Service and XRootD protocol. Each LHC VO has its own monitoring system which is limited to the scope of that particular VO. There is a need for a global system which would provide a complete cross-VO and cross-technology picture of all WLCG data transfers. We present a unified monitoring tool - WLCG Transfers Dashboard - where all the VOs and technologies coexist and are monitored together. The scale of the activity and the heterogeneity of the system raise a number of technical challenges. Each technology comes with its own monitoring specificities and some of the VOs use several of these technologies. This paper describes the implementation of the system with particular focus on the design principles applied to ensure the necessary scalability and performance, and to easily integrate any new technology providing additional functionality which might be specific to that technology.

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

NASA Technical Reports Server (NTRS)

Valenti, Elizabeth; Fitzpatrick, Patrick

2005-01-01

Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

PubMed

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

Final Report: High Energy Physics at the Energy Frontier at Louisiana Tech

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sawyer, Lee; Wobisch, Markus; Greenwood, Zeno D.

The Louisiana Tech University High Energy Physics group has developed a research program aimed at experimentally testing the Standard Model of particle physics and searching for new phenomena through a focused set of analyses in collaboration with the ATLAS experiment at the Large Hadron Collider (LHC) at the CERN laboratory in Geneva. This research program includes involvement in the current operation and maintenance of the ATLAS experiment and full involvement in Phase 1 and Phase 2 upgrades in preparation for future high luminosity (HL-LHC) operation of the LHC. Our focus is solely on the ATLAS experiment at the LHC, withmore » some related detector development and software efforts. We have established important service roles on ATLAS in five major areas: Triggers, especially jet triggers; Data Quality monitoring; grid computing; GPU applications for upgrades; and radiation testing for upgrades. Our physics research is focused on multijet measurements and top quark physics in final states containing tau leptons, which we propose to extend into related searches for new phenomena. Focusing on closely related topics in the jet and top analyses and coordinating these analyses in our group has led to high efficiency and increased visibility inside the ATLAS collaboration and beyond. Based on our work in the DØ experiment in Run II of the Fermilab Tevatron Collider, Louisiana Tech has developed a reputation as one of the leading institutions pursuing jet physics studies. Currently we are applying this expertise to the ATLAS experiment, with several multijet analyses in progress.« less

Representation and visualization of variability in a 3D anatomical atlas using the kidney as an example

NASA Astrophysics Data System (ADS)

Hacker, Silke; Handels, Heinz

2006-03-01

Computer-based 3D atlases allow an interactive exploration of the human body. However, in most cases such 3D atlases are derived from one single individual, and therefore do not regard the variability of anatomical structures concerning their shape and size. Since the geometric variability across humans plays an important role in many medical applications, our goal is to develop a framework of an anatomical atlas for representation and visualization of the variability of selected anatomical structures. The basis of the project presented is the VOXEL-MAN atlas of inner organs that was created from the Visible Human data set. For modeling anatomical shapes and their variability we utilize "m-reps" which allow a compact representation of anatomical objects on the basis of their skeletons. As an example we used a statistical model of the kidney that is based on 48 different variants. With the integration of a shape description into the VOXEL-MAN atlas it is now possible to query and visualize different shape variations of an organ, e.g. by specifying a person's age or gender. In addition to the representation of individual shape variants, the average shape of a population can be displayed. Besides a surface representation, a volume-based representation of the kidney's shape variants is also possible. It results from the deformation of the reference kidney of the volume-based model using the m-rep shape description. In this way a realistic visualization of the shape variants becomes possible, as well as the visualization of the organ's internal structures.

Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; McHugo, Maureen; Heckers, Stephan; Landman, Bennett A.

2017-02-01

Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p < 0.05 for all structures). This work signifies the first result in an ongoing work to develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

The Complexity Analysis Tool

DTIC Science & Technology

1988-10-01

overview of the complexity analysis tool ( CAT ), an automated tool which will analyze mission critical computer resources (MCCR) software. CAT is based...84 MAR UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE 19. ABSTRACT: (cont) CAT automates the metric for BASIC (HP-71), ATLAS (EQUATE), Ada (subset...UNIX 5.2). CAT analyzes source code and computes complexity on a module basis. CAT also generates graphic representations of the logic flow paths and

Restoration, Enhancement, and Distribution of the ATLAS-1 Imaging Spectrometric Observatory (ISO) Space Science Data Set

NASA Technical Reports Server (NTRS)

Germany, G. A.

2001-01-01

The primary goal of the funded task was to restore and distribute the ISO ATLAS-1 space science data set with enhanced software and database utilities. The first year was primarily dedicated to physically transferring the data from its original format to its initial CD archival format. The remainder of the first year was devoted to the verification of the restored data set and database. The second year was devoted to the enhancement of the data set, especially the development of IDL utilities and redesign of the database and search interface as needed. This period was also devoted to distribution of the rescued data set, principally the creation and maintenance of a web interface to the data set. The final six months was dedicated to working with NSSDC to create a permanent, off site, hive of the data set and supporting utilities. This time was also used to resolve last minute quality and design issues.

KSC-2013-3791

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit arrives at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-4389

NASA Image and Video Library

2013-12-12

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V first stage booster that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported from the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station to Launch Complex 41. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/Kim Shiflett

KSC-2013-3793

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit arrives at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-3794

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit arrives at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-4393

NASA Image and Video Library

2013-12-12

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V first stage booster that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported from the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station to Launch Complex 41. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/Kim Shiflett

KSC-2013-3784

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-4392

NASA Image and Video Library

2013-12-12

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V first stage booster that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported from the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station to Launch Complex 41. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/Kim Shiflett

KSC-2013-3788

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-3787

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-4390

NASA Image and Video Library

2013-12-12

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V first stage booster that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being prepared for transport from the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station to Launch Complex 41. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/Kim Shiflett

KSC-2013-3785

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

KSC-2013-4391

NASA Image and Video Library

2013-12-12

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V first stage booster that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported from the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station to Launch Complex 41. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/Kim Shiflett

Atlas-Based Ventricular Shape Analysis for Understanding Congenital Heart Disease.

PubMed

Farrar, Genevieve; Suinesiaputra, Avan; Gilbert, Kathleen; Perry, James C; Hegde, Sanjeet; Marsden, Alison; Young, Alistair A; Omens, Jeffrey H; McCulloch, Andrew D

2016-12-01

Congenital heart disease is associated with abnormal ventricular shape that can affect wall mechanics and may be predictive of long-term adverse outcomes. Atlas-based parametric shape analysis was used to analyze ventricular geometries of eight adolescent or adult single-ventricle CHD patients with tricuspid atresia and Fontans. These patients were compared with an "atlas" of non-congenital asymptomatic volunteers, resulting in a set of z-scores which quantify deviations from the control population distribution on a patient-by-patient basis. We examined the potential of these scores to: (1) quantify abnormalities of ventricular geometry in single ventricle physiologies relative to the normal population; (2) comprehensively quantify wall motion in CHD patients; and (3) identify possible relationships between ventricular shape and wall motion that may reflect underlying functional defects or remodeling in CHD patients. CHD ventricular geometries at end-diastole and end-systole were individually compared with statistical shape properties of an asymptomatic population from the Cardiac Atlas Project. Shape analysis-derived model properties, and myocardial wall motions between end-diastole and end-systole, were compared with physician observations of clinical functional parameters. Relationships between altered shape and altered function were evaluated via correlations between atlas-based shape and wall motion scores. Atlas-based shape analysis identified a diverse set of specific quantifiable abnormalities in ventricular geometry or myocardial wall motion in all subjects. Moreover, this initial cohort displayed significant relationships between specific shape abnormalities such as increased ventricular sphericity and functional defects in myocardial deformation, such as decreased long-axis wall motion. These findings suggest that atlas-based ventricular shape analysis may be a useful new tool in the management of patients with CHD who are at risk of impaired ventricular wall mechanics and chamber remodeling.

Experience with ATLAS MySQL PanDA database service

NASA Astrophysics Data System (ADS)

Smirnov, Y.; Wlodek, T.; De, K.; Hover, J.; Ozturk, N.; Smith, J.; Wenaus, T.; Yu, D.

2010-04-01

The PanDA distributed production and analysis system has been in production use for ATLAS data processing and analysis since late 2005 in the US, and globally throughout ATLAS since early 2008. Its core architecture is based on a set of stateless web services served by Apache and backed by a suite of MySQL databases that are the repository for all PanDA information: active and archival job queues, dataset and file catalogs, site configuration information, monitoring information, system control parameters, and so on. This database system is one of the most critical components of PanDA, and has successfully delivered the functional and scaling performance required by PanDA, currently operating at a scale of half a million jobs per week, with much growth still to come. In this paper we describe the design and implementation of the PanDA database system, its architecture of MySQL servers deployed at BNL and CERN, backup strategy and monitoring tools. The system has been developed, thoroughly tested, and brought to production to provide highly reliable, scalable, flexible and available database services for ATLAS Monte Carlo production, reconstruction and physics analysis.

Computational neuroanatomy: mapping cell-type densities in the mouse brain, simulations from the Allen Brain Atlas

NASA Astrophysics Data System (ADS)

Grange, Pascal

2015-09-01

The Allen Brain Atlas of the adult mouse (ABA) consists of digitized expression profiles of thousands of genes in the mouse brain, co-registered to a common three-dimensional template (the Allen Reference Atlas).This brain-wide, genome-wide data set has triggered a renaissance in neuroanatomy. Its voxelized version (with cubic voxels of side 200 microns) is available for desktop computation in MATLAB. On the other hand, brain cells exhibit a great phenotypic diversity (in terms of size, shape and electrophysiological activity), which has inspired the names of some well-studied cell types, such as granule cells and medium spiny neurons. However, no exhaustive taxonomy of brain cell is available. A genetic classification of brain cells is being undertaken, and some cell types have been chraracterized by their transcriptome profiles. However, given a cell type characterized by its transcriptome, it is not clear where else in the brain similar cells can be found. The ABA can been used to solve this region-specificity problem in a data-driven way: rewriting the brain-wide expression profiles of all genes in the atlas as a sum of cell-type-specific transcriptome profiles is equivalent to solving a quadratic optimization problem at each voxel in the brain. However, the estimated brain-wide densities of 64 cell types published recently were based on one series of co-registered coronal in situ hybridization (ISH) images per gene, whereas the online ABA contains several image series per gene, including sagittal ones. In the presented work, we simulate the variability of cell-type densities in a Monte Carlo way by repeatedly drawing a random image series for each gene and solving the optimization problem. This yields error bars on the region-specificity of cell types.

Inverse-consistent rigid registration of CT and MR for MR-based planning and adaptive prostate radiation therapy

NASA Astrophysics Data System (ADS)

Rivest-Hénault, David; Dowson, Nicholas; Greer, Peter; Dowling, Jason

2014-03-01

MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy are two promising techniques that could significantly increase the accuracy of the curative dose delivery processes while reducing the total radiation dose. State-of-the-art methods rely on the registration of a patient MRI with a MR-CT atlas for the estimation of pseudo-CT [5]. This atlas itself is generally created by registering many CT and MRI pairs. Most registration methods are not symmetric, but the order of the images influences the result [8]. The computed transformation is therefore biased, introducing unwanted variability. This work examines how much a symmetric algorithm improves the registration. Methods: A robust symmetric registration algorithm is proposed that simultaneously optimises a half space transform and its inverse. During the registration process, the two input volumetric images are transformed to a common position in space, therefore minimising any computational bias. An asymmetrical implementation of the same algorithm was used for comparison purposes. Results: Whole pelvis MRI and CT scans from 15 prostate patients were registered, as in the creation of MR-CT atlases. In each case, two registrations were performed, with different input image orders, and the transformation error quantified. Mean residuals of 0.63±0.26 mm (translation) and (8.7±7.3) × 10--3 rad (rotation) were found for the asymmetrical implementation with corresponding values of 0.038±0.039 mm and (1.6 ± 1.3) × 10--3 rad for the proposed symmetric algorithm, a substantial improvement. Conclusions: The increased registration precision will enhance the generation of pseudo-CT from MRI for atlas based MR planning methods.

Kernel Regression Estimation of Fiber Orientation Mixtures in Diffusion MRI

PubMed Central

Cabeen, Ryan P.; Bastin, Mark E.; Laidlaw, David H.

2016-01-01

We present and evaluate a method for kernel regression estimation of fiber orientations and associated volume fractions for diffusion MR tractography and population-based atlas construction in clinical imaging studies of brain white matter. This is a model-based image processing technique in which representative fiber models are estimated from collections of component fiber models in model-valued image data. This extends prior work in nonparametric image processing and multi-compartment processing to provide computational tools for image interpolation, smoothing, and fusion with fiber orientation mixtures. In contrast to related work on multi-compartment processing, this approach is based on directional measures of divergence and includes data-adaptive extensions for model selection and bilateral filtering. This is useful for reconstructing complex anatomical features in clinical datasets analyzed with the ball-and-sticks model, and our framework’s data-adaptive extensions are potentially useful for general multi-compartment image processing. We experimentally evaluate our approach with both synthetic data from computational phantoms and in vivo clinical data from human subjects. With synthetic data experiments, we evaluate performance based on errors in fiber orientation, volume fraction, compartment count, and tractography-based connectivity. With in vivo data experiments, we first show improved scan-rescan reproducibility and reliability of quantitative fiber bundle metrics, including mean length, volume, streamline count, and mean volume fraction. We then demonstrate the creation of a multi-fiber tractography atlas from a population of 80 human subjects. In comparison to single tensor atlasing, our multi-fiber atlas shows more complete features of known fiber bundles and includes reconstructions of the lateral projections of the corpus callosum and complex fronto-parietal connections of the superior longitudinal fasciculus I, II, and III. PMID:26691524

Mean PB To Failure - Initial results from a long-term study of disk storage patterns at the RACF

NASA Astrophysics Data System (ADS)

Caramarcu, C.; Hollowell, C.; Rao, T.; Strecker-Kellogg, W.; Wong, A.; Zaytsev, S. A.

2015-12-01

The RACF (RHIC-ATLAS Computing Facility) has operated a large, multi-purpose dedicated computing facility since the mid-1990’s, serving a worldwide, geographically diverse scientific community that is a major contributor to various HEPN projects. A central component of the RACF is the Linux-based worker node cluster that is used for both computing and data storage purposes. It currently has nearly 50,000 computing cores and over 23 PB of storage capacity distributed over 12,000+ (non-SSD) disk drives. The majority of the 12,000+ disk drives provide a cost-effective solution for dCache/XRootD-managed storage, and a key concern is the reliability of this solution over the lifetime of the hardware, particularly as the number of disk drives and the storage capacity of individual drives grow. We report initial results of a long-term study to measure lifetime PB read/written to disk drives in the worker node cluster. We discuss the historical disk drive mortality rate, disk drive manufacturers' published MPTF (Mean PB to Failure) data and how they are correlated to our results. The results help the RACF understand the productivity and reliability of its storage solutions and have implications for other highly-available storage systems (NFS, GPFS, CVMFS, etc) with large I/O requirements.

Browsing software of the Visible Korean data used for teaching sectional anatomy.

PubMed

Shin, Dong Sun; Chung, Min Suk; Park, Hyo Seok; Park, Jin Seo; Hwang, Sung Bae

2011-01-01

The interpretation of computed tomographs (CTs) and magnetic resonance images (MRIs) to diagnose clinical conditions requires basic knowledge of sectional anatomy. Sectional anatomy has traditionally been taught using sectioned cadavers, atlases, and/or computer software. The computer software commonly used for this subject is practical and efficient for students but could be more advanced. The objective of this research was to present browsing software developed from the Visible Korean images that can be used for teaching sectional anatomy. One thousand seven hundred and two sets of MRIs, CTs, and sectioned images (intervals, one millimeter) of a whole male cadaver were prepared. Over 900 structures in the sectioned images were outlined and then filled with different colors to elaborate each structure. Software was developed where four corresponding images could be displayed simultaneously; in addition, the structures in the image data could be readily recognized with the aid of the color-filled outlines. The software, distributed free of charge, could be a valuable tool to teach medical students. For example, sectional anatomy could be taught by showing the sectioned images with real color and high resolution. Students could then review the lecture by using the sectioned and color-filled images on their own computers. Students could also be evaluated using the same software. Furthermore, other investigators would be able to replace the images for more comprehensive sectional anatomy. Copyright © 2011 Wiley-Liss, Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redler, G; Templeton, A; Turian, J

Purpose: The portability of Xoft Axxent Electronic Brachytherapy (EBx) System has made it a viable option for intraoperative radiation therapy (IORT) treatment of early-stage breast cancer. The low energy (50kVp) of the X-ray source makes the shielding easy, but also means its dose distribution is sensitive to the medium’s composition. Current treatment planning systems (TPS) typically assume homogenous water for brachytherapy dose calculations, including the pre-calculated atlas plans for the Xoft IORT cases. However, Xoft recommends using saline to fill the balloon applicator. This study investigates the dosimetric difference due to the increased effective atomic number (Zeff) from water (7.42)more » to saline (7.56). Methods: The diameter of the balloon applicators ranges from 3–6cm, with 4cm being most frequently used. For the 4-cm and 6-cm diameter applicators, MCNP Monte Carlo program was used to calculate the dose at the surface (Ds) of the middle section of the balloon and 1 cm away (D1cm) for water- and saline-filled balloons: one plan with a single dwell at the center and another with multiple dwells as in the atlas plans. The single dwell plan is a simple estimation of the dosimetry, while the atlas plan is representative of the actual dose distribution. Results: The single-dwell plan showed a 5.1% and 6.1% decrease in Ds for the 4- and 6-cm applicators, respectively, due to the saline. The atlas plan showed similar Results: 4.8% and 6.4% decrease, respectively. The decrease in D1cm is 4.3%–5.2% and 3.3%–5.3s% in the single-dwell and atlas plans, respectively, for the 4- and 6-cm applicator. Conclusion: The dosimetric effect introduced by saline is on the order of 5%. This effect should be taken into account during both treatment planning and patient outcome studies.« less

Charged-particle distributions at low transverse momentum in [Formula: see text] TeV pp interactions measured with the ATLAS detector at the LHC.

PubMed

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2016-01-01

Measurements of distributions of charged particles produced in proton-proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 [Formula: see text]. The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators.

Charged-particle distributions at low transverse momentum in √{s} = 13 TeV pp interactions measured with the ATLAS detector at the LHC

NASA Astrophysics Data System (ADS)

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A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Seabra, L. F. Oleiro; Pino, S. A. Olivares; Damazio, D. Oliveira; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; y Garzon, G. Otero; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pages, A. Pacheco; Rodriguez, L. Pacheco; Aranda, C. Padilla; Pagáčová, M.; Griso, S. Pagan; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Palka, M.; Pallin, D.; Palma, A.; Panagiotopoulou, E. St.; Pandini, C. E.; Vazquez, J. G. Panduro; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Hernandez, D. Paredes; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Lopez, S. Pedraza; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Codina, E. Perez; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Astigarraga, M. E. Pozo; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Perez, A. Rodriguez; Rodriguez, D. Rodriguez; Roe, S.; Rogan, C. S.; Røhne, O.; Romaniouk, A.; Romano, M.; Saez, S. M. Romano; Adam, E. Romero; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosenthal, O.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. 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Santoyo; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Sanchez, C. A. Solans; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Kate, H. Ten; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Santurio, E. Valdes; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Ferrer, J. A. Valls; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Nedden, M. zur; Zwalinski, L.

2016-09-01

Measurements of distributions of charged particles produced in proton-proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 μ{b}^{-1}. The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators.

Search for new physics in the dijet mass distribution using 1 fb –1 of pp collision data at s = 7 TeV collected by the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2012-01-14

Invariant mass distributions of jet pairs (dijets) produced in LHC proton–proton collisions at a centre-of-mass energy √s = 7 TeV have been studied using a data set corresponding to an integrated luminosity of 1.0 fb -1 recorded in 2011 by ATLAS. Dijet masses up to ~4 TeV are observed in the data, and no evidence of resonance production over background is found. Here the limits are set at 95% C.L. for several new physics hypotheses: excited quarks are excluded for masses below 299 TeV, axigluons are excluded for masses below 3.32 TeV, and colour octet scalar resonances are excluded formore » masses below 1.92 TeV.« less

Accurate computation of survival statistics in genome-wide studies.

PubMed

Vandin, Fabio; Papoutsaki, Alexandra; Raphael, Benjamin J; Upfal, Eli

2015-05-01

A key challenge in genomics is to identify genetic variants that distinguish patients with different survival time following diagnosis or treatment. While the log-rank test is widely used for this purpose, nearly all implementations of the log-rank test rely on an asymptotic approximation that is not appropriate in many genomics applications. This is because: the two populations determined by a genetic variant may have very different sizes; and the evaluation of many possible variants demands highly accurate computation of very small p-values. We demonstrate this problem for cancer genomics data where the standard log-rank test leads to many false positive associations between somatic mutations and survival time. We develop and analyze a novel algorithm, Exact Log-rank Test (ExaLT), that accurately computes the p-value of the log-rank statistic under an exact distribution that is appropriate for any size populations. We demonstrate the advantages of ExaLT on data from published cancer genomics studies, finding significant differences from the reported p-values. We analyze somatic mutations in six cancer types from The Cancer Genome Atlas (TCGA), finding mutations with known association to survival as well as several novel associations. In contrast, standard implementations of the log-rank test report dozens-hundreds of likely false positive associations as more significant than these known associations.

Accurate Computation of Survival Statistics in Genome-Wide Studies

PubMed Central

Vandin, Fabio; Papoutsaki, Alexandra; Raphael, Benjamin J.; Upfal, Eli

2015-01-01

A key challenge in genomics is to identify genetic variants that distinguish patients with different survival time following diagnosis or treatment. While the log-rank test is widely used for this purpose, nearly all implementations of the log-rank test rely on an asymptotic approximation that is not appropriate in many genomics applications. This is because: the two populations determined by a genetic variant may have very different sizes; and the evaluation of many possible variants demands highly accurate computation of very small p-values. We demonstrate this problem for cancer genomics data where the standard log-rank test leads to many false positive associations between somatic mutations and survival time. We develop and analyze a novel algorithm, Exact Log-rank Test (ExaLT), that accurately computes the p-value of the log-rank statistic under an exact distribution that is appropriate for any size populations. We demonstrate the advantages of ExaLT on data from published cancer genomics studies, finding significant differences from the reported p-values. We analyze somatic mutations in six cancer types from The Cancer Genome Atlas (TCGA), finding mutations with known association to survival as well as several novel associations. In contrast, standard implementations of the log-rank test report dozens-hundreds of likely false positive associations as more significant than these known associations. PMID:25950620

Search for new phenomena in dijet mass and angular distributions from $pp$ collisions at $$\\sqrt{s}$$ = 13 TeV with the ATLAS detector

DOE PAGES

Aad, G.

2016-01-20

This Letter describes a model-agnostic search for pairs of jets (dijets) produced by resonant and non-resonant phenomena beyond the Standard Model in 3.6 fb -1 of proton–proton collisions with a centre-of-mass energy of √s = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. The distribution of the invariant mass of the two leading jets is examined for local excesses above a data-derived estimate of the smoothly falling prediction of the Standard Model. The data are also compared to a Monte Carlo simulation of Standard Model angular distributions derived from the rapidity of the two jets. Nomore » evidence of anomalous phenomena is observed in the data, which are used to exclude, at 95% CL, quantum black holes with threshold masses below 8.3 TeV, 8.1 TeV, or 5.1 TeV5.1 TeV in three different benchmark scenarios; resonance masses below 5.2 TeV for excited quarks, 2.6 TeV in a W' model, a range of masses starting from m Z' = 1.5 TeV and couplings from g q = 0.2 in a Z' model; and contact interactions with a compositeness scale below 12.0 TeV and 17.5 TeV respectively for destructive and constructive interference between the new interaction and QCD processes. These results significantly extend the ATLAS limits obtained from 8 TeV data. As a result, gaussian-shaped contributions to the mass distribution are also excluded if the effective cross-section exceeds values ranging from approximately 50–300 fb for masses below 2 TeV to 2–20 fb for masses above 4 TeV.« less

AB119. Computer-aided facial recognition of Chinese individuals with 22q11.2 deletion-algorithm training using NIH atlas of human malformation syndromes from diverse population

PubMed Central

Mok, Gary Tsz Kin; Chung, Brian Hon-Yin

2017-01-01

Background 22q11.2 deletion syndrome (22q11.2DS) is a common genetic disorder with an estimated frequency of 1/4,000. It is a multi-systemic disorder with high phenotypic variability. Our previous work showed substantial under-diagnosis of 22q11.2DS as 1 in 10 adult patients with conotruncal defects were found to have 22q11.2DS. The National Institute of Health (NIH) has created an atlas of human malformation syndrome from diverse populations to provide an easy tool to assist clinician in diagnosing the syndromic across various populations. In this study, we seek to determine whether training the computer-aided facial recognition technology using images from ethnicity-matched patients from the NIH Atlas can improve the detection performance of this technology. Methods Clinical photographs of 16 Chinese subjects with molecularly confirmed 22q11.2DS, from the NIH atlas and its related publication were used for training the facial recognition technology. The system automatically localizes hundreds of facial fiducial points and takes measurements. The final classification is based on these measurements, as well as an estimated probability of subjects having 22q11.2DS based on the entire facial image. Clinical photographs of 7 patients with molecularly confirmed 22q11.2DS were obtained with informed consent and used for testing the performance in recognizing facial profiles of the Chinese subjects before and after training. Results All 7 test cases were improved in ranking and scoring after the software training. In 4 cases, 22q11.2DS did not appear as one possible syndrome match before the training; however, it appeared within the first 10 syndrome matches after training. Conclusions The present pilot data shows that this technology can be trained to recognize patients with 22q11.2DS. It also highlights the need to collect clinical photographs of patients from diverse populations to be used as resources for training the software which can lead to improvement of the performance of computer-aided facial recognition technology.

Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

PubMed Central

Grocott, Timothy; Thomas, Paul; Münsterberg, Andrea E.

2016-01-01

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states. PMID:26864723

Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks.

PubMed

Grocott, Timothy; Thomas, Paul; Münsterberg, Andrea E

2016-02-11

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states.

A Sundial-Atlas Precursor to the TIMED Mission: A Quick-Response Global Investigation into Coupled Lower Thermospheric, Ionospheric, and Mesospheric Physics

NASA Technical Reports Server (NTRS)

Szuszczewicz, E. P.

1996-01-01

The SUNDIAL-ATLAS effort was a global-scale investigation which responded to the science priorities of the ITM Panel, the Integrated SPD Strategy Implementation Plan as a whole, and the need for potential cost-saving design criteria for the TIMED mission. The investigation focused on coupling processes in the ionospheric-thermospheric system, taking advantage of the timelines of the ATLAS-1 mission (March 1992), and the global-scale ground-based measurement and modeling activities of the SUNDIAL program. The collaborative SUNDIAL-ATLAS activity was the first opportunity for global measurements of the chemistry, kinetics, and electrodynamics which couple the E-, Fl-, and F2-regions into a single interactive system. As such, the program represented an important first step in studying global issues; and accordingly, was an important proof of concept experiment relevant to the strategic mission plans for the ITM community and the upcoming intermediate class satellite program called TIMED. To meet its projected goals, TIMED must perform a number of critical measurements and execute a number of correlations that were to be tried and tested for the first time in the SUNDIAL-ATLAS investigation. This was designed to include global correlations of thermospheric and ionospheric composition during quiet and disturbed conditions and the co-registration of global-scale ground-based measurements with along-track satellite diagnostics. The SUNDIAL component of the current investigation addressed this need by acquiring, reducing, and analyzing a multi-sensor database that complemented and extended that which was generated in the ATLAS mission (Atmospheric Laboratory for Applications and Science). The SUNDIAL data defined the state and condition of the global-scale ionosphere in the altitude range from 100 km to the F2-peak. These data specified the peak heights and densities of the E-, Fl-, and F2-regions, along with the global distributions of intermediate, descending, and sequential layers which play a critical role in the dynamo region of the lower ionospheric-thermospheric domain. The data were collected by the SUNDIAL network of more than 50 ground-based stations utilizing ionosondes, radars, photometers, Fabry-Perot interferometers, and total electron content measurements. The data were acquired during a three-week period centered on the eight-day ATLAS-1 mission, which provided image and photometric sensing of the altitude distributions of the major and minor ions and neutrals in the ITM system. This report focuses on the scientific contributions of the SUNDIAL component of the overall investigation. Specific findings are described in seven papers (attached) published in the Journal of Geophysical Research.

Teaching resources for dermatology on the WWW--quiz system and dynamic lecture scripts using a HTTP-database demon.

PubMed Central

Bittorf, A.; Diepgen, T. L.

1996-01-01

The World Wide Web (WWW) is becoming the major way of acquiring information in all scientific disciplines as well as in business. It is very well suitable for fast distribution and exchange of up to date teaching resources. However, to date most teaching applications on the Web do not use its full power by integrating interactive components. We have set up a computer based training (CBT) framework for Dermatology, which consists of dynamic lecture scripts, case reports, an atlas and a quiz system. All these components heavily rely on an underlying image database that permits the creation of dynamic documents. We used a demon process that keeps the database open and can be accessed using HTTP to achieve better performance and avoid the overhead involved by starting CGI-processes. The result of our evaluation was very encouraging. Images Figure 3 PMID:8947625

Computer-aided placement of deep brain stimulators: from planning to intraoperative guidance

NASA Astrophysics Data System (ADS)

D'Haese, Pierre-Francois; Pallavaram, Srivatsan; Kao, Chris; Konrad, Peter E.; Dawant, Benoit M.

2005-04-01

The long term objective of our research is to develop a system that will automate as much as possible DBS implantation procedures. It is estimated that about 180,000 patients/year would benefit from DBS implantation. Yet, only 3000 procedures are performed annually. This is so because the combined expertise required to perform the procedure successfully is only available at a limited number of sites. Our goal is to transform this procedure into a procedure that can be performed by a general neurosurgeon at a community hospital. In this work we report on our current progress toward developing a system for the computer-assisted pre-operative selection of target points and for the intra-operative adjustment of these points. The system consists of a deformable atlas of optimal target points that can be used to select automatically the pre-operative target, of an electrophysiological atlas, and of an intra-operative interface. The atlas is deformed using a rigid then a non-rigid registration algorithm developed at our institution. Results we have obtained show that automatic prediction of target points is an achievable goal. Our results also indicate that electrophysiological information can be used to resolve structures not visible in anatomic images, thus improving both pre-operative and intra-operative guidance. Our intra-operative system has reached the stage of a working prototype that is clinically used at our institution.

Recent advances in PC-Linux systems for electronic structure computations by optimized compilers and numerical libraries.

PubMed

Yu, Jen-Shiang K; Yu, Chin-Hui

2002-01-01

One of the most frequently used packages for electronic structure research, GAUSSIAN 98, is compiled on Linux systems with various hardware configurations, including AMD Athlon (with the "Thunderbird" core), AthlonMP, and AthlonXP (with the "Palomino" core) systems as well as the Intel Pentium 4 (with the "Willamette" core) machines. The default PGI FORTRAN compiler (pgf77) and the Intel FORTRAN compiler (ifc) are respectively employed with different architectural optimization options to compile GAUSSIAN 98 and test the performance improvement. In addition to the BLAS library included in revision A.11 of this package, the Automatically Tuned Linear Algebra Software (ATLAS) library is linked against the binary executables to improve the performance. Various Hartree-Fock, density-functional theories, and the MP2 calculations are done for benchmarking purposes. It is found that the combination of ifc with ATLAS library gives the best performance for GAUSSIAN 98 on all of these PC-Linux computers, including AMD and Intel CPUs. Even on AMD systems, the Intel FORTRAN compiler invariably produces binaries with better performance than pgf77. The enhancement provided by the ATLAS library is more significant for post-Hartree-Fock calculations. The performance on one single CPU is potentially as good as that on an Alpha 21264A workstation or an SGI supercomputer. The floating-point marks by SpecFP2000 have similar trends to the results of GAUSSIAN 98 package.

Computer-aided bone age assessment for ethnically diverse older children using integrated fuzzy logic system

NASA Astrophysics Data System (ADS)

Ma, Kevin; Moin, Paymann; Zhang, Aifeng; Liu, Brent

2010-03-01

Bone Age Assessment (BAA) of children is a clinical procedure frequently performed in pediatric radiology to evaluate the stage of skeletal maturation based on the left hand x-ray radiograph. The current BAA standard in the US is using the Greulich & Pyle (G&P) Hand Atlas, which was developed fifty years ago and was only based on Caucasian population from the Midwest US. To bring the BAA procedure up-to-date with today's population, a Digital Hand Atlas (DHA) consisting of 1400 hand images of normal children of different ethnicities, age, and gender. Based on the DHA and to solve inter- and intra-observer reading discrepancies, an automatic computer-aided bone age assessment system has been developed and tested in clinical environments. The algorithm utilizes features extracted from three regions of interests: phalanges, carpal, and radius. The features are aggregated into a fuzzy logic system, which outputs the calculated bone age. The previous BAA system only uses features from phalanges and carpal, thus BAA result for children over age of 15 is less accurate. In this project, the new radius features are incorporated into the overall BAA system. The bone age results, calculated from the new fuzzy logic system, are compared against radiologists' readings based on G&P atlas, and exhibits an improvement in reading accuracy for older children.

TDRS-L spacecraft lift to mate on Atlas V

NASA Image and Video Library

2014-01-13

CAPE CANAVERAL, Fla. – At Cape Canaveral Air Force Station's Vertical Integration Facility at Launch Complex 41, NASA's Tracking and Data Relay Satellite, or TDRS-L, spacecraft is lifted for mounting atop a United Launch Alliance Atlas V rocket. The TDRS-L satellite will be a part of the second of three next-generation spacecraft designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop a United Launch Alliance Atlas V rocket on Jan. 23, 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay contact with orbiting spacecraft ranging from the International Space Station and Hubble Space Telescope to the array of scientific observatories. For more information, visit: http://www.nasa.gov/mission_pages/tdrs/home/index.html Photo credit: NASA/Dimitri Gerondidakis

TDRS-L spacecraft lift to mate on Atlas V

NASA Image and Video Library

2014-01-13

CAPE CANAVERAL, Fla. – At Cape Canaveral Air Force Station's Vertical Integration Facility at Launch Complex 41, NASA's Tracking and Data Relay Satellite, or TDRS-L, spacecraft is moved into position for mating atop a United Launch Alliance Atlas V rocket. The TDRS-L satellite will be a part of the second of three next-generation spacecraft designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop a United Launch Alliance Atlas V rocket on Jan. 23, 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay contact with orbiting spacecraft ranging from the International Space Station and Hubble Space Telescope to the array of scientific observatories. For more information, visit: http://www.nasa.gov/mission_pages/tdrs/home/index.html Photo credit: NASA/Dimitri Gerondidakis

KSC-2013-3786

NASA Image and Video Library

2013-11-01

CAPE CANAVERAL, Fla. – The United Launch Alliance Atlas V launch vehicle, left, and Centaur upper stage that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to the hangar at the Atlas Spaceflight Operations Center on Cape Canaveral Air Force Station for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Jim Grossman

TDRS-L spacecraft lift to mate on Atlas V

NASA Image and Video Library

2014-01-13

CAPE CANAVERAL, Fla. – At Cape Canaveral Air Force Station's Vertical Integration Facility at Launch Complex 41, NASA's Tracking and Data Relay Satellite, or TDRS-L, spacecraft has been mated atop a United Launch Alliance Atlas V rocket. The TDRS-L satellite will be a part of the second of three next-generation spacecraft designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop a United Launch Alliance Atlas V rocket on Jan. 23, 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay contact with orbiting spacecraft ranging from the International Space Station and Hubble Space Telescope to the array of scientific observatories. For more information, visit: http://www.nasa.gov/mission_pages/tdrs/home/index.html Photo credit: NASA/Dimitri Gerondidakis

KSC-2013-3782

NASA Image and Video Library

2013-11-01

PORT CANAVERAL, Fla. – Following arrival at Port Canaveral, Fla., the United Launch Alliance Atlas V first stage and Centaur upper stage that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to Cape Canaveral Air Force Station's Atlas Spaceflight Operations Center for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Kim Shiflett

KSC-2013-3781

NASA Image and Video Library

2013-11-01

PORT CANAVERAL, Fla. – Following arrival at Port Canaveral, Fla., the United Launch Alliance Atlas V first stage and Centaur upper stage that will boost the Tracking and Data Relay Satellite, or TDRS-L, spacecraft into orbit is being transported to Cape Canaveral Air Force Station's Atlas Spaceflight Operations Center for checkout in preparation for launch. TDRS-L is the second of three next-generation satellites designed to ensure vital operational continuity for the NASA Space Network. It is scheduled to launch from Cape Canaveral's Space Launch Complex 41 atop an Atlas V rocket in January 2014. The current Tracking and Data Relay Satellite system consists of eight in-orbit satellites distributed to provide near continuous information relay service to missions such as the Hubble Space Telescope and International Space Station. For more information, visit: http://www.nasa.gov/content/tracking-and-data-relay-satellite-tdrs/ Photo credit: NASA/ Kim Shiflett

Improvements in simulation of multiple scattering effects in ATLAS fast simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Basalaev, A. E., E-mail: artem.basalaev@cern.ch

Fast ATLAS Tracking Simulation (Fatras) package was verified on single layer geometry with respect to full simulation with GEANT4. Fatras hadronic interactions and multiple scattering simulation were studied in comparison with GEANT4. Disagreement was found in multiple scattering distributions of primary charged particles (μ, π, e). A new model for multiple scattering simulation was implemented in Fatras. The model was based on R. Frühwirth’s mixture models. New model was tested on single layer geometry and a good agreement with GEANT4 was achieved. Also a comparison of reconstructed tracks’ parameters was performed for Inner Detector geometry, and Fatras with new multiplemore » scattering model proved to have better agreement with GEANT4. New model of multiple scattering was added as a part of Fatras package in the development release of ATLAS software—ATHENA.« less

Machine learning of network metrics in ATLAS Distributed Data Management

NASA Astrophysics Data System (ADS)

Lassnig, Mario; Toler, Wesley; Vamosi, Ralf; Bogado, Joaquin; ATLAS Collaboration

2017-10-01

The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for networkaware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

A transversal approach for patch-based label fusion via matrix completion

PubMed Central

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Thung, Kim-Han; Guo, Yanrong; Shen, Dinggang

2015-01-01

Recently, multi-atlas patch-based label fusion has received an increasing interest in the medical image segmentation field. After warping the anatomical labels from the atlas images to the target image by registration, label fusion is the key step to determine the latent label for each target image point. Two popular types of patch-based label fusion approaches are (1) reconstruction-based approaches that compute the target labels as a weighted average of atlas labels, where the weights are derived by reconstructing the target image patch using the atlas image patches; and (2) classification-based approaches that determine the target label as a mapping of the target image patch, where the mapping function is often learned using the atlas image patches and their corresponding labels. Both approaches have their advantages and limitations. In this paper, we propose a novel patch-based label fusion method to combine the above two types of approaches via matrix completion (and hence, we call it transversal). As we will show, our method overcomes the individual limitations of both reconstruction-based and classification-based approaches. Since the labeling confidences may vary across the target image points, we further propose a sequential labeling framework that first labels the highly confident points and then gradually labels more challenging points in an iterative manner, guided by the label information determined in the previous iterations. We demonstrate the performance of our novel label fusion method in segmenting the hippocampus in the ADNI dataset, subcortical and limbic structures in the LONI dataset, and mid-brain structures in the SATA dataset. We achieve more accurate segmentation results than both reconstruction-based and classification-based approaches. Our label fusion method is also ranked 1st in the online SATA Multi-Atlas Segmentation Challenge. PMID:26160394

Atlas instrumentation guided by the medial edge of the posterior arch: An anatomic and radiologic study.

PubMed

Al-Habib, Amro F; Al-Rabie, Abdulkarim; Aleissa, Sami; Albakr, Abdulrahman; Abobotain, Abdulaziz

2017-01-01

This was an interventional human cadaver study and radiological study. Atlas instrumentation is frequently involved in fusion procedures involving the craniocervical junction area. Identification of the entry point at the center of atlas lateral mass (ALM) is challenging because of its rounded posterior surface and the surrounding venous plexus. This report examines using the medial edge of atlas posterior arch (MEC1) as a fixed and reliable anatomic reference to guide the entry point of ALM screws. Fifty, normal, cervical spine computed tomography studies were reviewed. ALM screw trajectories were planned at one point along MEC1 and another point 2 mm lateral to MEC1. Free-hand ALM instrumentation was performed in ten fresh human cadavers using the 2 mm entry point, with a sagittal trajectory parallel to atlas inferior arch (IAC1); three-dimensional imaging was then performed to confirm instrumentation accuracy. The average ALM diameter was 12.35 mm. Inserting a screw using the entry point 2 mm lateral to MEC1 was closer to ALM midpoint than using the entry point along MEC1 ( P < 0.0001). Twenty ALM screws were successfully inserted in the ten cadavers. No encroachments into the spinal canal or foramen transversarium occurred. However, two screws were superiorly directed and violated the occipitocervical joint; they were not parallel to IAC1. MEC1 provides a fixed and reliable landmark for ALM instrumentation. An entry point 2 mm point lateral to MEC1 is close to ALM midpoint. IAC1 also provides a guide for the sagittal trajectory. Attention to anatomic landmarks may help reduce complications associated with atlas instrumentation but should be verified in future clinical studies.

Measurement of the centrality dependence of the charged-particle pseudorapidity distribution in proton-lead collisions at [Formula: see text] TeV with the ATLAS detector.

PubMed

Aad, G; Abajyan, T; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Adomeit, S; Adye, T; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmadov, F; Aielli, G; Åkesson, T P A; Akimoto, G; Akimov, A V; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Alimonti, G; Alio, L; Alison, J; Allbrooke, B M M; Allison, L J; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alonso, F; Alpigiani, C; Altheimer, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Ammosov, V V; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Angelidakis, S; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoki, M; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Arce, A T H; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arslan, O; Artamonov, A; Artoni, G; Asai, S; Asbah, N; Ask, S; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Auerbach, B; Auge, E; Augsten, K; Aurousseau, M; Avolio, G; Azuelos, G; Azuma, Y; Baak, M A; Bacci, C; Bach, A M; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Backus Mayes, J; Badescu, E; Bagiacchi, P; Bagnaia, P; Bai, Y; Bailey, D C; Bain, T; Baines, J T; Baker, O K; Baker, S; Balek, P; Balli, F; Banas, E; Banerjee, Sw; Bangert, A; Bansal, V; Bansil, H S; Barak, L; Barber, T; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnett, B M; Barnett, R M; Baroncelli, A; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Bartoldus, R; Barton, A E; Bartos, P; Bartsch, V; Bassalat, A; Basye, A; Bates, R L; Batkova, L; Batley, J R; Battistin, M; Bauer, F; Bawa, H S; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, K; Becker, S; Beckingham, M; Beddall, A J; Beddall, A; Bedikian, S; Bednyakov, V A; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belloni, A; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Bensinger, J R; Benslama, K; Bentvelsen, S; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Berglund, E; Beringer, J; Bernard, C; Bernat, P; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertolucci, F; Besana, M I; Besjes, G J; Bessidskaia Bylund, O; Besson, N; Betancourt, C; Bethke, S; Bhimji, W; Bianchi, R M; Bianchini, L; Bianco, M; Biebel, O; Bieniek, S P; 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Zimmermann, R; Zimmermann, S; Zimmermann, S; Zinonos, Z; Ziolkowski, M; Zitoun, R; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zurzolo, G; Zutshi, V; Zwalinski, L

2016-01-01

The centrality dependence of the mean charged-particle multiplicity as a function of pseudorapidity is measured in approximately 1 [Formula: see text]b[Formula: see text] of proton-lead collisions at a nucleon-nucleon centre-of-mass energy of [Formula: see text] [Formula: see text] using the ATLAS detector at the Large Hadron Collider. Charged particles with absolute pseudorapidity less than 2.7 are reconstructed using the ATLAS pixel detector. The [Formula: see text] collision centrality is characterised by the total transverse energy measured in the Pb-going direction of the forward calorimeter. The charged-particle pseudorapidity distributions are found to vary strongly with centrality, with an increasing asymmetry between the proton-going and Pb-going directions as the collisions become more central. Three different estimations of the number of nucleons participating in the [Formula: see text] collision have been carried out using the Glauber model as well as two Glauber-Gribov inspired extensions to the Glauber model. Charged-particle multiplicities per participant pair are found to vary differently for these three models, highlighting the importance of including colour fluctuations in nucleon-nucleon collisions in the modelling of the initial state of [Formula: see text] collisions.

Measurement of the centrality dependence of the charged-particle pseudorapidity distribution in proton–lead collisions at $$\\sqrt{s_{_\\text {NN}}} = 5.02$$ TeV with the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.; Abajyan, T.; Abbott, B.

2016-04-01

The centrality dependence of the mean charged-particle multiplicity as a function of pseudorapidity is measured in approximately 1 μb -1 of proton–lead collisions at a nucleon–nucleon centre-of-mass energy ofmore » $$\\sqrt{s_{_\\text {NN}}} = 5.02$$ TeV using the ATLAS detector at the Large Hadron Collider. Charged particles with absolute pseudorapidity less than 2.7 are reconstructed using the ATLAS pixel detector. The ρ + Ρb collision centrality is characterised by the total transverse energy measured in the Pb-going direction of the forward calorimeter. The charged-particle pseudorapidity distributions are found to vary strongly with centrality, with an increasing asymmetry between the proton-going and Pb-going directions as the collisions become more central. Three different estimations of the number of nucleons participating in the ρ + Ρb collision have been carried out using the Glauber model as well as two Glauber–Gribov inspired extensions to the Glauber model. In conclusion, charged-particle multiplicities per participant pair are found to vary differently for these three models, highlighting the importance of including colour fluctuations in nucleon–nucleon collisions in the modelling of the initial state of ρ + Ρb collisions.« less

Large Scale Software Building with CMake in ATLAS

NASA Astrophysics Data System (ADS)

Elmsheuser, J.; Krasznahorkay, A.; Obreshkov, E.; Undrus, A.; ATLAS Collaboration

2017-10-01

The offline software of the ATLAS experiment at the Large Hadron Collider (LHC) serves as the platform for detector data reconstruction, simulation and analysis. It is also used in the detector’s trigger system to select LHC collision events during data taking. The ATLAS offline software consists of several million lines of C++ and Python code organized in a modular design of more than 2000 specialized packages. Because of different workflows, many stable numbered releases are in parallel production use. To accommodate specific workflow requests, software patches with modified libraries are distributed on top of existing software releases on a daily basis. The different ATLAS software applications also require a flexible build system that strongly supports unit and integration tests. Within the last year this build system was migrated to CMake. A CMake configuration has been developed that allows one to easily set up and build the above mentioned software packages. This also makes it possible to develop and test new and modified packages on top of existing releases. The system also allows one to detect and execute partial rebuilds of the release based on single package changes. The build system makes use of CPack for building RPM packages out of the software releases, and CTest for running unit and integration tests. We report on the migration and integration of the ATLAS software to CMake and show working examples of this large scale project in production.

The evaluation of multi-structure, multi-atlas pelvic anatomy features in a prostate MR lymphography CAD system

NASA Astrophysics Data System (ADS)

Meijs, M.; Debats, O.; Huisman, H.

2015-03-01

In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.

Creation of an atlas of filter positions for fluence field modulated CT.

PubMed

Szczykutowicz, Timothy P; Hermus, James

2015-04-01

Fluence field modulated CT (FFMCT) and volume of interest (VOI) CT imaging applications require adjustment of the profile of the x-ray fluence incident on a patient as a function of view angle. Since current FFMCT prototypes can theoretically take on an infinite number of configurations, measuring a calibration data set for all possible positions would not be feasible. The present work details a methodology for calculating an atlas of configurations that will span all likely body regions, patient sizes, patient positioning, and imaging modes. The hypothesis is that there exists a finite number of unique modulator configurations that effectively span the infinite number of possible fluence profiles with minimal loss in performance. CT images of a head, shoulder, thorax, abdominal, wrist, and leg anatomical slices were dilated and contracted to model small, medium, and large sized patients. Additionally, the images were positioned from iso-center by three different amounts. The modulator configurations required to compensate for each image were computed assuming a FFMCT prototype, digital beam attenuator, (DBA), was set to equalize the detector exposure. Each atlas configuration should be different from the other atlas configurations. The degree of difference was quantified using the sum of the absolute differences in filter thickness between configurations. Using this metric, a set of unique wedge configurations for which no two configurations have a metric value smaller than some threshold can be constructed. Differences in the total number of incident photons between the unconstrained filters and the atlas were studied as a function of the number of atlas positions for each anatomical site and size/off-centering combination. By varying the threshold used in creating the atlas, it was found that roughly 322 atlas positions provided an incident number of photons within 20% of using 19,440 unique filters (the number of atlas entries ranged from 7213 to 1). Additionally, for VOI applications implemented with a single VOI region, the number of required filter configurations was expressed in a simple closed form solution. The methodology proposed in this work will enable DBA-FFMCT and DBA-VOI imaging in the clinic without the need for patient specific air-scans to be performed. In addition, the methodology proposed here is directly applicable to other modulator designs such as piecewise linear, TomoTherapy multi leaf collimators, 2D fluid arrays, and inverse geometry CT.

Constructing a statistical atlas of the radii of the optic nerve and cerebrospinal fluid sheath in young healthy adults

NASA Astrophysics Data System (ADS)

Harrigan, Robert L.; Plassard, Andrew J.; Mawn, Louise A.; Galloway, Robert L.; Smith, Seth A.; Landman, Bennett A.

2015-03-01

Optic neuritis is a sudden inflammation of the optic nerve (ON) and is marked by pain on eye movement, and visual symptoms such as a decrease in visual acuity, color vision, contrast and visual field defects. The ON is closely linked with multiple sclerosis (MS) and patients have a 50% chance of developing MS within 15 years. Recent advances in multi-atlas segmentation methods have omitted volumetric assessment. In the past, measuring the size of the ON has been done by hand. We utilize a new method of automatically segmenting the ON to measure the radii of both the ON and surrounding cerebrospinal fluid (CSF) sheath to develop a normative distribution of healthy young adults. We examine this distribution for any trends and find that ON and CSF sheath radii do not vary between 20-35 years of age and between sexes. We evaluate how six patients suffering from optic neuropathy compare to this distribution of controls. We find that of these six patients, five of them qualitatively differ from the normative distribution which suggests this technique could be used in the future to distinguish between optic neuritis patients and healthy controls

Measurement of charged-particle distributions sensitive to the underlying event in $$ \\sqrt{s}=13 $$ TeV proton-proton collisions with the ATLAS detector at the LHC

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-03-29

We present charged-particle distributions sensitive to the underlying event, measured by the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV, in low-luminosity Large Hadron Collider fills corresponding to an integrated luminosity of 1.6 nb –1. The distributions were constructed using charged particles with absolute pseudorapidity less than 2.5 and with transverse momentum greater than 500 MeV, in events with at least one such charged particle with transverse momentum above 1 GeV. These distributions characterise the angular distribution of energy and particle flows with respect to the charged particle with highest transverse momentum, as a function ofmore » both that momentum and of charged-particle multiplicity. The results have been corrected for detector effects and are compared to the predictions of various Monte Carlo event generators, experimentally establishing the level of underlying-event activity at LHC Run 2 energies and providing inputs for the development of event generator modelling. The current models in use for UE modelling typically describe this data to 5% accuracy, compared with data uncertainties of less than 1%.« less

Measurement of charged-particle distributions sensitive to the underlying event in $$ \\sqrt{s}=13 $$ TeV proton-proton collisions with the ATLAS detector at the LHC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

We present charged-particle distributions sensitive to the underlying event, measured by the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV, in low-luminosity Large Hadron Collider fills corresponding to an integrated luminosity of 1.6 nb –1. The distributions were constructed using charged particles with absolute pseudorapidity less than 2.5 and with transverse momentum greater than 500 MeV, in events with at least one such charged particle with transverse momentum above 1 GeV. These distributions characterise the angular distribution of energy and particle flows with respect to the charged particle with highest transverse momentum, as a function ofmore » both that momentum and of charged-particle multiplicity. The results have been corrected for detector effects and are compared to the predictions of various Monte Carlo event generators, experimentally establishing the level of underlying-event activity at LHC Run 2 energies and providing inputs for the development of event generator modelling. The current models in use for UE modelling typically describe this data to 5% accuracy, compared with data uncertainties of less than 1%.« less