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.

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.

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.

Evolution of the ATLAS distributed computing system during the LHC long shutdown

NASA Astrophysics Data System (ADS)

Campana, S.; Atlas Collaboration

2014-06-01

The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the Worldwide LHC Computing Grid (WLCG) distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1 PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileup. We will describe the evolution of the ADC software foreseen during this period. This includes consolidating the existing Production and Distributed Analysis framework (PanDA) and ATLAS Grid Information System (AGIS), together with the development and commissioning of next generation systems for distributed data management (DDM/Rucio) and production (Prodsys-2). We will explain how new technologies such as Cloud Computing and NoSQL databases, which ATLAS investigated as R&D projects in past years, will be integrated in production. Finally, we will describe more fundamental developments such as breaking job-to-data locality by exploiting storage federations and caches, and event level (rather than file or dataset level) workload engines.

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.

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

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

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,

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.

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.

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.

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.

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.

Automating ATLAS Computing Operations using the Site Status Board

NASA Astrophysics Data System (ADS)

J, Andreeva; Iglesias C, Borrego; S, Campana; Girolamo A, Di; I, Dzhunov; Curull X, Espinal; S, Gayazov; E, Magradze; M, Nowotka M.; L, Rinaldi; P, Saiz; J, Schovancova; A, Stewart G.; M, Wright

2012-12-01

The automation of operations is essential to reduce manpower costs and improve the reliability of the system. The Site Status Board (SSB) is a framework which allows Virtual Organizations to monitor their computing activities at distributed sites and to evaluate site performance. The ATLAS experiment intensively uses the SSB for the distributed computing shifts, for estimating data processing and data transfer efficiencies at a particular site, and for implementing automatic exclusion of sites from computing activities, in case of potential problems. The ATLAS SSB provides a real-time aggregated monitoring view and keeps the history of the monitoring metrics. Based on this history, usability of a site from the perspective of ATLAS is calculated. The paper will describe how the SSB is integrated in the ATLAS operations and computing infrastructure and will cover implementation details of the ATLAS SSB sensors and alarm system, based on the information in the SSB. It will demonstrate the positive impact of the use of the SSB on the overall performance of ATLAS computing activities and will overview future plans.

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.

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.

Integration of Titan supercomputer at OLCF with ATLAS Production System

NASA Astrophysics Data System (ADS)

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

2017-10-01

The PanDA (Production and Distributed Analysis) workload management system was developed to meet the scale and complexity of distributed computing for the ATLAS experiment. PanDA managed resources are distributed worldwide, on hundreds of computing sites, with thousands of physicists accessing hundreds of Petabytes of data and the rate of data processing already exceeds Exabyte per year. While PanDA currently uses more than 200,000 cores at well over 100 Grid sites, future LHC data taking runs will require more resources than Grid computing can possibly provide. Additional computing and storage resources are required. Therefore ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. In this paper we will describe a project aimed at integration of ATLAS Production System with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). Current approach utilizes modified PanDA Pilot framework for job submission to Titan’s batch queues and local data management, with lightweight MPI wrappers to run single node workloads in parallel on Titan’s multi-core worker nodes. It provides for running of standard ATLAS production jobs on unused resources (backfill) on Titan. The system already allowed ATLAS to collect on Titan millions of core-hours per month, execute hundreds of thousands jobs, while simultaneously improving Titans utilization efficiency. We will discuss the details of the implementation, current experience with running the system, as well as future plans aimed at improvements in scalability and efficiency. 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.

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.

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.

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.

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.

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.

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: 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.

--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

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.

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.

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.

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.

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.

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.

Common Accounting System for Monitoring the ATLAS Distributed Computing Resources

NASA Astrophysics Data System (ADS)

Karavakis, E.; Andreeva, J.; Campana, S.; Gayazov, S.; Jezequel, S.; Saiz, P.; Sargsyan, L.; Schovancova, J.; Ueda, I.; Atlas Collaboration

2014-06-01

This paper covers in detail a variety of accounting tools used to monitor the utilisation of the available computational and storage resources within the ATLAS Distributed Computing during the first three years of Large Hadron Collider data taking. The Experiment Dashboard provides a set of common accounting tools that combine monitoring information originating from many different information sources; either generic or ATLAS specific. This set of tools provides quality and scalable solutions that are flexible enough to support the constantly evolving requirements of the ATLAS user community.

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.

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.

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.

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.

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.

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.

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

Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

NASA Astrophysics Data System (ADS)

Read, A.; Taga, A.; O-Saada, F.; Pajchel, K.; Samset, B. H.; Cameron, D.

2008-07-01

Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation.

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

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

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.

Do Three-dimensional Visualization and Three-dimensional Printing Improve Hepatic Segment Anatomy Teaching? A Randomized Controlled Study.

PubMed

Kong, Xiangxue; Nie, Lanying; Zhang, Huijian; Wang, Zhanglin; Ye, Qiang; Tang, Lei; Li, Jianyi; Huang, Wenhua

2016-01-01

Hepatic segment anatomy is difficult for medical students to learn. Three-dimensional visualization (3DV) is a useful tool in anatomy teaching, but current models do not capture haptic qualities. However, three-dimensional printing (3DP) can produce highly accurate complex physical models. Therefore, in this study we aimed to develop a novel 3DP hepatic segment model and compare the teaching effectiveness of a 3DV model, a 3DP model, and a traditional anatomical atlas. A healthy candidate (female, 50-years old) was recruited and scanned with computed tomography. After three-dimensional (3D) reconstruction, the computed 3D images of the hepatic structures were obtained. The parenchyma model was divided into 8 hepatic segments to produce the 3DV hepatic segment model. The computed 3DP model was designed by removing the surrounding parenchyma and leaving the segmental partitions. Then, 6 experts evaluated the 3DV and 3DP models using a 5-point Likert scale. A randomized controlled trial was conducted to evaluate the educational effectiveness of these models compared with that of the traditional anatomical atlas. The 3DP model successfully displayed the hepatic segment structures with partitions. All experts agreed or strongly agreed that the 3D models provided good realism for anatomical instruction, with no significant differences between the 3DV and 3DP models in each index (p > 0.05). Additionally, the teaching effects show that the 3DV and 3DP models were significantly better than traditional anatomical atlas in the first and second examinations (p < 0.05). Between the first and second examinations, only the traditional method group had significant declines (p < 0.05). A novel 3DP hepatic segment model was successfully developed. Both the 3DV and 3DP models could improve anatomy teaching significantly. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

Atlas : A library for numerical weather prediction and climate modelling

NASA Astrophysics Data System (ADS)

Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

2017-11-01

The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

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.

A virtual reality atlas of craniofacial anatomy.

PubMed

Smith, Darren M; Oliker, Aaron; Carter, Christina R; Kirov, Miro; McCarthy, Joseph G; Cutting, Court B

2007-11-01

Head and neck anatomy is complex and represents an educational challenge to the student. Conventional two-dimensional illustrations inherently fall short in conveying intricate anatomical relationships that exist in three dimensions. A gratis three-dimensional virtual reality atlas of craniofacial anatomy is presented in an effort to address the paucity of readily accessible and customizable three-dimensional educational material available to the student of head and neck anatomy. Three-dimensional model construction was performed in Alias Maya 4.5 and 6.0. A basic three-dimensional skull model was altered to include surgical landmarks and proportions. Some of the soft tissues were adapted from previous work, whereas others were constructed de novo. Texturing was completed with Adobe Photoshop 7.0 and Maya. The Internet application was designed in Viewpoint Enliven 1.0. A three-dimensional computer model of craniofacial anatomy (bone and soft tissue) was completed. The model is compatible with many software packages and can be accessed by means of the Internet or downloaded to a personal computer. As the three-dimensional meshes are publicly available, they can be extensively manipulated by the user, even at the polygonal level. Three-dimensional computer graphics has yet to be fully exploited for head and neck anatomy education. In this context, the authors present a publicly available computer model of craniofacial anatomy. This model may also find applications beyond clinical medicine. The model can be accessed gratis at the Plastic and Reconstructive Surgery Web site or obtained as a three-dimensional mesh, also gratis, by contacting the authors.

[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.

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.

Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model.

PubMed

Martin, Sébastien; Troccaz, Jocelyne; Daanenc, Vincent

2010-04-01

The authors present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. The approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves toward the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. During the evolution of the surface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. The proposed method is evaluated on 36 exams that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.

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.

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.

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.

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.

Distributing and storing data efficiently by means of special datasets in the ATLAS collaboration

NASA Astrophysics Data System (ADS)

Köneke, Karsten; ATLAS Collaboration

2011-12-01

With the start of the LHC physics program, the ATLAS experiment started to record vast amounts of data. This data has to be distributed and stored on the world-wide computing grid in a smart way in order to enable an effective and efficient analysis by physicists. This article describes how the ATLAS collaboration chose to create specialized reduced datasets in order to efficiently use computing resources and facilitate physics analyses.

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.

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

NASA Technical Reports Server (NTRS)

Valenti, Elizabeth; Fitzpatrick, Patrick

2006-01-01

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. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

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

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.

MR-based synthetic CT generation using a deep convolutional neural network method.

PubMed

Han, Xiao

2017-04-01

Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images. The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion. The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN method also provided significantly better accuracy when being evaluated using two other metrics: the mean squared error (188.6 ± 33.7 versus 198.3 ± 33.0) and the Pearson correlation coefficient(0.906 ± 0.03 versus 0.896 ± 0.03). Although training a DCNN model can be slow, training only need be done once. Applying a trained model to generate a complete sCT volume for each new patient MR image only took 9 s, which was much faster than the atlas-based approach. A DCNN model method was developed, and shown to be able to produce highly accurate sCT estimations from conventional, single-sequence MR images in near real time. Quantitative results also showed that the proposed method competed favorably with an atlas-based method, in terms of both accuracy and computation speed at test time. Further validation on dose computation accuracy and on a larger patient cohort is warranted. Extensions of the method are also possible to further improve accuracy or to handle multi-sequence MR images. © 2017 American Association of Physicists in Medicine.

Running ATLAS workloads within massively parallel distributed applications using Athena Multi-Process framework (AthenaMP)

NASA Astrophysics Data System (ADS)

Calafiura, Paolo; Leggett, Charles; Seuster, Rolf; Tsulaia, Vakhtang; Van Gemmeren, Peter

2015-12-01

AthenaMP is a multi-process version of the ATLAS reconstruction, simulation and data analysis framework Athena. By leveraging Linux fork and copy-on-write mechanisms, it allows for sharing of memory pages between event processors running on the same compute node with little to no change in the application code. Originally targeted to optimize the memory footprint of reconstruction jobs, AthenaMP has demonstrated that it can reduce the memory usage of certain configurations of ATLAS production jobs by a factor of 2. AthenaMP has also evolved to become the parallel event-processing core of the recently developed ATLAS infrastructure for fine-grained event processing (Event Service) which allows the running of AthenaMP inside massively parallel distributed applications on hundreds of compute nodes simultaneously. We present the architecture of AthenaMP, various strategies implemented by AthenaMP for scheduling workload to worker processes (for example: Shared Event Queue and Shared Distributor of Event Tokens) and the usage of AthenaMP in the diversity of ATLAS event processing workloads on various computing resources: Grid, opportunistic resources and HPC.

Overview of ATLAS PanDA Workload Management

NASA Astrophysics Data System (ADS)

Maeno, T.; De, K.; Wenaus, T.; Nilsson, P.; Stewart, G. A.; Walker, R.; Stradling, A.; Caballero, J.; Potekhin, M.; Smith, D.; ATLAS Collaboration

2011-12-01

The Production and Distributed Analysis System (PanDA) plays a key role in the ATLAS distributed computing infrastructure. All ATLAS Monte-Carlo simulation and data reprocessing jobs pass through the PanDA system. We will describe how PanDA manages job execution on the grid using dynamic resource estimation and data replication together with intelligent brokerage in order to meet the scaling and automation requirements of ATLAS distributed computing. PanDA is also the primary ATLAS system for processing user and group analysis jobs, bringing further requirements for quick, flexible adaptation to the rapidly evolving analysis use cases of the early datataking phase, in addition to the high reliability, robustness and usability needed to provide efficient and transparent utilization of the grid for analysis users. We will describe how PanDA meets ATLAS requirements, the evolution of the system in light of operational experience, how the system has performed during the first LHC data-taking phase and plans for the future.

Overview of ATLAS PanDA Workload Management

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

Maeno T.; De K.; Wenaus T.

2011-01-01

The Production and Distributed Analysis System (PanDA) plays a key role in the ATLAS distributed computing infrastructure. All ATLAS Monte-Carlo simulation and data reprocessing jobs pass through the PanDA system. We will describe how PanDA manages job execution on the grid using dynamic resource estimation and data replication together with intelligent brokerage in order to meet the scaling and automation requirements of ATLAS distributed computing. PanDA is also the primary ATLAS system for processing user and group analysis jobs, bringing further requirements for quick, flexible adaptation to the rapidly evolving analysis use cases of the early datataking phase, in additionmore » to the high reliability, robustness and usability needed to provide efficient and transparent utilization of the grid for analysis users. We will describe how PanDA meets ATLAS requirements, the evolution of the system in light of operational experience, how the system has performed during the first LHC data-taking phase and plans for the future.« less

Advanced Technology Lifecycle Analysis System (ATLAS)

NASA Technical Reports Server (NTRS)

O'Neil, Daniel A.; Mankins, John C.

2004-01-01

Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is satisfied with the system configurations, technology portfolios, and deployment strategies, he or she can present the concepts to a team, which will conduct a detailed, discipline-oriented analysis within a CEE. An analog to this approach is the music industry where a songwriter creates the lyrics and music before entering a recording studio.

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.

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.

Medical Student Preferences for Self-Directed Study Resources in Gross Anatomy

ERIC Educational Resources Information Center

Choi-Lundberg, Derek L.; Low, Tze Feng; Patman, Phillip; Turner, Paul; Sinha, Sankar N.

2016-01-01

Gross anatomy instruction in medical curricula involve a range of resources and activities including dissection, prosected specimens, anatomical models, radiological images, surface anatomy, textbooks, atlases, and computer-assisted learning (CAL). These resources and activities are underpinned by the expectation that students will actively engage…

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

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.

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.

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.

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.

ATLAS Distributed Computing Monitoring tools during the LHC Run I

NASA Astrophysics Data System (ADS)

Schovancová, J.; Campana, S.; Di Girolamo, A.; Jézéquel, S.; Ueda, I.; Wenaus, T.; Atlas Collaboration

2014-06-01

This contribution summarizes evolution of the ATLAS Distributed Computing (ADC) Monitoring project during the LHC Run I. The ADC Monitoring targets at the three groups of customers: ADC Operations team to early identify malfunctions and escalate issues to an activity or a service expert, ATLAS national contacts and sites for the real-time monitoring and long-term measurement of the performance of the provided computing resources, and the ATLAS Management for long-term trends and accounting information about the ATLAS Distributed Computing resources. During the LHC Run I a significant development effort has been invested in standardization of the monitoring and accounting applications in order to provide extensive monitoring and accounting suite. ADC Monitoring applications separate the data layer and the visualization layer. The data layer exposes data in a predefined format. The visualization layer is designed bearing in mind visual identity of the provided graphical elements, and re-usability of the visualization bits across the different tools. A rich family of various filtering and searching options enhancing available user interfaces comes naturally with the data and visualization layer separation. With a variety of reliable monitoring data accessible through standardized interfaces, the possibility of automating actions under well defined conditions correlating multiple data sources has become feasible. In this contribution we discuss also about the automated exclusion of degraded resources and their automated recovery in various activities.

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.

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.

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.

The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart.

PubMed

Fonseca, Carissa G; Backhaus, Michael; Bluemke, David A; Britten, Randall D; Chung, Jae Do; Cowan, Brett R; Dinov, Ivo D; Finn, J Paul; Hunter, Peter J; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Medrano-Gracia, Pau; Shivkumar, Kalyanam; Suinesiaputra, Avan; Tao, Wenchao; Young, Alistair A

2011-08-15

Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups. Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt). http://www.cardiacatlas.org a.young@auckland.ac.nz Supplementary data are available at Bioinformatics online.

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.

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.

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.

Implementation of an object oriented track reconstruction model into multiple LHC experiments*

NASA Astrophysics Data System (ADS)

Gaines, Irwin; Gonzalez, Saul; Qian, Sijin

2001-10-01

An Object Oriented (OO) model (Gaines et al., 1996; 1997; Gaines and Qian, 1998; 1999) for track reconstruction by the Kalman filtering method has been designed for high energy physics experiments at high luminosity hadron colliders. The model has been coded in the C++ programming language and has been successfully implemented into the OO computing environments of both the CMS (1994) and ATLAS (1994) experiments at the future Large Hadron Collider (LHC) at CERN. We shall report: how the OO model was adapted, with largely the same code, to different scenarios and serves the different reconstruction aims in different experiments (i.e. the level-2 trigger software for ATLAS and the offline software for CMS); how the OO model has been incorporated into different OO environments with a similar integration structure (demonstrating the ease of re-use of OO program); what are the OO model's performance, including execution time, memory usage, track finding efficiency and ghost rate, etc.; and additional physics performance based on use of the OO tracking model. We shall also mention the experience and lessons learned from the implementation of the OO model into the general OO software framework of the experiments. In summary, our practice shows that the OO technology really makes the software development and the integration issues straightforward and convenient; this may be particularly beneficial for the general non-computer-professional physicists.

Comparison of optimization strategy and similarity metric in atlas-to-subject registration using statistical deformation model

NASA Astrophysics Data System (ADS)

Otake, Y.; Murphy, R. J.; Grupp, R. B.; Sato, Y.; Taylor, R. H.; Armand, M.

2015-03-01

A robust atlas-to-subject registration using a statistical deformation model (SDM) is presented. The SDM uses statistics of voxel-wise displacement learned from pre-computed deformation vectors of a training dataset. This allows an atlas instance to be directly translated into an intensity volume and compared with a patient's intensity volume. Rigid and nonrigid transformation parameters were simultaneously optimized via the Covariance Matrix Adaptation - Evolutionary Strategy (CMA-ES), with image similarity used as the objective function. The algorithm was tested on CT volumes of the pelvis from 55 female subjects. A performance comparison of the CMA-ES and Nelder-Mead downhill simplex optimization algorithms with the mutual information and normalized cross correlation similarity metrics was conducted. Simulation studies using synthetic subjects were performed, as well as leave-one-out cross validation studies. Both studies suggested that mutual information and CMA-ES achieved the best performance. The leave-one-out test demonstrated 4.13 mm error with respect to the true displacement field, and 26,102 function evaluations in 180 seconds, on average.

Fast automated segmentation of multiple objects via spatially weighted shape learning

NASA Astrophysics Data System (ADS)

Chandra, Shekhar S.; Dowling, Jason A.; Greer, Peter B.; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

2016-11-01

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice’s similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

Fast automated segmentation of multiple objects via spatially weighted shape learning.

PubMed

Chandra, Shekhar S; Dowling, Jason A; Greer, Peter B; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

2016-11-21

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice's similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

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.

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

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

Automated anatomical description of pleural thickening towards improvement of its computer-assisted diagnosis

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Jiang, Mingze; Faltin, Peter; Merhof, Dorit; Eisenhawer, Christian; Gube, Monika; Kraus, Thomas

2016-03-01

Pleural thickenings are caused by asbestos exposure and may evolve into malignant pleural mesothelioma. An early diagnosis plays a key role towards an early treatment and an increased survival rate. Today, pleural thickenings are detected by visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment. A computer-assisted diagnosis system to automatically assess pleural thickenings has been developed, which includes not only a quantitative assessment with respect to size and location, but also enhances this information with an anatomical description, i.e. lung side (left, right), part of pleura (pars costalis, mediastinalis, diaphragmatica, spinalis), as well as vertical (upper, middle, lower) and horizontal (ventral, dorsal) position. For this purpose, a 3D anatomical model of the lung surface has been manually constructed as a 3D atlas. Three registration sub-steps including rigid, affine, and nonrigid registration align the input patient lung to the 3D anatomical atlas model of the lung surface. Finally, each detected pleural thickening is assigned a set of labels describing its anatomical properties. Through this added information, an enhancement to the existing computer-assisted diagnosis system is presented in order to assure a higher precision and reproducible assessment of pleural thickenings, aiming at the diagnosis of the pleural mesothelioma in its early stage.

Exploring the changing learning environment of the gross anatomy lab.

PubMed

Hopkins, Robin; Regehr, Glenn; Wilson, Timothy D

2011-07-01

The objective of this study was to assess the impact of virtual models and prosected specimens in the context of the gross anatomy lab. In 2009, student volunteers from an undergraduate anatomy class were randomly assigned to study groups in one of three learning conditions. All groups studied the muscles of mastication and completed identical learning objectives during a 45-minute lab. All groups were provided with two reference atlases. Groups were distinguished by the type of primary tools they were provided: gross prosections, three-dimensional stereoscopic computer model, or both resources. The facilitator kept observational field notes. A prepost multiple-choice knowledge test was administered to evaluate students' learning. No significant effect of the laboratory models was demonstrated between groups on the prepost assessment of knowledge. Recurring observations included students' tendency to revert to individual memorization prior to the posttest, rotation of models to match views in the provided atlas, and dissemination of groups into smaller working units. The use of virtual lab resources seemed to influence the social context and learning environment of the anatomy lab. As computer-based learning methods are implemented and studied, they must be evaluated beyond their impact on knowledge gain to consider the effect technology has on students' social development.

Classifying Infrastructure in an Urban Battlespace Using Thermal IR Signatures

DTIC Science & Technology

2006-11-01

Huntsville, Alabama for sharing their ATLAS data for Atlanta. REFERENCES Bentz , D . P . (2000). A Computer Model to Predict the Surface Temperature...10: 2 2 xt α Δ Δ ≤ (10) 2.2 Implementing the Model Bentz uses a 1- D finite difference grid with a varying number of nodes. The nodes are equally...and rooftops were modeled as a function of time and environmental conditions using 1- D heat transfer theory. The model was implemented in MATLAB

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

Evolution of the ATLAS PanDA workload management system for exascale computational science

NASA Astrophysics Data System (ADS)

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

2014-06-01

An important foundation underlying the impressive success of data processing and analysis in the ATLAS experiment [1] at the LHC [2] is the Production and Distributed Analysis (PanDA) workload management system [3]. PanDA was designed specifically for ATLAS and proved to be highly successful in meeting all the distributed computing needs of the experiment. However, the core design of PanDA is not experiment specific. The PanDA workload management system is capable of meeting the needs of other data intensive scientific applications. Alpha-Magnetic Spectrometer [4], an astro-particle experiment on the International Space Station, and the Compact Muon Solenoid [5], an LHC experiment, have successfully evaluated PanDA and are pursuing its adoption. In this paper, a description of the new program of work to develop a generic version of PanDA will be given, as well as the progress in extending PanDA's capabilities to support supercomputers and clouds and to leverage intelligent networking. PanDA has demonstrated at a very large scale the value of automated dynamic brokering of diverse workloads across distributed computing resources. The next generation of PanDA will allow other data-intensive sciences and a wider exascale community employing a variety of computing platforms to benefit from ATLAS' experience and proven tools.

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

Atlas-Independent, Electrophysiological Mapping of the Optimal Locus of Subthalamic Deep Brain Stimulation for the Motor Symptoms of Parkinson Disease.

PubMed

Conrad, Erin C; Mossner, James M; Chou, Kelvin L; Patil, Parag G

2018-05-23

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms of Parkinson disease (PD). However, motor outcomes can be variable, perhaps due to inconsistent positioning of the active contact relative to an unknown optimal locus of stimulation. Here, we determine the optimal locus of STN stimulation in a geometrically unconstrained, mathematically precise, and atlas-independent manner, using Unified Parkinson Disease Rating Scale (UPDRS) motor outcomes and an electrophysiological neuronal stimulation model. In 20 patients with PD, we mapped motor improvement to active electrode location, relative to the individual, directly MRI-visualized STN. Our analysis included a novel, unconstrained and computational electrical-field model of neuronal activation to estimate the optimal locus of DBS. We mapped the optimal locus to a tightly defined ovoid region 0.49 mm lateral, 0.88 mm posterior, and 2.63 mm dorsal to the anatomical midpoint of the STN. On average, this locus is 11.75 lateral, 1.84 mm posterior, and 1.08 mm ventral to the mid-commissural point. Our novel, atlas-independent method reveals a single, ovoid optimal locus of stimulation in STN DBS for PD. The methodology, here applied to UPDRS and PD, is generalizable to atlas-independent mapping of other motor and non-motor effects of DBS. © 2018 S. Karger AG, Basel.

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.

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.

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.

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.

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.

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.

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.

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

Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials.

PubMed

Yan, Zhennan; Zhang, Shaoting; Tan, Chaowei; Qin, Hongxing; Belaroussi, Boubakeur; Yu, Hui Jing; Miller, Colin; Metaxas, Dimitris N

2015-04-01

Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework. Copyright © 2014 Elsevier Ltd. All rights reserved.

ATLAS WORLD-cloud and networking in PanDA

NASA Astrophysics Data System (ADS)

Barreiro Megino, F.; De, K.; Di Girolamo, A.; Maeno, T.; Walker, R.; ATLAS Collaboration

2017-10-01

The ATLAS computing model was originally designed as static clouds (usually national or geographical groupings of sites) around the Tier 1 centres, which confined tasks and most of the data traffic. Since those early days, the sites’ network bandwidth has increased at 0(1000) and the difference in functionalities between Tier 1s and Tier 2s has reduced. After years of manual, intermediate solutions, we have now ramped up to full usage of World-cloud, the latest step in the PanDA Workload Management System to increase resource utilization on the ATLAS Grid, for all workflows (MC production, data (re)processing, etc.). We have based the development on two new site concepts. Nuclei sites are the Tier 1s and large Tier 2s, where tasks will be assigned and the output aggregated, and satellites are the sites that will execute the jobs and send the output to their nucleus. PanDA dynamically pairs nuclei and satellite sites for each task based on the input data availability, capability matching, site load and network connectivity. This contribution will introduce the conceptual changes for World-cloud, the development necessary in PanDA, an insight into the network model and the first half-year of operational experience.

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.

A Study of ATLAS Grid Performance for Distributed Analysis

NASA Astrophysics Data System (ADS)

Panitkin, Sergey; Fine, Valery; Wenaus, Torre

2012-12-01

In the past two years the ATLAS Collaboration at the LHC has collected a large volume of data and published a number of ground breaking papers. The Grid-based ATLAS distributed computing infrastructure played a crucial role in enabling timely analysis of the data. We will present a study of the performance and usage of the ATLAS Grid as platform for physics analysis in 2011. This includes studies of general properties as well as timing properties of user jobs (wait time, run time, etc). These studies are based on mining of data archived by the PanDA workload management system.

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.

Computed tomography synthesis from magnetic resonance images in the pelvis using multiple random forests and auto-context features

NASA Astrophysics Data System (ADS)

Andreasen, Daniel; Edmund, Jens M.; Zografos, Vasileios; Menze, Bjoern H.; Van Leemput, Koen

2016-03-01

In radiotherapy treatment planning that is only based on magnetic resonance imaging (MRI), the electron density information usually obtained from computed tomography (CT) must be derived from the MRI by synthesizing a so-called pseudo CT (pCT). This is a non-trivial task since MRI intensities are neither uniquely nor quantitatively related to electron density. Typical approaches involve either a classification or regression model requiring specialized MRI sequences to solve intensity ambiguities, or an atlas-based model necessitating multiple registrations between atlases and subject scans. In this work, we explore a machine learning approach for creating a pCT of the pelvic region from conventional MRI sequences without using atlases. We use a random forest provided with information about local texture, edges and spatial features derived from the MRI. This helps to solve intensity ambiguities. Furthermore, we use the concept of auto-context by sequentially training a number of classification forests to create and improve context features, which are finally used to train a regression forest for pCT prediction. We evaluate the pCT quality in terms of the voxel-wise error and the radiologic accuracy as measured by water-equivalent path lengths. We compare the performance of our method against two baseline pCT strategies, which either set all MRI voxels in the subject equal to the CT value of water, or in addition transfer the bone volume from the real CT. We show an improved performance compared to both baseline pCTs suggesting that our method may be useful for MRI-only radiotherapy.

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

Monitoring Of The Middle Atmosphere: Grille Spectrometer Experiment Results On Board SPACELAB 1 And Scientific Program Of ATLAS 1 Mission

NASA Astrophysics Data System (ADS)

Papineau, N.; Camy-Peyret, C.; Ackerman, Marcel E.

1989-10-01

Measurements of atmospheric trace gases have been performed during the first Spacelab mission on board the Space Shuttle. The principle of the observations is infrared absorption spectroscopy using the solar occultation technique. Infrared absorption spectra of NO, CO, CO2, NO2, N20, CH4 and H2O have been recorded using the Grille spectrometer developped by ONERA and IASB. From the observed spectra, vertical profiles for these molecules have been derived. The present paper summarizes the main results and compares them with computed vertical profiles from a zonally averaged model of the middle atmosphere. The scientific objectives of the second mission, Atlas 1, planned for 1990 are also presented.

Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging.

PubMed

Kolb, Christoph; Wetscherek, Andreas; Buzan, Maria Teodora; Werner, René; Rank, Christopher M; Kachelrie, Marc; Kreuter, Michael; Dinkel, Julien; Heuel, Claus Peter; Maier-Hein, Klaus

We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.

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

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

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.

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.

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.

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.

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.

Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy

NASA Astrophysics Data System (ADS)

Gil, D.; Garcia-Barnes, J.; Hernández-Sabate, A.; Marti, E.

2010-03-01

Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.

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.

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

Cembranos, Jose A. R.; Diaz-Cruz, J. Lorenzo; Prado, Lilian

Dark Matter direct detection experiments are able to exclude interesting parameter space regions of particle models which predict an important amount of thermal relics. We use recent data to constrain the branon model and to compute the region that is favored by CDMS measurements. Within this work, we also update present colliders constraints with new studies coming from the LHC. Despite the present low luminosity, it is remarkable that for heavy branons, CMS and ATLAS measurements are already more constraining than previous analyses performed with TEVATRON and LEP data.

Using Generalized Equivalent Uniform Dose Atlases to Combine and Analyze Prospective Dosimetric and Radiation Pneumonitis Data From 2 Non-Small Cell Lung Cancer Dose Escalation Protocols

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

Liu Fan; Yorke, Ellen D.; Belderbos, Jose S.A.

2013-01-01

Purpose: To demonstrate the use of generalized equivalent uniform dose (gEUD) atlas for data pooling in radiation pneumonitis (RP) modeling, to determine the dependence of RP on gEUD, to study the consistency between data sets, and to verify the increased statistical power of the combination. Methods and Materials: Patients enrolled in prospective phase I/II dose escalation studies of radiation therapy of non-small cell lung cancer at Memorial Sloan-Kettering Cancer Center (MSKCC) (78 pts) and the Netherlands Cancer Institute (NKI) (86 pts) were included; 10 (13%) and 14 (17%) experienced RP requiring steroids (RPS) within 6 months after treatment. gEUD wasmore » calculated from dose-volume histograms. Atlases for each data set were created using 1-Gy steps from exact gEUDs and RPS data. The Lyman-Kutcher-Burman model was fit to the atlas and exact gEUD data. Heterogeneity and inconsistency statistics for the fitted parameters were computed. gEUD maps of the probability of RPS rate {>=}20% were plotted. Results: The 2 data sets were homogeneous and consistent. The best fit values of the volume effect parameter a were small, with upper 95% confidence limit around 1.0 in the joint data. The likelihood profiles around the best fit a values were flat in all cases, making determination of the best fit a weak. All confidence intervals (CIs) were narrower in the joint than in the individual data sets. The minimum P value for correlations of gEUD with RPS in the joint data was .002, compared with P=.01 and .05 for MSKCC and NKI data sets, respectively. gEUD maps showed that at small a, RPS risk increases with gEUD. Conclusions: The atlas can be used to combine gEUD and RPS information from different institutions and model gEUD dependence of RPS. RPS has a large volume effect with the mean dose model barely included in the 95% CI. Data pooling increased statistical power.« less

Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain

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

Andreasen, Daniel, E-mail: dana@dtu.dk; Van Leemput, Koen; Hansen, Rasmus H.

Purpose: In radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, the information on electron density must be derived from the MRI scan by creating a so-called pseudo computed tomography (pCT). This is a nontrivial task, since the voxel-intensities in an MRI scan are not uniquely related to electron density. To solve the task, voxel-based or atlas-based models have typically been used. The voxel-based models require a specialized dual ultrashort echo time MRI sequence for bone visualization and the atlas-based models require deformable registrations of conventional MRI scans. In this study, we investigate the potential of amore » patch-based method for creating a pCT based on conventional T{sub 1}-weighted MRI scans without using deformable registrations. We compare this method against two state-of-the-art methods within the voxel-based and atlas-based categories. Methods: The data consisted of CT and MRI scans of five cranial RT patients. To compare the performance of the different methods, a nested cross validation was done to find optimal model parameters for all the methods. Voxel-wise and geometric evaluations of the pCTs were done. Furthermore, a radiologic evaluation based on water equivalent path lengths was carried out, comparing the upper hemisphere of the head in the pCT and the real CT. Finally, the dosimetric accuracy was tested and compared for a photon treatment plan. Results: The pCTs produced with the patch-based method had the best voxel-wise, geometric, and radiologic agreement with the real CT, closely followed by the atlas-based method. In terms of the dosimetric accuracy, the patch-based method had average deviations of less than 0.5% in measures related to target coverage. Conclusions: We showed that a patch-based method could generate an accurate pCT based on conventional T{sub 1}-weighted MRI sequences and without deformable registrations. In our evaluations, the method performed better than existing voxel-based and atlas-based methods and showed a promising potential for RT of the brain based only on MRI.« less

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.

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.

Automated Loads Analysis System (ATLAS)

NASA Technical Reports Server (NTRS)

Gardner, Stephen; Frere, Scot; O’Reilly, Patrick

2013-01-01

ATLAS is a generalized solution that can be used for launch vehicles. ATLAS is used to produce modal transient analysis and quasi-static analysis results (i.e., accelerations, displacements, and forces) for the payload math models on a specific Shuttle Transport System (STS) flight using the shuttle math model and associated forcing functions. This innovation solves the problem of coupling of payload math models into a shuttle math model. It performs a transient loads analysis simulating liftoff, landing, and all flight events between liftoff and landing. ATLAS utilizes efficient and numerically stable algorithms available in MSC/NASTRAN.

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

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.

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.

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.

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.

Analysis of metabolomics datasets with high-performance computing and metabolite atlases

DOE PAGES

Yao, Yushu; Sun, Terence; Wang, Tony; ...

2015-07-20

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged formore » future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.« less

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.

Vector and Scalar Bosons at DØ and ATLAS

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

Lammers, Sabine Sabine

2014-09-26

Vector Boson Fusion (VBF) has never been measured in hadron collisions, but it is one of the most sensitive modes for low mass Standard Model Higgs production at ATLAS. The objective of this proposal is to measure VBF production of W and Z bosons at the DØ Experiment taking place at the Tevatron Collider near Chicago, Illinois, and at the ATLAS Experiment, running at the Large Hadron Collider in Geneva, Switzerland. The framework developed in these measurements will be used to discover and study the Higgs Boson produced through the same mechanism (VBF) at ATLAS. The 10 f b-1 datasetmore » recently collected by the DØ experiment provides a unique opportunity to observe evidence of VBF production of W Bosons, which will provide the required theoretical knowledge - VBF cross sections - and experimental knowledge - tuning of measurement techniques - on which to base the VBF measurements at the LHC. At the time of this writing, the ATLAS experiment has recorded 5 fb-1 of data at √s = 7 TeV, and expects to collect at least another 5 in 2012. Assuming Standard Model cross sections, this dataset will allow for the observation of VBF production of W, Z and Higgs bosons. The major challenges for the first observation of VBF interactions are: developing highly optimized forward jet identification algorithms, and accurately modeling both rates and kinematics of background processes. With the research program outlined in this grant proposal, I plan to address each of these areas, paving the way for VBF observation. The concentration on VBF production for the duration of this grant will be at ATLAS where the anticipated high pileup rates necessitates a cleaner signal. My past experience with forward jet identification at the ZEUS experiment, and with W+(n)Jets measurements at DØ , puts me in a unique position to lead this effort. The proposed program will have a dual focus: on DØ where the VBF analysis effort is mature and efforts of a postdoc will be required to bring the VBF W analysis to a paper, and at ATLAS where a graduate student will begin the effort. I therefore request funding for a student and a postdoc, as well as summer support for myself, for the four year duration of the grant proposal. I also request travel funds to facilitate interactions with my group, presentation at conferences, and a modest amount of money to purchase computing resources.« less

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 Three-Dimensional Atlas of the Honeybee Neck

PubMed Central

Berry, Richard P.; Ibbotson, Michael R.

2010-01-01

Three-dimensional digital atlases are rapidly becoming indispensible in modern biology. We used serial sectioning combined with manual registration and segmentation of images to develop a comprehensive and detailed three-dimensional atlas of the honeybee head-neck system. This interactive atlas includes skeletal structures of the head and prothorax, the neck musculature, and the nervous system. The scope and resolution of the model exceeds atlases previously developed on similar sized animals, and the interactive nature of the model provides a far more accessible means of interpreting and comprehending insect anatomy and neuroanatomy. PMID:20520729

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.

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.

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.

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

Automatic aortic root segmentation in CTA whole-body dataset

NASA Astrophysics Data System (ADS)

Gao, Xinpei; Kitslaar, Pieter H.; Scholte, Arthur J. H. A.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke; Reiber, Johan H. C.

2016-03-01

Trans-catheter aortic valve replacement (TAVR) is an evolving technique for patients with serious aortic stenosis disease. Typically, in this application a CTA data set is obtained of the patient's arterial system from the subclavian artery to the femoral arteries, to evaluate the quality of the vascular access route and analyze the aortic root to determine if and which prosthesis should be used. In this paper, we concentrate on the automated segmentation of the aortic root. The purpose of this study was to automatically segment the aortic root in computed tomography angiography (CTA) datasets to support TAVR procedures. The method in this study includes 4 major steps. First, the patient's cardiac CTA image was resampled to reduce the computation time. Next, the cardiac CTA image was segmented using an atlas-based approach. The most similar atlas was selected from a total of 8 atlases based on its image similarity to the input CTA image. Third, the aortic root segmentation from the previous step was transferred to the patient's whole-body CTA image by affine registration and refined in the fourth step using a deformable subdivision surface model fitting procedure based on image intensity. The pipeline was applied to 20 patients. The ground truth was created by an analyst who semi-automatically corrected the contours of the automatic method, where necessary. The average Dice similarity index between the segmentations of the automatic method and the ground truth was found to be 0.965±0.024. In conclusion, the current results are very promising.

Evaluation of morphological changes in the adult skull with age and sex.

PubMed

Urban, Jillian E; Weaver, Ashley A; Lillie, Elizabeth M; Maldjian, Joseph A; Whitlow, Christopher T; Stitzel, Joel D

2016-12-01

The morphology of the brain and skull are important in the evaluation of the aging human; however, little is known about how the skull may change with age. The objective of this study was to evaluate the morphological changes of the adult skull using three-dimensional geometric morphometric analysis of thousands of landmarks with the focus on anatomic regions that may be correlated with brain atrophy and head injury. Computed tomography data were collected between ages 20 and 100. Each scan was segmented using thresholding techniques. An atlas image of a 50th percentile skull was registered to each subject scan by computing a series of rigid, affine, and non-linear transformations between atlas space and subject space. Landmarks on the atlas skull were transformed to each subject and partitioned into the inner and outer cranial vault and the cranial fossae. A generalized Procrustes analysis was completed for the landmark sets. The coordinate locations describing the shape of each region were regressed with age to generate a model predicting the landmark location with age. Permutation testing was performed to assess significant changes with age. For the males, all anatomic regions reveal significant changes in shape with age except for the posterior cranial fossa. For the females, only the middle cranial fossa and anterior cranial fossa were found to change significantly in shape. Results of this study are important for understanding the adult skull and how shape changes may pertain to brain atrophy, aging, and injury. © 2014 Anatomical Society.

Spatiotemporal characterization of current and future droughts in the High Atlas basins (Morocco)

NASA Astrophysics Data System (ADS)

Zkhiri, Wiam; Tramblay, Yves; Hanich, Lahoucine; Jarlan, Lionel; Ruelland, Denis

2018-02-01

Over the past decades, drought has become a major concern in Morocco due to the importance of agriculture in the economy of the country. In the present work, the standardized precipitation index (SPI) is used to monitor the evolution, frequency, and severity of droughts in the High Atlas basins (N'Fis, Ourika, Rhéraya, Zat, and R'dat), located south of Marrakech city. The spatiotemporal characterization of drought in these basins is performed by computing the SPI with precipitation spatially interpolated over the catchments. The Haouz plain, located downstream of these basins, is strongly dependent on water provided by the mountain ranges, as shown by the positive correlations between the normalized difference vegetation index (NDVI) in the plain and the 3, 6, and 12-month SPI in the High Atlas catchments. On the opposite, no significant correlations are found with piezometric levels of the Haouz groundwater due to intensified pumping for irrigation in the recent decades. A relative SPI index was computed to evaluate the climate change impacts on drought occurrence, based on the projected precipitation (2006-2100) from five high-resolution CORDEX regional climate simulations, under two emission scenarios (RCP 4.5 and RCP 8.5). These models show a decrease in precipitation towards the future up to - 65% compared to the historical period. In terms of drought events, the future projections indicate a strong increase in the frequency of SPI events below - 2, considered as severe drought condition.

Application and histology-driven refinement of active contour models to functional region and nerve delineation: towards a digital brainstem atlas

NASA Astrophysics Data System (ADS)

Patel, Nirmal; Sultana, Sharmin; Rashid, Tanweer; Krusienski, Dean; Audette, Michel A.

2015-03-01

This paper presents a methodology for the digital formatting of a printed atlas of the brainstem and the delineation of cranial nerves from this digital atlas. It also describes on-going work on the 3D resampling and refinement of the 2D functional regions and nerve contours. In MRI-based anatomical modeling for neurosurgery planning and simulation, the complexity of the functional anatomy entails a digital atlas approach, rather than less descriptive voxel or surface-based approaches. However, there is an insufficiency of descriptive digital atlases, in particular of the brainstem. Our approach proceeds from a series of numbered, contour-based sketches coinciding with slices of the brainstem featuring both closed and open contours. The closed contours coincide with functionally relevant regions, whereby our objective is to fill in each corresponding label, which is analogous to painting numbered regions in a paint-by-numbers kit. Any open contour typically coincides with a cranial nerve. This 2D phase is needed in order to produce densely labeled regions that can be stacked to produce 3D regions, as well as identifying the embedded paths and outer attachment points of cranial nerves. Cranial nerves are modeled using an explicit contour based technique called 1-Simplex. The relevance of cranial nerves modeling of this project is two-fold: i) this atlas will fill a void left by the brain segmentation communities, as no suitable digital atlas of the brainstem exists, and ii) this atlas is necessary to make explicit the attachment points of major nerves (except I and II) having a cranial origin. Keywords: digital atlas, contour models, surface models

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…

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

PubMed

Ferradal, Silvina L; Eggebrecht, Adam T; Hassanpour, Mahlega; Snyder, Abraham Z; Culver, Joseph P

2014-01-15

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available. Copyright © 2013. Published by Elsevier Inc.

Limb-darkening coefficients for the purpose of pulsation mode identification for A-F stars. .

NASA Astrophysics Data System (ADS)

Barban, C.; Goupil, M. J.; van't Veer-Menneret, C.; Garrido, R.; Heiter, U.; Kupka, F.

Limb-darkening coefficients are computed from a set of model atmospheres with: a solar chemical composition, 6000 K< Teff < 8500 K (Delta T_eff=250 K), 2.5 < logg < 4.5 (Delta log g=0.1) and a microturbulent velocity of 2 km/s. Convection is included assuming either the turbulent convection approach of \\citet{cm} or the classical mixing length prescription with alpha =0.5 and 1.25. Four limb-darkening laws have been used: quadratic, cubic, square root and the one of \\citet{cl}. We compare the ATLAS 9 intensities and the ones computed from these laws. We find that Claret's law is the best law for almost all the models, independently of the convection prescription used.

Oklahoma Center for High Energy Physics (OCHEP)

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

Nandi, S; Strauss, M J; Snow, J

2012-02-29

The DOE EPSCoR implementation grant, with the support from the State of Oklahoma and from the three universities, Oklahoma State University, University of Oklahoma and Langston University, resulted in establishing of the Oklahoma Center for High Energy Physics (OCHEP) in 2004. Currently, OCHEP continues to flourish as a vibrant hub for research in experimental and theoretical particle physics and an educational center in the State of Oklahoma. All goals of the original proposal were successfully accomplished. These include foun- dation of a new experimental particle physics group at OSU, the establishment of a Tier 2 computing facility for the Largemore » Hadron Collider (LHC) and Tevatron data analysis at OU and organization of a vital particle physics research center in Oklahoma based on resources of the three universities. OSU has hired two tenure-track faculty members with initial support from the grant funds. Now both positions are supported through OSU budget. This new HEP Experimental Group at OSU has established itself as a full member of the Fermilab D0 Collaboration and LHC ATLAS Experiment and has secured external funds from the DOE and the NSF. These funds currently support 2 graduate students, 1 postdoctoral fellow, and 1 part-time engineer. The grant initiated creation of a Tier 2 computing facility at OU as part of the Southwest Tier 2 facility, and a permanent Research Scientist was hired at OU to maintain and run the facility. Permanent support for this position has now been provided through the OU university budget. OCHEP represents a successful model of cooperation of several universities, providing the establishment of critical mass of manpower, computing and hardware resources. This led to increasing Oklahoma's impact in all areas of HEP, theory, experiment, and computation. The Center personnel are involved in cutting edge research in experimental, theoretical, and computational aspects of High Energy Physics with the research areas ranging from the search for new phenomena at the Fermilab Tevatron and the CERN Large Hadron Collider to theoretical modeling, computer simulation, detector development and testing, and physics analysis. OCHEP faculty members participating on the D0 collaboration at the Fermilab Tevatron and on the ATLAS collaboration at the CERN LHC have made major impact on the Standard Model (SM) Higgs boson search, top quark studies, B physics studies, and measurements of Quantum Chromodynamics (QCD) phenomena. The OCHEP Grid computing facility consists of a large computer cluster which is playing a major role in data analysis and Monte Carlo productions for both the D0 and ATLAS experiments. Theoretical efforts are devoted to new ideas in Higgs bosons physics, extra dimensions, neutrino masses and oscillations, Grand Unified Theories, supersymmetric models, dark matter, and nonperturbative quantum field theory. Theory members are making major contributions to the understanding of phenomena being explored at the Tevatron and the LHC. They have proposed new models for Higgs bosons, and have suggested new signals for extra dimensions, and for the search of supersymmetric particles. During the seven year period when OCHEP was partially funded through the DOE EPSCoR implementation grant, OCHEP members published over 500 refereed journal articles and made over 200 invited presentations at major conferences. The Center is also involved in education and outreach activities by offering summer research programs for high school teachers and college students, and organizing summer workshops for high school teachers, sometimes coordinating with the Quarknet programs at OSU and OU. The details of the Center can be found in http://ochep.phy.okstate.edu.« 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.

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.

Tumor growth model for atlas based registration of pathological brain MR images

NASA Astrophysics Data System (ADS)

Moualhi, Wafa; Ezzeddine, Zagrouba

2015-02-01

The motivation of this work is to register a tumor brain magnetic resonance (MR) image with a normal brain atlas. A normal brain atlas is deformed in order to take account of the presence of a large space occupying tumor. The method use a priori model of tumor growth assuming that the tumor grows in a radial way from a starting point. First, an affine transformation is used in order to bring the patient image and the brain atlas in a global correspondence. Second, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed combining a method derived from optical flow principles and a model for tumor growth (MTG). Results show that an automatic segmentation method of brain structures in the presence of large deformation can be provided.

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.

Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

NASA Technical Reports Server (NTRS)

Doyle, Monica; ONeil, Daniel A.; Christensen, Carissa B.

2005-01-01

The Advanced Technology Lifecycle Analysis System (ATLAS) is a decision support tool designed to aid program managers and strategic planners in determining how to invest technology research and development dollars. It is an Excel-based modeling package that allows a user to build complex space architectures and evaluate the impact of various technology choices. ATLAS contains system models, cost and operations models, a campaign timeline and a centralized technology database. Technology data for all system models is drawn from a common database, the ATLAS Technology Tool Box (TTB). The TTB provides a comprehensive, architecture-independent technology database that is keyed to current and future timeframes.

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.

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.

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.

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.

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.

Estimation of Mouse Organ Locations Through Registration of a Statistical Mouse Atlas With Micro-CT Images

PubMed Central

Stout, David B.; Chatziioannou, Arion F.

2012-01-01

Micro-CT is widely used in preclinical studies of small animals. Due to the low soft-tissue contrast in typical studies, segmentation of soft tissue organs from noncontrast enhanced micro-CT images is a challenging problem. Here, we propose an atlas-based approach for estimating the major organs in mouse micro-CT images. A statistical atlas of major trunk organs was constructed based on 45 training subjects. The statistical shape model technique was used to include inter-subject anatomical variations. The shape correlations between different organs were described using a conditional Gaussian model. For registration, first the high-contrast organs in micro-CT images were registered by fitting the statistical shape model, while the low-contrast organs were subsequently estimated from the high-contrast organs using the conditional Gaussian model. The registration accuracy was validated based on 23 noncontrast-enhanced and 45 contrast-enhanced micro-CT images. Three different accuracy metrics (Dice coefficient, organ volume recovery coefficient, and surface distance) were used for evaluation. The Dice coefficients vary from 0.45 ± 0.18 for the spleen to 0.90 ± 0.02 for the lungs, the volume recovery coefficients vary from for the liver to 1.30 ± 0.75 for the spleen, the surface distances vary from 0.18 ± 0.01 mm for the lungs to 0.72 ± 0.42 mm for the spleen. The registration accuracy of the statistical atlas was compared with two publicly available single-subject mouse atlases, i.e., the MOBY phantom and the DIGIMOUSE atlas, and the results proved that the statistical atlas is more accurate than the single atlases. To evaluate the influence of the training subject size, different numbers of training subjects were used for atlas construction and registration. The results showed an improvement of the registration accuracy when more training subjects were used for the atlas construction. The statistical atlas-based registration was also compared with the thin-plate spline based deformable registration, commonly used in mouse atlas registration. The results revealed that the statistical atlas has the advantage of improving the estimation of low-contrast organs. PMID:21859613

Computer-based learning in neuroanatomy: A longitudinal study of learning, transfer, and retention

NASA Astrophysics Data System (ADS)

Chariker, Julia H.

A longitudinal experiment was conducted to explore computer-based learning of neuroanatomy. Using a realistic 3D graphical model of neuroanatomy, and sections derived from the model, exploratory graphical tools were integrated into interactive computer programs so as to allow adaptive exploration. 72 participants learned either sectional anatomy alone or learned whole anatomy followed by sectional anatomy. Sectional anatomy was explored either in perceptually continuous animation or discretely, as in the use of an anatomical atlas. Learning was measured longitudinally to a high performance criterion. After learning, transfer to biomedical images and long-term retention was tested. Learning whole anatomy prior to learning sectional anatomy led to a more efficient learning experience. Learners demonstrated high levels of transfer from whole anatomy to sectional anatomy and from sectional anatomy to complex biomedical images. All learning groups demonstrated high levels of retention at 2--3 weeks.

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.

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

The Visible Heart® project and free-access website 'Atlas of Human Cardiac Anatomy'.

PubMed

Iaizzo, Paul A

2016-12-01

Pre- and post-evaluations of implantable cardiac devices require innovative and critical testing in all phases of the design process. The Visible Heart ® Project was successfully launched in 1997 and 3 years later the Atlas of Human Cardiac Anatomy website was online. The Visible Heart ® methodologies and Atlas website can be used to better understand human cardiac anatomy, disease states and/or to improve cardiac device design throughout the development process. To date, Visible ® Heart methodologies have been used to reanimate 75 human hearts, all considered non-viable for transplantation. The Atlas is a unique free-access website featuring novel images of functional and fixed human cardiac anatomies from >400 human heart specimens. Furthermore, this website includes education tutorials on anatomy, physiology, congenital heart disease and various imaging modalities. For instance, the Device Tutorial provides examples of commonly deployed devices that were present at the time of in vitro reanimation or were subsequently delivered, including: leads, catheters, valves, annuloplasty rings, leadless pacemakers and stents. Another section of the website displays 3D models of vasculature, blood volumes, and/or tissue volumes reconstructed from computed tomography (CT) and magnetic resonance images (MRI) of various heart specimens. A new section allows the user to interact with various heart models. Visible Heart ® methodologies have enabled our laboratory to reanimate 75 human hearts and visualize functional cardiac anatomies and device/tissue interfaces. The website freely shares all images, video clips and CT/MRI DICOM files in honour of the generous gifts received from donors and their families. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For Permissions, please email: journals.permissions@oup.com.

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.

Automatic labeling of MR brain images through extensible learning and atlas forests.

PubMed

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic atlas datasets and obtain accurate results. © 2017 American Association of Physicists in Medicine.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

PubMed

Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

2018-06-04

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

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

The Offshore New European Wind Atlas

NASA Astrophysics Data System (ADS)

Karagali, I.; Hahmann, A. N.; Badger, M.; Hasager, C.; Mann, J.

2017-12-01

The New European Wind Atlas (NEWA) is a joint effort of research agencies from eight European countries, co-funded under the ERANET Plus Program. The project is structured around two areas of work: development of dynamical downscaling methodologies and measurement campaigns to validate these methodologies, leading to the creation and publication of a European wind atlas in electronic form. This atlas will contain an offshore component extending 100 km from the European coasts. To achieve this, mesoscale models along with various observational datasets are utilised. Scanning lidars located at the coastline were used to compare the coastal wind gradient reproduced by the meso-scale model. Currently, an experimental campaign is occurring in the Baltic Sea, with a lidar located in a commercial ship sailing from Germany to Lithuania, thus covering the entire span of the south Baltic basin. In addition, satellite wind retrievals from scatterometers and Synthetic Aperture Radar (SAR) instruments were used to generate mean wind field maps and validate offshore modelled wind fields and identify the optimal model set-up parameters.The aim of this study is to compare the initial outputs from the offshore wind atlas produced by the Weather & Research Forecasting (WRF) model, still in pre-operational phase, and the METOP-A/B Advanced Scatterometer (ASCAT) wind fields, reprocessed to stress equivalent winds at 10m. Different experiments were set-up to evaluate the model sensitivity for the various domains covered by the NEWA offshore atlas. ASCAT winds were utilised to assess the performance of the WRF offshore atlases. In addition, ASCAT winds were used to create an offshore atlas covering the years 2007 to 2016, capturing the signature of various spatial wind features, such as channelling and lee effects from complex coastal topographical elements.

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

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

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.

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.

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.

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.

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.

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

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

Wang, Li; Gao, Yaozong; Shi, Feng

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segmentmore » CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT segmentation based on 15 patients.« less

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.

Fully Convolutional Neural Networks Improve Abdominal Organ Segmentation.

PubMed

Bobo, Meg F; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G; Hilmes, Melissa A; Landman, Bennett A

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities.

Fully convolutional neural networks improve abdominal organ segmentation

NASA Astrophysics Data System (ADS)

Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

Probabilistic atlas and geometric variability estimation to drive tissue segmentation.

PubMed

Xu, Hao; Thirion, Bertrand; Allassonnière, Stéphanie

2014-09-10

Computerized anatomical atlases play an important role in medical image analysis. While an atlas usually refers to a standard or mean image also called template, which presumably represents well a given population, it is not enough to characterize the observed population in detail. A template image should be learned jointly with the geometric variability of the shapes represented in the observations. These two quantities will in the sequel form the atlas of the corresponding population. The geometric variability is modeled as deformations of the template image so that it fits the observations. In this paper, we provide a detailed analysis of a new generative statistical model based on dense deformable templates that represents several tissue types observed in medical images. Our atlas contains both an estimation of probability maps of each tissue (called class) and the deformation metric. We use a stochastic algorithm for the estimation of the probabilistic atlas given a dataset. This atlas is then used for atlas-based segmentation method to segment the new images. Experiments are shown on brain T1 MRI datasets. Copyright © 2014 John Wiley & Sons, Ltd.

Thermal Testing and Model Correlation for Advanced Topographic Laser Altimeter Instrument (ATLAS)

NASA Technical Reports Server (NTRS)

Patel, Deepak

2016-01-01

The Advanced Topographic Laser Altimeter System (ATLAS) part of the Ice Cloud and Land Elevation Satellite 2 (ICESat-2) is an upcoming Earth Science mission focusing on the effects of climate change. The flight instrument passed all environmental testing at GSFC (Goddard Space Flight Center) and is now ready to be shipped to the spacecraft vendor for integration and testing. This topic covers the analysis leading up to the test setup for ATLAS thermal testing as well as model correlation to flight predictions. Test setup analysis section will include areas where ATLAS could not meet flight like conditions and what were the limitations. Model correlation section will walk through changes that had to be made to the thermal model in order to match test results. The correlated model will then be integrated with spacecraft model for on-orbit predictions.

System Architecture Modeling for Technology Portfolio Management using ATLAS

NASA Technical Reports Server (NTRS)

Thompson, Robert W.; O'Neil, Daniel A.

2006-01-01

Strategic planners and technology portfolio managers have traditionally relied on consensus-based tools, such as Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) in planning the funding of technology development. While useful to a certain extent, these tools are limited in the ability to fully quantify the impact of a technology choice on system mass, system reliability, project schedule, and lifecycle cost. The Advanced Technology Lifecycle Analysis System (ATLAS) aims to provide strategic planners a decision support tool for analyzing technology selections within a Space Exploration Architecture (SEA). Using ATLAS, strategic planners can select physics-based system models from a library, configure the systems with technologies and performance parameters, and plan the deployment of a SEA. Key parameters for current and future technologies have been collected from subject-matter experts and other documented sources in the Technology Tool Box (TTB). ATLAS can be used to compare the technical feasibility and economic viability of a set of technology choices for one SEA, and compare it against another set of technology choices or another SEA. System architecture modeling in ATLAS is a multi-step process. First, the modeler defines the system level requirements. Second, the modeler identifies technologies of interest whose impact on an SEA. Third, the system modeling team creates models of architecture elements (e.g. launch vehicles, in-space transfer vehicles, crew vehicles) if they are not already in the model library. Finally, the architecture modeler develops a script for the ATLAS tool to run, and the results for comparison are generated.

Monitoring the injured brain: registered, patient specific atlas models to improve accuracy of recovered brain saturation values

NASA Astrophysics Data System (ADS)

Clancy, Michael; Belli, Antonio; Davies, David; Lucas, Samuel J. E.; Su, Zhangjie; Dehghani, Hamid

2015-07-01

The subject of superficial contamination and signal origins remains a widely debated topic in the field of Near Infrared Spectroscopy (NIRS), yet the concept of using the technology to monitor an injured brain, in a clinical setting, poses additional challenges concerning the quantitative accuracy of recovered parameters. Using high density diffuse optical tomography probes, quantitatively accurate parameters from different layers (skin, bone and brain) can be recovered from subject specific reconstruction models. This study assesses the use of registered atlas models for situations where subject specific models are not available. Data simulated from subject specific models were reconstructed using the 8 registered atlas models implementing a regional (layered) parameter recovery in NIRFAST. A 3-region recovery based on the atlas model yielded recovered brain saturation values which were accurate to within 4.6% (percentage error) of the simulated values, validating the technique. The recovered saturations in the superficial regions were not quantitatively accurate. These findings highlight differences in superficial (skin and bone) layer thickness between the subject and atlas models. This layer thickness mismatch was propagated through the reconstruction process decreasing the parameter accuracy.

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.

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)

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.

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.

Breakup of Pangaea and plate kinematics of the central Atlantic and Atlas regions

NASA Astrophysics Data System (ADS)

Schettino, Antonio; Turco, Eugenio

2009-08-01

A new central Pangaea fit (type A) is proposed for the late Ladinian (230 Ma), together with a plate motions model for the subsequent phases of rifting, continental breakup and initial spreading in the central Atlantic. This model is based on: (1) a reinterpretation of the process of formation of the East Coast Magnetic Anomaly along the eastern margin of North America and the corresponding magnetic anomalies at the conjugate margins of northwest Africa and the Moroccan Meseta; (2) an analysis of major rifting events in the central Atlantic, Atlas and central Mediterranean and (3) a crustal balancing of the stretched margins of North America, Moroccan Meseta and northwest Africa. The process of fragmentation of central Pangaea can be described by three major phases spanning the time interval from the late Ladinian (230 Ma) to the Tithonian (147.7 Ma). During the first phase, from the late Ladinian (230 Ma) to the latest Rhaetian (200 Ma), rifting proceeded along the eastern margin of North America, the northwest African margin and the High, Saharan and Tunisian Atlas, determining the formation of a separate Moroccan microplate at the interface between Gondwana and Laurasia. During the second phase, from the latest Rhaetian (200 Ma) to the late Pliensbachian (185 Ma), oceanic crust started forming between the East Coast and Blake Spur magnetic anomalies, whereas the Morrocan Meseta simply continued to rift away from North America. During this time interval, the Atlas rift reached its maximum extent. Finally, the third phase, encompassing the time interval from the late Pliensbachian (185 Ma) to chron M21 (147.7 Ma), was triggered by the northward jump of the main plate boundary connecting the central Atlantic with the Tethys area. Therefore, as soon as rifting in the Atlas zone ceased, plate motion started along complex fault systems between Morocco and Iberia, whereas a rift/drift transition occurred in the northern segment of the central Atlantic, between Morocco and the conjugate margin of Nova Scotia. The inversion of the Atlas rift and the subsequent formation of the Atlas mountain belt occurred during the Oligocene-early Miocene time interval. In the central Atlantic, this event was associated with higher spreading rates of the ridge segments north of the Atlantis FZ. An estimate of 170 km of dextral offset of Morocco relative to northwest Africa, in the central Atlantic, is required by an analysis of marine magnetic anomalies. Five plate tectonic reconstructions and a computer animation are proposed to illustrate the late Triassic and Jurassic process of breakup of Pangaea in the central Atlantic and Atlas regions.

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.

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 .

Large-scale extraction of brain connectivity from the neuroscientific literature

PubMed Central

Richardet, Renaud; Chappelier, Jean-Cédric; Telefont, Martin; Hill, Sean

2015-01-01

Motivation: In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630 216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity. Results: NERs and connectivity extractors are evaluated against a manually annotated corpus. The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%. The resulting database contains over 4 million brain region mentions and over 100 000 (ABA) and 122 000 (BAMS) potential brain region connections. This database drastically accelerates connectivity literature review, by providing a centralized repository of connectivity data to neuroscientists. Availability and implementation: The resulting models are publicly available at github.com/BlueBrain/bluima. Contact: renaud.richardet@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25609795

Aqueduct: a methodology to measure and communicate global water risks

NASA Astrophysics Data System (ADS)

Gassert, Francis; Reig, Paul

2013-04-01

The Aqueduct Water Risk Atlas (Aqueduct) is a publicly available, global database and interactive tool that maps indicators of water related risks for decision makers worldwide. Aqueduct makes use of the latest geo-statistical modeling techniques to compute a composite index and translate the most recently available hydrological data into practical information on water related risks for companies, investors, and governments alike. Twelve global indicators are grouped into a Water Risk Framework designed in response to the growing concerns from private sector actors around water scarcity, water quality, climate change, and increasing demand for freshwater. The Aqueduct framework organizes indicators into three categories of risk that bring together multiple dimensions of water related risk into comprehensive aggregated scores and includes indicators of water stress, variability in supply, storage, flood, drought, groundwater, water quality and social conflict, addressing both spatial and temporal variation in water hazards. Indicators are selected based on relevance to water users, availability and robustness of global data sources, and expert consultation, and are collected from existing datasets or derived from a Global Land Data Assimilation System (GLDAS) based integrated water balance model. Indicators are normalized using a threshold approach, and composite scores are computed using a linear aggregation scheme that allows for dynamic weighting to capture users' unique exposure to water hazards. By providing consistent scores across the globe, the Aqueduct Water Risk Atlas enables rapid comparison across diverse aspects of water risk. Companies can use this information to prioritize actions, investors to leverage financial interest to improve water management, and governments to engage with the private sector to seek solutions for more equitable and sustainable water governance. The Aqueduct Water Risk Atlas enables practical applications of scientific data, helping non-expert audiences better understand and evaluate risks facing water users. This presentation will discuss the methodology used to combine the indicator values into aggregated risk scores and lessons learned from working with diverse audiences in academia, development institutions, and the public and private sectors.

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

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.

The Atlas of Physiology and Pathophysiology: Web-based multimedia enabled interactive simulations.

PubMed

Kofranek, Jiri; Matousek, Stanislav; Rusz, Jan; Stodulka, Petr; Privitzer, Pavol; Matejak, Marek; Tribula, Martin

2011-11-01

The paper is a presentation of the current state of development for the Atlas of Physiology and Pathophysiology (Atlas). Our main aim is to provide a novel interactive multimedia application that can be used for biomedical education where (a) simulations are combined with tutorials and (b) the presentation layer is simplified while the underlying complexity of the model is retained. The development of the Atlas required the cooperation of many professionals including teachers, system analysts, artists, and programmers. During the design of the Atlas, tools were developed that allow for component-based creation of simulation models, creation of interactive multimedia and their final coordination into a compact unit based on the given design. The Atlas is a freely available online application, which can help to explain the function of individual physiological systems and the causes and symptoms of their disorders. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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.

Creation of an atlas of filter positions for fluence field modulated CT

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

Szczykutowicz, Timothy P., E-mail: TSzczykutowicz@uwhealth.org; Hermus, James

2015-04-15

Purpose: 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 effectivelymore » span the infinite number of possible fluence profiles with minimal loss in performance. Methods: 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. Results: 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. Conclusions: 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.« less

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

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

Atlas - a data warehouse for integrative bioinformatics.

PubMed

Shah, Sohrab P; Huang, Yong; Xu, Tao; Yuen, Macaire M S; Ling, John; Ouellette, B F Francis

2005-02-21

We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: http://bioinformatics.ubc.ca/atlas/

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.

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

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.

Multi-Atlas Segmentation of Biomedical Images: A Survey

PubMed Central

Iglesias, Juan Eugenio; Sabuncu, Mert R.

2015-01-01

Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, Brandt, Menzel and Maurer Jr (2004), Klein, Mensh, Ghosh, Tourville and Hirsch (2005), and Heckemann, Hajnal, Aljabar, Rueckert and Hammers (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of “atlases” (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003 – 2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation. PMID:26201875

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.

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.

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.

A three-dimensional digital atlas of the dura mater based on human head MRI.

PubMed

Yang, Zhirong; Guo, Zhilin

2015-03-30

The goal of this paper was to design a three-dimensional (3D) digital dural atlas of the human brain for assisting neurosurgeons during the planning of an operation, medical research and teaching activities in neurosurgical anatomy. The 176 sagittal head magnetic resonance(MR) images of a 54-year-old female who suffered from the left posterior fossa tumor were processed and outlined, based on which a 3D dural model was created using the softwares of 3ds-max and Mimics. Then the model and images/anatomy photos were matched using the softwares of Z-brush and Photoshop to form the 3-D dural atlas. Dural anatomic photographs were needed to produce the 3D atlas in dural vault and skull base areas. The 3D dural atlas of the brain and related structures was successfully constructed using 73 dural delineations, the contours of dural model match very well on the dural structures of the original images in three orthogonal (axial, coronal and sagittal view) MR cross-sections. The atlas can be arbitrarily rotated and viewed from any direction. It can also be zoomed in and out directly using the zoom function. We successfully generated a 3D dural atlas of human brain, which can be used for repeated observation and research without limitations of time and shortage of corpses. In addition, the atlas has many potential applications in operative planning, surgical training, teaching activities, and so on. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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.

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

ShakeMap Atlas 2.0: an improved suite of recent historical earthquake ShakeMaps for global hazard analyses and loss model calibration

USGS Publications Warehouse

Garcia, D.; Mah, R.T.; Johnson, K.L.; Hearne, M.G.; Marano, K.D.; Lin, K.-W.; Wald, D.J.

2012-01-01

We introduce the second version of the U.S. Geological Survey ShakeMap Atlas, which is an openly-available compilation of nearly 8,000 ShakeMaps of the most significant global earthquakes between 1973 and 2011. This revision of the Atlas includes: (1) a new version of the ShakeMap software that improves data usage and uncertainty estimations; (2) an updated earthquake source catalogue that includes regional locations and finite fault models; (3) a refined strategy to select prediction and conversion equations based on a new seismotectonic regionalization scheme; and (4) vastly more macroseismic intensity and ground-motion data from regional agencies All these changes make the new Atlas a self-consistent, calibrated ShakeMap catalogue that constitutes an invaluable resource for investigating near-source strong ground-motion, as well as for seismic hazard, scenario, risk, and loss-model development. To this end, the Atlas will provide a hazard base layer for PAGER loss calibration and for the Earthquake Consequences Database within the Global Earthquake Model initiative.

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

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.

Developments in the ATLAS Tracking Software ahead of LHC Run 2

NASA Astrophysics Data System (ADS)

Styles, Nicholas; Bellomo, Massimiliano; Salzburger, Andreas; ATLAS Collaboration

2015-05-01

After a hugely successful first run, the Large Hadron Collider (LHC) is currently in a shut-down period, during which essential maintenance and upgrades are being performed on the accelerator. The ATLAS experiment, one of the four large LHC experiments has also used this period for consolidation and further developments of the detector and of its software framework, ahead of the new challenges that will be brought by the increased centre-of-mass energy and instantaneous luminosity in the next run period. This is of particular relevance for the ATLAS Tracking software, responsible for reconstructing the trajectory of charged particles through the detector, which faces a steep increase in CPU consumption due to the additional combinatorics of the high-multiplicity environment. The steps taken to mitigate this increase and stay within the available computing resources while maintaining the excellent performance of the tracking software in terms of the information provided to the physics analyses will be presented. Particular focus will be given to changes to the Event Data Model, replacement of the maths library, and adoption of a new persistent output format. The resulting CPU profiling results will be discussed, as well as the performance of the algorithms for physics processes under the expected conditions for the next LHC run.

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.

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.

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

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

Atlas – a data warehouse for integrative bioinformatics

PubMed Central

Shah, Sohrab P; Huang, Yong; Xu, Tao; Yuen, Macaire MS; Ling, John; Ouellette, BF Francis

2005-01-01

Background We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: PMID:15723693

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.

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.

Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.

PubMed

Bricq, S; Collet, Ch; Armspach, J P

2008-12-01

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.

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.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration.

PubMed

Ehrhardt, Jan; Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz

2011-02-01

Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory motion model is capable of providing valuable prior knowledge in many fields of applications. We present two examples of possible applications in radiation therapy and image guided diagnosis.

Reconstructing Buildings with Discontinuities and Roof Overhangs from Oblique Aerial Imagery

NASA Astrophysics Data System (ADS)

Frommholz, D.; Linkiewicz, M.; Meissner, H.; Dahlke, D.

2017-05-01

This paper proposes a two-stage method for the reconstruction of city buildings with discontinuities and roof overhangs from oriented nadir and oblique aerial images. To model the structures the input data is transformed into a dense point cloud, segmented and filtered with a modified marching cubes algorithm to reduce the positional noise. Assuming a monolithic building the remaining vertices are initially projected onto a 2D grid and passed to RANSAC-based regression and topology analysis to geometrically determine finite wall, ground and roof planes. If this should fail due to the presence of discontinuities the regression will be repeated on a 3D level by traversing voxels within the regularly subdivided bounding box of the building point set. For each cube a planar piece of the current surface is approximated and expanded. The resulting segments get mutually intersected yielding both topological and geometrical nodes and edges. These entities will be eliminated if their distance-based affiliation to the defining point sets is violated leaving a consistent building hull including its structural breaks. To add the roof overhangs the computed polygonal meshes are projected onto the digital surface model derived from the point cloud. Their shapes are offset equally along the edge normals with subpixel accuracy by detecting the zero-crossings of the second-order directional derivative in the gradient direction of the height bitmap and translated back into world space to become a component of the building. As soon as the reconstructed objects are finished the aerial images are further used to generate a compact texture atlas for visualization purposes. An optimized atlas bitmap is generated that allows perspectivecorrect multi-source texture mapping without prior rectification involving a partially parallel placement algorithm. Moreover, the texture atlases undergo object-based image analysis (OBIA) to detect window areas which get reintegrated into the building models. To evaluate the performance of the proposed method a proof-of-concept test on sample structures obtained from real-world data of Heligoland/Germany has been conducted. It revealed good reconstruction accuracy in comparison to the cadastral map, a speed-up in texture atlas optimization and visually attractive render results.

A spatiotemporal atlas of MR intensity, tissue probability and shape of the fetal brain with application to segmentation

PubMed Central

Habas, Piotr A.; Kim, Kio; Corbett-Detig, James M.; Rousseau, Francois; Glenn, Orit A.; Barkovich, A. James; Studholme, Colin

2010-01-01

Modeling and analysis of MR images of the developing human brain is a challenge due to rapid changes in brain morphology and morphometry. We present an approach to the construction of a spatiotemporal atlas of the fetal brain with temporal models of MR intensity, tissue probability and shape changes. This spatiotemporal model is created from a set of reconstructed MR images of fetal subjects with different gestational ages. Groupwise registration of manual segmentations and voxelwise nonlinear modeling allow us to capture the appearance, disappearance and spatial variation of brain structures over time. Applying this model to atlas-based segmentation, we generate age-specific MR templates and tissue probability maps and use them to initialize automatic tissue delineation in new MR images. The choice of model parameters and the final performance are evaluated using clinical MR scans of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. Experimental results indicate that quadratic temporal models can correctly capture growth-related changes in the fetal brain anatomy and provide improvement in accuracy of atlas-based tissue segmentation. PMID:20600970

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. 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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. 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A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobos, D.; Dobson, E.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Perez, S. Fernandez; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Parodi, A. Ferretto; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, J.; Fisher, M. J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Castillo, L. R. Flores; Bustos, A. C. Florez; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Torregrosa, E. Fullana; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gandrajula, R. P.; Gao, J.; Gao, Y. S.; Walls, F. M. Garay; Garberson, F.; García, C.; Navarro, J. E. García; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gianotti, F.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Glonti, G. L.; Goblirsch-Kolb, M.; Goddard, J. R.; Godfrey, J.; Godlewski, J.; Goeringer, C.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Fajardo, L. S. Gomez; Gonçalo, R.; Da Costa, J. Goncalves Pinto Firmino; Gonella, L.; de la Hoz, S. González; Parra, G. Gonzalez; Silva, M. L. Gonzalez; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Gozpinar, S.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, F.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Grebenyuk, O. G.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grishkevich, Y. V.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Groth-Jensen, J.; Grout, Z. J.; Grybel, K.; Guan, L.; Guescini, F.; Guest, D.; Gueta, O.; Guicheney, C.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Gunther, J.; Guo, J.; Gupta, S.; Gutierrez, P.; Ortiz, N. G. Gutierrez; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. 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Henriques; Henrot-Versille, S.; Hensel, C.; Herbert, G. H.; Jiménez, Y. Hernández; Herrberg-Schubert, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hofmann, J. I.; Hohlfeld, M.; Holmes, T. R.; Hong, T. M.; van Huysduynen, L. Hooft; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Hurwitz, M.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikematsu, K.; Ikeno, M.; Iliadis, D.; Ilic, N.; Inamaru, Y.; Ince, T.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Quiles, A. Irles; Isaksson, C.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ponce, J. M. Iturbe; Ivashin, A. V.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, J. N.; Jackson, M.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jakubek, J.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansen, H.; Janssen, J.; Janus, M.; Jarlskog, G.; Javůrek, T.; Jeanty, L.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Ji, H.; Ji, W.; Jia, J.; Jiang, Y.; Belenguer, M. Jimenez; Jin, S.; Jinaru, A.; Jinnouchi, O.; Joergensen, M. D.; Johansson, K. E.; Johansson, P.; Johns, K. 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A.; Su, D.; Su, J.; Subramania, H. S.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Swedish, S.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tamsett, M. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tani, K.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teischinger, F. A.; Castanheira, M. Teixeira Dias; Teixeira-Dias, P.; Temming, K. K.; Kate, H. Ten; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thoma, S.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Topilin, N. D.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Tran, H. L.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Urbaniec, D.; Urquijo, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Gallego, E. Valladolid; Vallecorsa, S.; Ferrer, J. A. Valls; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; Van Der Leeuw, R.; van der Ster, D.; Eldik, N. van; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; 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.; Vigne, R.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Virzi, J.; Vitells, O.; Vivarelli, I.; Vaque, F. Vives; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; Radziewski, H. von; von Toerne, E.; Vorobel, V.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Anh, T. Vu; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, X.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watanabe, I.; 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.; Weigell, P.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; 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.; Wilkens, H. G.; Will, J. Z.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wittig, T.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wright, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xiao, M.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamada, M.; Yamaguchi, H.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yanush, S.; Yao, L.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yen, A. L.; Yildirim, E.; Yilmaz, M.; Yoosoofmiya, R.; 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.; Yurkewicz, A.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zaytsev, A.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; della Porta, G. Zevi; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, X.; Zhang, Z.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, L.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; 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.

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.

Primal/dual linear programming and statistical atlases for cartilage segmentation.

PubMed

Glocker, Ben; Komodakis, Nikos; Paragios, Nikos; Glaser, Christian; Tziritas, Georgios; Navab, Nassir

2007-01-01

In this paper we propose a novel approach for automatic segmentation of cartilage using a statistical atlas and efficient primal/dual linear programming. To this end, a novel statistical atlas construction is considered from registered training examples. Segmentation is then solved through registration which aims at deforming the atlas such that the conditional posterior of the learned (atlas) density is maximized with respect to the image. Such a task is reformulated using a discrete set of deformations and segmentation becomes equivalent to finding the set of local deformations which optimally match the model to the image. We evaluate our method on 56 MRI data sets (28 used for the model and 28 used for evaluation) and obtain a fully automatic segmentation of patella cartilage volume with an overlap ratio of 0.84 with a sensitivity and specificity of 94.06% and 99.92%, respectively.

Toward the holistic, reference, and extendable atlas of the human brain, head, and neck.

PubMed

Nowinski, Wieslaw L

2015-06-01

Despite numerous efforts, a fairly complete (holistic) anatomical model of the whole, normal, adult human brain, which is required as the reference in brain studies and clinical applications, has not yet been constructed. Our ultimate objective is to build this kind of atlas from advanced in vivo imaging. This work presents the taxonomy of our currently developed brain atlases and addresses the design, content, functionality, and current results in the holistic atlas development as well as atlas usefulness and future directions. We have developed to date 35 commercial brain atlases (along with numerous research prototypes), licensed to 63 companies and institutions, and made available to medical societies, organizations, medical schools, and individuals. These atlases have been applied in education, research, and clinical applications. Hundreds of thousands of patients have been treated by using our atlases. Based on this experience, the first version of the holistic and reference atlas of the brain, head, and neck has been developed and made available. The atlas has been created from multispectral 3 and 7 Tesla and high-resolution CT in vivo scans. It is fully 3D, scalable, interactive, and highly detailed with about 3,000 labeled components. This atlas forms a foundation for the development of a multi-level molecular, cellular, anatomical, physiological, and behavioral brain atlas platform.

Whole abdominal wall segmentation using augmented active shape models (AASM) with multi-atlas label fusion and level set

NASA Astrophysics Data System (ADS)

Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

2016-03-01

The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes.

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.

Update of the Polar SWIFT model for polar stratospheric ozone loss (Polar SWIFT version 2)

NASA Astrophysics Data System (ADS)

Wohltmann, Ingo; Lehmann, Ralph; Rex, Markus

2017-07-01

The Polar SWIFT model is a fast scheme for calculating the chemistry of stratospheric ozone depletion in polar winter. It is intended for use in global climate models (GCMs) and Earth system models (ESMs) to enable the simulation of mutual interactions between the ozone layer and climate. To date, climate models often use prescribed ozone fields, since a full stratospheric chemistry scheme is computationally very expensive. Polar SWIFT is based on a set of coupled differential equations, which simulate the polar vortex-averaged mixing ratios of the key species involved in polar ozone depletion on a given vertical level. These species are O3, chemically active chlorine (ClOx), HCl, ClONO2 and HNO3. The only external input parameters that drive the model are the fraction of the polar vortex in sunlight and the fraction of the polar vortex below the temperatures necessary for the formation of polar stratospheric clouds. Here, we present an update of the Polar SWIFT model introducing several improvements over the original model formulation. In particular, the model is now trained on vortex-averaged reaction rates of the ATLAS Chemistry and Transport Model, which enables a detailed look at individual processes and an independent validation of the different parameterizations contained in the differential equations. The training of the original Polar SWIFT model was based on fitting complete model runs to satellite observations and did not allow for this. A revised formulation of the system of differential equations is developed, which closely fits vortex-averaged reaction rates from ATLAS that represent the main chemical processes influencing ozone. In addition, a parameterization for the HNO3 change by denitrification is included. The rates of change of the concentrations of the chemical species of the Polar SWIFT model are purely chemical rates of change in the new version, whereas in the original Polar SWIFT model, they included a transport effect caused by the original training on satellite data. Hence, the new version allows for an implementation into climate models in combination with an existing stratospheric transport scheme. Finally, the model is now formulated on several vertical levels encompassing the vertical range in which polar ozone depletion is observed. The results of the Polar SWIFT model are validated with independent Microwave Limb Sounder (MLS) satellite observations and output from the original detailed chemistry model of ATLAS.

Dark matter interpretations of ATLAS searches for the electroweak production of supersymmetric particles in s = 8 $$ \\sqrt{s}=8 $$ TeV proton-proton collisions

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

Aaboud, M.; Aad, G.; Abbott, B.

2016-09-01

A selection of searches by the ATLAS experiment at the LHC for the electroweak production of SUSY particles are used to study their impact on the constraints on dark matter candidates. The searches use 20 fb-1 of proton-proton collision data at s√=8s=8 TeV. A likelihood-driven scan of a five-dimensional effective model focusing on the gaugino-higgsino and Higgs sector of the phenomenological minimal supersymmetric Standard Model is performed. This scan uses data from direct dark matter detection experiments, the relic dark matter density and precision flavour physics results. Further constraints from the ATLAS Higgs mass measurement and SUSY searches at LEPmore » are also applied. A subset of models selected from this scan are used to assess the impact of the selected ATLAS searches in this five-dimensional parameter space. These ATLAS searches substantially impact those models for which the mass m(χ~01)m(χ~10) of the lightest neutralino is less than 65 GeV, excluding 86% of such models. The searches have limited impact on models with larger m(χ~01)m(χ~10) due to either heavy electroweakinos or compressed mass spectra where the mass splittings between the produced particles and the lightest supersymmetric particle is small.« less

Dark matter interpretations of ATLAS searches for the electroweak production of supersymmetric particles in $$ \\sqrt{s}=8 $$ TeV proton-proton collisions

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2016-09-30

A selection of searches by the ATLAS experiment at the LHC for the electroweak production of SUSY particles are used to study their impact on the constraints on dark matter candidates. The searches use 20 fb -1 of proton-proton collision data at √s=8 TeV. A likelihood-driven scan of a five-dimensional effective model focusing on the gaugino-higgsino and Higgs sector of the phenomenological minimal supersymmetric Standard Model is performed. This scan uses data from direct dark matter detection experiments, the relic dark matter density and precision flavour physics results. Further constraints from the ATLAS Higgs mass measurement and SUSY searches at LEP are also applied. A subset of models selected from this scan are used to assess the impact of the selected ATLAS searches in this five-dimensional parameter space. These ATLAS searches substantially impact those models for which the mass m(more » $$\\tilde{χ}$$$0\\atop{1}$$) of the lightest neutralino is less than 65 GeV, excluding 86% of such models. The searches have limited impact on models with larger m($$\\tilde{χ}$$$0\\atop{1}$$) due to either heavy electroweakinos or compressed mass spectra where the mass splittings between the produced particles and the lightest supersymmetric particle is small.« less

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.

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.

New limb-darkening coefficients for modeling binary star light curves

NASA Technical Reports Server (NTRS)

Van Hamme, W.

1993-01-01

We present monochromatic, passband-specific, and bolometric limb-darkening coefficients for a linear as well as nonlinear logarithmic and square root limb-darkening laws. These coefficients, including the bolometric ones, are needed when modeling binary star light curves with the latest version of the Wilson-Devinney light curve progam. We base our calculations on the most recent ATLAS stellar atmosphere models for solar chemical composition stars with a wide range of effective temperatures and surface gravitites. We examine how well various limb-darkening approximations represent the variation of the emerging specific intensity across a stellar surface as computed according to the model. For binary star light curve modeling purposes, we propose the use of a logarithmic or a square root law. We design our tables in such a manner that the relative quality of either law with respect to another can be easily compared. Since the computation of bolometric limb-darkening coefficients first requires monochromatic coefficients, we also offer tables of these coefficients (at 1221 wavelength values between 9.09 nm and 160 micrometer) and tables of passband-specific coefficients for commonly used photometric filters.

Automatic tissue segmentation of head and neck MR images for hyperthermia treatment planning

NASA Astrophysics Data System (ADS)

Fortunati, Valerio; Verhaart, René F.; Niessen, Wiro J.; Veenland, Jifke F.; Paulides, Margarethus M.; van Walsum, Theo

2015-08-01

A hyperthermia treatment requires accurate, patient-specific treatment planning. This planning is based on 3D anatomical models which are generally derived from computed tomography. Because of its superior soft tissue contrast, magnetic resonance imaging (MRI) information can be introduced to improve the quality of these 3D patient models and therefore the treatment planning itself. Thus, we present here an automatic atlas-based segmentation algorithm for MR images of the head and neck. Our method combines multiatlas local weighting fusion with intensity modelling. The accuracy of the method was evaluated using a leave-one-out cross validation experiment over a set of 11 patients for which manual delineation were available. The accuracy of the proposed method was high both in terms of the Dice similarity coefficient (DSC) and the 95th percentile Hausdorff surface distance (HSD) with median DSC higher than 0.8 for all tissues except sclera. For all tissues, except the spine tissues, the accuracy was approaching the interobserver agreement/variability both in terms of DSC and HSD. The positive effect of adding the intensity modelling to the multiatlas fusion decreased when a more accurate atlas fusion method was used. Using the proposed approach we improved the performance of the approach previously presented for H&N hyperthermia treatment planning, making the method suitable for clinical application.

Statistical shape modeling of human cochlea: alignment and principal component analysis

NASA Astrophysics Data System (ADS)

Poznyakovskiy, Anton A.; Zahnert, Thomas; Fischer, Björn; Lasurashvili, Nikoloz; Kalaidzidis, Yannis; Mürbe, Dirk

2013-02-01

The modeling of the cochlear labyrinth in living subjects is hampered by insufficient resolution of available clinical imaging methods. These methods usually provide resolutions higher than 125 μm. This is too crude to record the position of basilar membrane and, as a result, keep apart even the scala tympani from other scalae. This problem could be avoided by the means of atlas-based segmentation. The specimens can endure higher radiation loads and, conversely, provide better-resolved images. The resulting surface can be used as the seed for atlas-based segmentation. To serve this purpose, we have developed a statistical shape model (SSM) of human scala tympani based on segmentations obtained from 10 μCT image stacks. After segmentation, we aligned the resulting surfaces using Procrustes alignment. This algorithm was slightly modified to accommodate single models with nodes which do not necessarily correspond to salient features and vary in number between models. We have established correspondence by mutual proximity between nodes. Rather than using the standard Euclidean norm, we have applied an alternative logarithmic norm to improve outlier treatment. The minimization was done using BFGS method. We have also split the surface nodes along an octree to reduce computation cost. Subsequently, we have performed the principal component analysis of the training set with Jacobi eigenvalue algorithm. We expect the resulting method to help acquiring not only better understanding in interindividual variations of cochlear anatomy, but also a step towards individual models for pre-operative diagnostics prior to cochlear implant insertions.

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.

A Deformable Atlas of the Laboratory Mouse

PubMed Central

Wang, Hongkai; Stout, David B.; Chatziioannou, Arion F.

2015-01-01

Purpose This paper presents a deformable mouse atlas of the laboratory mouse anatomy. This atlas is fully articulated and can be positioned into arbitrary body poses. The atlas can also adapt body weight by changing body length and fat amount. Procedures A training set of 103 micro-CT images was used to construct the atlas. A cage-based deformation method was applied to realize the articulated pose change. The weight-related body deformation was learned from the training set using a linear regression method. A conditional Gaussian model and thin-plate spline mapping were used to deform the internal organs following the changes of pose and weight. Results The atlas was deformed into different body poses and weights, and the deformation results were more realistic compared to the results achieved with other mouse atlases. The organ weights of this atlas matched well with the measurements of real mouse organ weights. This atlas can also be converted into voxelized images with labeled organs, pseudo CT images and tetrahedral mesh for phantom studies. Conclusions With the unique ability of articulated pose and weight changes, the deformable laboratory mouse atlas can become a valuable tool for preclinical image analysis. PMID:25049072

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

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.

Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model

PubMed Central

Gooya, Ali; Pohl, Kilian M.; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR ) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth. PMID:21995070

Joint segmentation and deformable registration of brain scans guided by a tumor growth model.

PubMed

Gooya, Ali; Pohl, Kilian M; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth.

Probabilistic liver atlas construction.

PubMed

Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E

2017-01-13

Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

Atlas-based system for functional neurosurgery

NASA Astrophysics Data System (ADS)

Nowinski, Wieslaw L.; Yeo, Tseng T.; Yang, Guo L.; Dow, Douglas E.

1997-05-01

This paper addresses the development of an atlas-based system for preoperative functional neurosurgery planning and training, intraoperative support and postoperative analysis. The system is based on Atlas of Stereotaxy of the Human Brain by Schaltenbrand and Wahren used for interactive segmentation and labeling of clinical data in 2D/3D, and for assisting stereotactic targeting. The atlas microseries are digitized, enhanced, segmented, labeled, aligned and organized into mutually preregistered atlas volumes 3D models of the structures are also constructed. The atlas may be interactively registered with the actual patient's data. Several other features are also provided including data reformatting, visualization, navigation, mensuration, and stereotactic path display and editing in 2D/3D. The system increases the accuracy of target definition, reduces the time of planning and time of the procedure itself. It also constitutes a research platform for the construction of more advanced neurosurgery supporting tools and brain atlases.

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.

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.

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.

Advanced Training in Laparoscopic Abdominal Surgery (Atlas): A Systematic Review

PubMed Central

Beyer-Berjot, Laura; Palter, Vanessa; Grantcharov, Teodor; Aggarwal, Rajesh

2014-01-01

Background Simulation has widely spread this last decade, especially in laparoscopic surgery, and training out of the operating room (OR) has proven its positive impact on basic skills during real laparoscopic procedures. However, few articles dealing with advanced training in laparoscopic abdominal surgery (ATLAS) have been published so far. Such training may reduce learning curves in the OR for junior surgeons with limited access to complex laparoscopic procedures as a primary operator. Methods Two reviewers, using MEDLINE, EMBASE, and The Cochrane Library, conducted a systematic research with combinations of the following keywords: (teaching OR education OR computer simulation) AND laparoscopy AND (gastric OR stomach OR colorectal OR colon OR rectum OR small bowel OR liver OR spleen OR pancreas OR advanced surgery OR advanced procedure OR complex procedure). Additional studies were searched in the reference lists of all included articles. Results Fifty-four original studies were retrieved. Their level of evidence was low: most of the studies were case series, one fifth purely descriptive, and there were 8 randomized trials. Porcine models and video trainers, as well as gastric and colorectal procedures were mainly assessed. The retrieved studies showed some encouraging trends in terms of trainees' satisfaction, improvement after training (but mainly on the training tool itself). Some tools have been proven to be construct-valid. Conclusions Higher quality studies are required to appraise ATLAS educational value. PMID:24947643

Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.

PubMed

Torrado-Carvajal, Angel; Herraiz, Joaquin L; Hernandez-Tamames, Juan A; San Jose-Estepar, Raul; Eryaman, Yigitcan; Rozenholc, Yves; Adalsteinsson, Elfar; Wald, Lawrence L; Malpica, Norberto

2016-04-01

MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume. The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms. The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers. It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. © 2015 Wiley Periodicals, Inc.

Second NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

NASA Technical Reports Server (NTRS)

ONeil, D. A.; Mankins, J. C.; Christensen, C. B.; Gresham, E. C.

2005-01-01

The Advanced Technology Lifecycle Analysis System (ATLAS), a spreadsheet analysis tool suite, applies parametric equations for sizing and lifecycle cost estimation. Performance, operation, and programmatic data used by the equations come from a Technology Tool Box (TTB) database. In this second TTB Technical Interchange Meeting (TIM), technologists, system model developers, and architecture analysts discussed methods for modeling technology decisions in spreadsheet models, identified specific technology parameters, and defined detailed development requirements. This Conference Publication captures the consensus of the discussions and provides narrative explanations of the tool suite, the database, and applications of ATLAS within NASA s changing environment.

Meter-scale Urban Land Cover Mapping for EPA EnviroAtlas Using Machine Learning and OBIA Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.

2013-12-01

US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.

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

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.

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.

An Update on the VAMOS Extremes Working Group Activities

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Cavalcanti, Iracema

2011-01-01

We review here the progress of the Variability of the American MOnsoon Systems (VAMOS) extremes working group since it was formed in February of 2010. The goals of the working group are to 1) develop an atlas of warm-season extremes over the Americas, 2) evaluate existing and planned simulations, and 3) suggest new model runs to address mechanisms and predictability of extremes. Substantial progress has been made in the development of an extremes atlas based on gridded observations and several reanalysis products including Modern Era Retrospective-Analysis for Research and Applications (MERRA) and Climate Forecast System Reanalysis (CFSR). The status of the atlas, remaining issues and plans for its expansion to include model data will be discussed. This includes the possibility of adding a companion atlas based on station observations based on the software developed under the World Climate Research Programme (WCRP) Expert Team on Climate Change. Detection and Indices (ETCCDI) activity. We will also review progress on relevant research and plans for the use and validation of the atlas results.

Boeing CST-100 Starliner/ULA Atlas V Wind Tunnel Demonstration

NASA Image and Video Library

2016-10-13

An engineer works with a model of a United Launch Alliance Atlas V rocket with a Boeing CST-100 Starliner capsule inside a wind tunnel at NASA's Ames Research Center in California. The Starliner/Atlas V system is under development by Boeing and ULA in partnership with NASA's Commercial Crew Program to launch astronauts to the International Space Station.

Experimental and code simulation of a station blackout scenario for APR1400 with test facility ATLAS and MARS code

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

Yu, X. G.; Kim, Y. S.; Choi, K. Y.

2012-07-01

A SBO (station blackout) experiment named SBO-01 was performed at full-pressure IET (Integral Effect Test) facility ATLAS (Advanced Test Loop for Accident Simulation) which is scaled down from the APR1400 (Advanced Power Reactor 1400 MWe). In this study, the transient of SBO-01 is discussed and is subdivided into three phases: the SG fluid loss phase, the RCS fluid loss phase, and the core coolant depletion and core heatup phase. In addition, the typical phenomena in SBO-01 test - SG dryout, natural circulation, core coolant boiling, the PRZ full, core heat-up - are identified. Furthermore, the SBO-01 test is reproduced bymore » the MARS code calculation with the ATLAS model which represents the ATLAS test facility. The experimental and calculated transients are then compared and discussed. The comparison reveals there was malfunction of equipments: the SG leakage through SG MSSV and the measurement error of loop flow meter. As the ATLAS model is validated against the experimental results, it can be further employed to investigate the other possible SBO scenarios and to study the scaling distortions in the ATLAS. (authors)« less

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.

Performing label-fusion-based segmentation using multiple automatically generated templates.

PubMed

Chakravarty, M Mallar; Steadman, Patrick; van Eede, Matthijs C; Calcott, Rebecca D; Gu, Victoria; Shaw, Philip; Raznahan, Armin; Collins, D Louis; Lerch, Jason P

2013-10-01

Classically, model-based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi-atlas-based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel-by-voxel label-voting procedure. In this article, we demonstrate how the multi-atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high-resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model-based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi-atlas label-fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively). Copyright © 2012 Wiley Periodicals, Inc.

Grid-Enabled High Energy Physics Research using a Beowulf Cluster

NASA Astrophysics Data System (ADS)

Mahmood, Akhtar

2005-04-01

At Edinboro University of Pennsylvania, we have built a 8-node 25 Gflops Beowulf Cluster with 2.5 TB of disk storage space to carry out grid-enabled, data-intensive high energy physics research for the ATLAS experiment via Grid3. We will describe how we built and configured our Cluster, which we have named the Sphinx Beowulf Cluster. We will describe the results of our cluster benchmark studies and the run-time plots of several parallel application codes. Once fully functional, the Cluster will be part of Grid3[www.ivdgl.org/grid3]. The current ATLAS simulation grid application, models the entire physical processes from the proton anti-proton collisions and detector's response to the collision debri through the complete reconstruction of the event from analyses of these responses. The end result is a detailed set of data that simulates the real physical collision event inside a particle detector. Grid is the new IT infrastructure for the 21^st century science -- a new computing paradigm that is poised to transform the practice of large-scale data-intensive research in science and engineering. The Grid will allow scientist worldwide to view and analyze huge amounts of data flowing from the large-scale experiments in High Energy Physics. The Grid is expected to bring together geographically and organizationally dispersed computational resources, such as CPUs, storage systems, communication systems, and data sources.

GLISTR: Glioma Image Segmentation and Registration

PubMed Central

Pohl, Kilian M.; Bilello, Michel; Cirillo, Luigi; Biros, George; Melhem, Elias R.; Davatzikos, Christos

2015-01-01

We present a generative approach for simultaneously registering a probabilistic atlas of a healthy population to brain magnetic resonance (MR) scans showing glioma and segmenting the scans into tumor as well as healthy tissue labels. The proposed method is based on the expectation maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the original atlas into one with tumor and edema adapted to best match a given set of patient’s images. The modified atlas is registered into the patient space and utilized for estimating the posterior probabilities of various tissue labels. EM iteratively refines the estimates of the posterior probabilities of tissue labels, the deformation field and the tumor growth model parameters. Hence, in addition to segmentation, the proposed method results in atlas registration and a low-dimensional description of the patient scans through estimation of tumor model parameters. We validate the method by automatically segmenting 10 MR scans and comparing the results to those produced by clinical experts and two state-of-the-art methods. The resulting segmentations of tumor and edema outperform the results of the reference methods, and achieve a similar accuracy from a second human rater. We additionally apply the method to 122 patients scans and report the estimated tumor model parameters and their relations with segmentation and registration results. Based on the results from this patient population, we construct a statistical atlas of the glioma by inverting the estimated deformation fields to warp the tumor segmentations of patients scans into a common space. PMID:22907965

Symbolic modeling of human anatomy for visualization and simulation

NASA Astrophysics Data System (ADS)

Pommert, Andreas; Schubert, Rainer; Riemer, Martin; Schiemann, Thomas; Tiede, Ulf; Hoehne, Karl H.

1994-09-01

Visualization of human anatomy in a 3D atlas requires both spatial and more abstract symbolic knowledge. Within our 'intelligent volume' model which integrates these two levels, we developed and implemented a semantic network model for describing human anatomy. Concepts for structuring (abstraction levels, domains, views, generic and case-specific modeling, inheritance) are introduced. Model, tools for generation and exploration and applications in our 3D anatomical atlas are presented and discussed.

Atlas of low-mass young stellar object disks from mid-infrared interferometry

NASA Astrophysics Data System (ADS)

Varga, J.; Ábrahám, P.; Ratzka, Th.; Menu, J.; Gabányi, K.; Kóspál, Á.; van Boekel, R.; Mosoni, L.; Henning, Th.

We present our approach of visibility modeling of disks around low-mass (< 2 M ⊙) young stellar objects (YSOs). We compiled an atlas based on mid-infrared interferometric observations from the MIDI instrument at the VLTI. We use three different models to fit the data. These models allow us to determine overall sizes (and the extent of the inner gaps) of the modeled circumstellar disks.

Constraints on the Velocity Structure and Accommodation of Shortening in the Atlas Mountains (Morocco) from Travel-Time Inversion of Refraction/Wide Angle Reflection Seismic Data

NASA Astrophysics Data System (ADS)

Ayarza, P.; Carbonell, R.; Palomeras, I.; Levander, A.; Teixell, A.; Zelt, C. A.; Kchikach, A.

2013-12-01

The Atlas Mountains are an intra-continental Cenozoic orogenic belt located at the southern edge of the diffuse plate boundary zone separating Africa and Europe. Its western part, the Moroccan Atlas, has long been under the scope of geoscientists investigating the origin of its high topography, locally exceeding 4000 m. Geological studies indicate that this mountain belt has experienced low to moderate shortening (<24% from balanced sections) and that topography and shortening do not keep a direct relationship. Forward modelling of the SIMA (Seismic Imaging of the Moroccan Atlas) refraction/wide angle reflection seismic data suggests that the total orogenic shortening, is resolved at depth with a Moho offset and a limited lower crust duplication that defines a 40 km-deep root in the northern part of the central High Atlas. However, the shortening accomodated by this feature (50 km) exceeds that estimated with surface data, and the position of the root appears to the north of the highest topography. In order to achieve a better definition of the crust/mantle boundary and to outline a tectonic model more coherent with surface data, we have used the RAYINVR code to carry out travel-time inversion of the SIMA data set. Inversion results depict a small shift to the south of the crustal root, formerly positioned in the northern part of the High Atlas, and define a thrusted mantle wedge. A limited crustal imbrication also appears in the Middle Atlas. The new velocity model implies complex ray trajectories but provides a better travel-time fit between the observed and the calculated data. Also, the amount of shortening implied by the this model is in agreement with that estimated from geological cross-sections. The final crustal thickness, as yet not exceeding 40 km in the root zone and less than 35 km elsewhere, still implies the need of a significant contribution from the mantle to support the topography of the Atlas mountains

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.

Synthetic event-related potentials: a computational bridge between neurolinguistic models and experiments.

PubMed

Barrès, Victor; Simons, Arthur; Arbib, Michael

2013-01-01

Our previous work developed Synthetic Brain Imaging to link neural and schema network models of cognition and behavior to PET and fMRI studies of brain function. We here extend this approach to Synthetic Event-Related Potentials (Synthetic ERP). Although the method is of general applicability, we focus on ERP correlates of language processing in the human brain. The method has two components: Phase 1: To generate cortical electro-magnetic source activity from neural or schema network models; and Phase 2: To generate known neurolinguistic ERP data (ERP scalp voltage topographies and waveforms) from putative cortical source distributions and activities within a realistic anatomical model of the human brain and head. To illustrate the challenges of Phase 2 of the methodology, spatiotemporal information from Friederici's 2002 model of auditory language comprehension was used to define cortical regions and time courses of activation for implementation within a forward model of ERP data. The cortical regions from the 2002 model were modeled using atlas-based masks overlaid on the MNI high definition single subject cortical mesh. The electromagnetic contribution of each region was modeled using current dipoles whose position and orientation were constrained by the cortical geometry. In linking neural network computation via EEG forward modeling to empirical results in neurolinguistics, we emphasize the need for neural network models to link their architecture to geometrically sound models of the cortical surface, and the need for conceptual models to refine and adopt brain-atlas based approaches to allow precise brain anchoring of their modules. The detailed analysis of Phase 2 sets the stage for a brief introduction to Phase 1 of the program, including the case for a schema-theoretic approach to language production and perception presented in detail elsewhere. Unlike Dynamic Causal Modeling (DCM) and Bojak's mean field model, Synthetic ERP builds on models of networks that mediate the relation between the brain's inputs, outputs, and internal states in executing a specific task. The neural networks used for Synthetic ERP must include neuroanatomically realistic placement and orientation of the cortical pyramidal neurons. These constraints pose exciting challenges for future work in neural network modeling that is applicable to systems and cognitive neuroscience. Copyright © 2012 Elsevier Ltd. All rights reserved.

EnviroAtlas - Woodbine, IA - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1 block group in Woodbine, Iowa. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Pittsburgh, PA - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1,089 block groups in Pittsburgh, Pennsylvania. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Portland, OR - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1176 block groups in Portland, Oregon. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (http:/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).

EnviroAtlas - Fresno, CA - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 405 block groups in Fresno, California. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - New Bedford, MA - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 128 block group in New Bedford, Massachusetts. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Tampa, FL - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1,833 block groups in Tampa Bay, Florida. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Minneapolis/St. Paul, MN - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1,772 block groups in Minneapolis/St. Paul, Minnesota. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Cleveland, OH - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1,442 block groups in Cleveland, Ohio. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Milwaukee, WI - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 1,175 block groups in Milwaukee, Wisconsin. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Portland, ME - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 146 block groups in Portland, Maine. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Memphis, TN - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 703 block groups in Memphis, Tennessee. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

EnviroAtlas - Green Bay, WI - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 155 block groups in Green Bay, Wisconsin. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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 ).

EnviroAtlas - Austin, TX - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset presents environmental benefits of the urban forest in 750 block groups in Austin, Texas. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service 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).

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.

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.

Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

NASA Astrophysics Data System (ADS)

Liu, Mengyuan; Seshamani, Sharmishtaa; Harrylock, Lisa; Kitsch, Averi; Miller, Steven; Chau, Van; Poskitt, Kenneth; Rousseau, Francois; Studholme, Colin

2014-03-01

One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

EMAP and EMAGE: a framework for understanding spatially organized data.

PubMed

Baldock, Richard A; Bard, Jonathan B L; Burger, Albert; Burton, Nicolas; Christiansen, Jeff; Feng, Guanjie; Hill, Bill; Houghton, Derek; Kaufman, Matthew; Rao, Jianguo; Sharpe, James; Ross, Allyson; Stevenson, Peter; Venkataraman, Shanmugasundaram; Waterhouse, Andrew; Yang, Yiya; Davidson, Duncan R

2003-01-01

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box

NASA Technical Reports Server (NTRS)

ONeil, D. A.; Craig, D. A.; Christensen, C. B.; Gresham, E. C.

2005-01-01

The objective of this Technical Interchange Meeting was to increase the quantity and quality of technical, cost, and programmatic data used to model the impact of investing in different technologies. The focus of this meeting was the Technology Tool Box (TTB), a database of performance, operations, and programmatic parameters provided by technologists and used by systems engineers. The TTB is the data repository used by a system of models known as the Advanced Technology Lifecycle Analysis System (ATLAS). This report describes the result of the November meeting, and also provides background information on ATLAS and the TTB.

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

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

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.

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.

Automated bone segmentation from large field of view 3D MR images of the hip joint

NASA Astrophysics Data System (ADS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

Automated bone segmentation from large field of view 3D MR images of the hip joint.

PubMed

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-21

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

Bayesian longitudinal segmentation of hippocampal substructures in brain MRI using subject-specific atlases

PubMed Central

Iglesias, Juan Eugenio; Van Leemput, Koen; Augustinack, Jean; Insausti, Ricardo; Fischl, Bruce; Reuter, Martin

2016-01-01

The hippocampal formation is a complex, heterogeneous structure that consists of a number of distinct, interacting subregions. Atrophy of these subregions is implied in a variety of neurodegenerative diseases, most prominently in Alzheimer’s disease (AD). Thanks to the increasing resolution of MR images and computational atlases, automatic segmentation of hippocampal subregions is becoming feasible in MRI scans. Here we introduce a generative model for dedicated longitudinal segmentation that relies on subject-specific atlases. The segmentations of the scans at the different time points are jointly computed using Bayesian inference. All time points are treated the same to avoid processing bias. We evaluate this approach using over 4,700 scans from two publicly available datasets (ADNI and MIRIAD). In test-retest reliability experiments, the proposed method yielded significantly lower volume differences and significantly higher Dice overlaps than the cross-sectional approach for nearly every subregion (average across subregions: 4.5% vs. 6.5%, Dice overlap: 81.8% vs. 75.4%). The longitudinal algorithm also demonstrated increased sensitivity to group differences: in MIRIAD (69 subjects: 46 with AD and 23 controls), it found differences in atrophy rates between AD and controls that the cross sectional method could not detect in a number of subregions: right parasubiculum, left and right presubiculum, right subiculum, left dentate gyrus, left CA4, left HATA and right tail. In ADNI (836 subjects: 369 with AD, 215 with early cognitive impairment – eMCI – and 252 controls), all methods found significant differences between AD and controls, but the proposed longitudinal algorithm detected differences between controls and eMCI and differences between eMCI and AD that the cross sectional method could not find: left presubiculum, right subiculum, left and right parasubiculum, left and right HATA. Moreover, many of the differences that the cross-sectional method already found were detected with higher significance. The presented algorithm will be made available as part of the open-source neuroimaging package FreeSurfer. PMID:27426838

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.

A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability.

PubMed

Calabrese, Evan; Badea, Alexandra; Watson, Charles; Johnson, G Allan

2013-05-01

There has been growing interest in the role of postnatal brain development in the etiology of several neurologic diseases. The rat has long been recognized as a powerful model system for studying neuropathology and the safety of pharmacologic treatments. However, the complex spatiotemporal changes that occur during rat neurodevelopment remain to be elucidated. This work establishes the first magnetic resonance histology (MRH) atlas of the developing rat brain, with an emphasis on quantitation. The atlas comprises five specimens at each of nine time points, imaged with eight distinct MR contrasts and segmented into 26 developmentally defined brain regions. The atlas was used to establish a timeline of morphometric changes and variability throughout neurodevelopment and represents a quantitative database of rat neurodevelopment for characterizing rat models of human neurologic disease. Published by Elsevier Inc.

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.

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

Zero echo time MRI-only treatment planning for radiation therapy of brain tumors after resection.

PubMed

Boydev, C; Demol, B; Pasquier, D; Saint-Jalmes, H; Delpon, G; Reynaert, N

2017-10-01

Using magnetic resonance imaging (MRI) as the sole imaging modality for patient modeling in radiation therapy (RT) is a challenging task due to the need to derive electron density information from MRI and construct a so-called pseudo-computed tomography (pCT) image. We have previously published a new method to derive pCT images from head T1-weighted (T1-w) MR images using a single-atlas propagation scheme followed by a post hoc correction of the mapped CT numbers using local intensity information. The purpose of this study was to investigate the performance of our method with head zero echo time (ZTE) MR images. To evaluate results, the mean absolute error in bins of 20 HU was calculated with respect to the true planning CT scan of the patient. We demonstrated that applying our method using ZTE MR images instead of T1-w improved the correctness of the pCT in case of bone resection surgery prior to RT (that is, an example of large anatomical difference between the atlas and the patient). Copyright © 2017. Published by Elsevier Ltd.

MODTRAN: a moderate resolution model for LOWTRAN. Technical report, 12 May 1986-11 May 1987

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

Berk, A.; Bernstein, L.S.; Robertson, D.C.

1987-07-08

This interim technical report describes a new band-model formulation for the LOWTRAN 6 atmospheric transmittance/radiation computer code. Band-model parameters for H/sub 2/O, CO/sub 2/, O/sub 3/, CO, CH/sub 4/, O/sub 2/, and N/sub 2/ were calculated using the 1986 HITRAN line atlas. They were calculated for 1 /cm bins from 0 - 17,900/cm and at five temperatures from 200 to 300K. This transmittance model and associated subroutines were integrated into LOWTRAN 6. The spectral resolution of this new option is better than 5/cm (FWHM). A preliminary version of the code was delivered to AFGL for testing. Validation against FASCOD2 calculationsmore » will be the emphasis for the remainder of this effort.« less

Validation of model-based brain shift correction in neurosurgery via intraoperative magnetic resonance imaging: preliminary results

NASA Astrophysics Data System (ADS)

Luo, Ma; Frisken, Sarah F.; Weis, Jared A.; Clements, Logan W.; Unadkat, Prashin; Thompson, Reid C.; Golby, Alexandra J.; Miga, Michael I.

2017-03-01

The quality of brain tumor resection surgery is dependent on the spatial agreement between preoperative image and intraoperative anatomy. However, brain shift compromises the aforementioned alignment. Currently, the clinical standard to monitor brain shift is intraoperative magnetic resonance (iMR). While iMR provides better understanding of brain shift, its cost and encumbrance is a consideration for medical centers. Hence, we are developing a model-based method that can be a complementary technology to address brain shift in standard resections, with resource-intensive cases as referrals for iMR facilities. Our strategy constructs a deformation `atlas' containing potential deformation solutions derived from a biomechanical model that account for variables such as cerebrospinal fluid drainage and mannitol effects. Volumetric deformation is estimated with an inverse approach that determines the optimal combinatory `atlas' solution fit to best match measured surface deformation. Accordingly, preoperative image is updated based on the computed deformation field. This study is the latest development to validate our methodology with iMR. Briefly, preoperative and intraoperative MR images of 2 patients were acquired. Homologous surface points were selected on preoperative and intraoperative scans as measurement of surface deformation and used to drive the inverse problem. To assess the model accuracy, subsurface shift of targets between preoperative and intraoperative states was measured and compared to model prediction. Considering subsurface shift above 3 mm, the proposed strategy provides an average shift correction of 59% across 2 cases. While further improvements in both the model and ability to validate with iMR are desired, the results reported are encouraging.

Multi-atlas segmentation for abdominal organs with Gaussian mixture models

NASA Astrophysics Data System (ADS)

Burke, Ryan P.; Xu, Zhoubing; Lee, Christopher P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

2015-03-01

Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid / gray matter / white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.

Modeling the Effect of Nonlinear and Rate-Limited Sorption on the Natural Attenuation of Chlorinated Ethenes

DTIC Science & Technology

2000-03-01

toxicity. Determine what parameters lead to minimized risk to human health. 64 6.0 Bibliography Atlas , R.M. and R. Bartha . Microbial Ecology ...single-celled organisms ( Atlas and Bartha , 1993). Biodegradation - Process where bacteria mineralize or transform contaminants using organic...NRC, 1994) Methanogenesis - The process of creating methane from H2 and CO2 during the respiration of methanogens ( Atlas and Bartha , 1993

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.

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.

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.

Interdigitated Back-Surface-Contact Solar Cell Modeling Using Silvaco Atlas

DTIC Science & Technology

2015-06-01

11 2. Solar Spectrum ...................................................................................13 3. PV Cell Efficiency...Figure 10. Spectrum of solar radiance, from [12]. 14 3. PV Cell Efficiency There are many factors that affect the efficiency of a solar cell. Metal...BACK-SURFACE-CONTACT SOLAR CELL MODELING USING SILVACO ATLAS by Shawn E. Green June 2015 Thesis Advisor: Sherif Michael Second Reader

Efficient patient modeling for visuo-haptic VR simulation using a generic patient atlas.

PubMed

Mastmeyer, Andre; Fortmeier, Dirk; Handels, Heinz

2016-08-01

This work presents a new time-saving virtual patient modeling system by way of example for an existing visuo-haptic training and planning virtual reality (VR) system for percutaneous transhepatic cholangio-drainage (PTCD). Our modeling process is based on a generic patient atlas to start with. It is defined by organ-specific optimized models, method modules and parameters, i.e. mainly individual segmentation masks, transfer functions to fill the gaps between the masks and intensity image data. In this contribution, we show how generic patient atlases can be generalized to new patient data. The methodology consists of patient-specific, locally-adaptive transfer functions and dedicated modeling methods such as multi-atlas segmentation, vessel filtering and spline-modeling. Our full image volume segmentation algorithm yields median DICE coefficients of 0.98, 0.93, 0.82, 0.74, 0.51 and 0.48 regarding soft-tissue, liver, bone, skin, blood and bile vessels for ten test patients and three selected reference patients. Compared to standard slice-wise manual contouring time saving is remarkable. Our segmentation process shows out efficiency and robustness for upper abdominal puncture simulation systems. This marks a significant step toward establishing patient-specific training and hands-on planning systems in a clinical environment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

PubMed

Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

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

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.

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.

Aquatic models, genomics and chemical risk management.

PubMed

Cheng, Keith C; Hinton, David E; Mattingly, Carolyn J; Planchart, Antonio

2012-01-01

The 5th Aquatic Animal Models for Human Disease meeting follows four previous meetings (Nairn et al., 2001; Schmale, 2004; Schmale et al., 2007; Hinton et al., 2009) in which advances in aquatic animal models for human disease research were reported, and community discussion of future direction was pursued. At this meeting, discussion at a workshop entitled Bioinformatics and Computational Biology with Web-based Resources (20 September 2010) led to an important conclusion: Aquatic model research using feral and experimental fish, in combination with web-based access to annotated anatomical atlases and toxicological databases, yields data that advance our understanding of human gene function, and can be used to facilitate environmental management and drug development. We propose here that the effects of genes and environment are best appreciated within an anatomical context - the specifically affected cells and organs in the whole animal. We envision the use of automated, whole-animal imaging at cellular resolution and computational morphometry facilitated by high-performance computing and automated entry into toxicological databases, as anchors for genetic and toxicological data, and as connectors between human and model system data. These principles should be applied to both laboratory and feral fish populations, which have been virtually irreplaceable sentinals for environmental contamination that results in human morbidity and mortality. We conclude that automation, database generation, and web-based accessibility, facilitated by genomic/transcriptomic data and high-performance and cloud computing, will potentiate the unique and potentially key roles that aquatic models play in advancing systems biology, drug development, and environmental risk management. Copyright © 2011 Elsevier Inc. All rights reserved.

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/.

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.

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.

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.

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.

Three-dimensional stereotactic atlas of the extracranial vasculature correlated with the intracranial vasculature, cranial nerves, skull and muscles

PubMed Central

Shoon Let Thaung, Thant; Choon Chua, Beng; Hnin Wut Yi, Su; Yang, Yili; Urbanik, Andrzej

2015-01-01

Our objective was to construct a 3D, interactive, and reference atlas of the extracranial vasculature spatially correlated with the intracranial blood vessels, cranial nerves, skull, glands, and head muscles. The atlas has been constructed from multiple 3T and 7T magnetic resonance angiogram (MRA) brain scans, and 3T phase contrast and inflow MRA neck scans of the same specimen in the following steps: vessel extraction from the scans, building 3D tubular models of the vessels, spatial registration of the extra- and intracranial vessels, vessel editing, vessel naming and color-coding, vessel simplification, and atlas validation. This new atlas contains 48 names of the extracranial vessels (25 arterial and 23 venous) and it has been integrated with the existing brain atlas. The atlas is valuable for medical students and residents to easily get familiarized with the extracranial vasculature with a few clicks; is useful for educators to prepare teaching materials; and potentially can serve as a reference in the diagnosis of vascular disease and treatment, including craniomaxillofacial surgeries and radiologic interventions of the face and neck. PMID:25923683

CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules.

PubMed

Cestarelli, Valerio; Fiscon, Giulia; Felici, Giovanni; Bertolazzi, Paola; Weitschek, Emanuel

2016-03-01

Nowadays, knowledge extraction methods from Next Generation Sequencing data are highly requested. In this work, we focus on RNA-seq gene expression analysis and specifically on case-control studies with rule-based supervised classification algorithms that build a model able to discriminate cases from controls. State of the art algorithms compute a single classification model that contains few features (genes). On the contrary, our goal is to elicit a higher amount of knowledge by computing many classification models, and therefore to identify most of the genes related to the predicted class. We propose CAMUR, a new method that extracts multiple and equivalent classification models. CAMUR iteratively computes a rule-based classification model, calculates the power set of the genes present in the rules, iteratively eliminates those combinations from the data set, and performs again the classification procedure until a stopping criterion is verified. CAMUR includes an ad-hoc knowledge repository (database) and a querying tool.We analyze three different types of RNA-seq data sets (Breast, Head and Neck, and Stomach Cancer) from The Cancer Genome Atlas (TCGA) and we validate CAMUR and its models also on non-TCGA data. Our experimental results show the efficacy of CAMUR: we obtain several reliable equivalent classification models, from which the most frequent genes, their relationships, and the relation with a particular cancer are deduced. dmb.iasi.cnr.it/camur.php emanuel@iasi.cnr.it Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Piecewise Delamination Drives Uplift in the Atlas Mountains Region of Morocco

NASA Astrophysics Data System (ADS)

Bezada, M. J.; Humphreys, E.; Martin Davila, J.; mimoun, H.; Josep, G.; Palomeras, I.

2013-12-01

The elevation of the intra-continental Atlas Mountains of Morocco and surrounding regions requires a mantle component of buoyancy, and there is consensus that this buoyancy results from an abnormally thin lithosphere. Lithospheric delamination under the Atlas Mountains and thermal erosion caused by upwelling mantle have each been suggested as thinning mechanisms. We use seismic tomography to image the upper mantle of Morocco by inverting teleseimic p-wave delay times, complemented with local delays, recorded on a dense array of stations in the Iberian peninsula and Morocco. A surface wave model provides constraint on the shallower layers. We determine the geometry of lithospheric cavities and mantle upwelling beneath the Middle Atlas and central High Atlas, and image delaminated lithosphere at ~400 km beneath the Middle Atlas. We propose discontinuous delamination of an intrinsically unstable Atlas lithosphere, enabled by the presence of anomalously hot mantle, as a mechanism for producing the imaged structures. The Atlas lithosphere was made unstable by a combination of tectonic shortening and eclogite loading during Mesozoic rifting and Cenozoic magmatism. The presence of hot mantle, sourced from regional upwellings in northern Africa or the Canary Islands, enabled the mobilization of this lithosphere. Flow around the retreating Alboran slab focused upwelling mantle under the Middle Atlas, where we image the most recent delamination. The Atlas Mountains of Morocco stand as an example of mantle-generated uplift and large-scale lithospheric loss in a mildly contractional orogen.

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.

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.

Multi-atlas label fusion using hybrid of discriminative and generative classifiers for segmentation of cardiac MR images.

PubMed

Sedai, Suman; Garnavi, Rahil; Roy, Pallab; Xi Liang

2015-08-01

Multi-atlas segmentation first registers each atlas image to the target image and transfers the label of atlas image to the coordinate system of the target image. The transferred labels are then combined, using a label fusion algorithm. In this paper, we propose a novel label fusion method which aggregates discriminative learning and generative modeling for segmentation of cardiac MR images. First, a probabilistic Random Forest classifier is trained as a discriminative model to obtain the prior probability of a label at the given voxel of the target image. Then, a probability distribution of image patches is modeled using Gaussian Mixture Model for each label, providing the likelihood of the voxel belonging to the label. The final label posterior is obtained by combining the classification score and the likelihood score under Bayesian rule. Comparative study performed on MICCAI 2013 SATA Segmentation Challenge demonstrates that our proposed hybrid label fusion algorithm is accurate than other five state-of-the-art label fusion methods. The proposed method obtains dice similarity coefficient of 0.94 and 0.92 in segmenting epicardium and endocardium respectively. Moreover, our label fusion method achieves more accurate segmentation results compared to four other label fusion methods.

The Herschel-ATLAS: Extragalatic Number Counts from 250 to 500 Microns

NASA Technical Reports Server (NTRS)

Clements, D. L.; Rigby, E.; Maddox, S.; Dunne, L.; Mortier, A.; Amblard, A.; Auld, R.; Bonfield, D.; Cooray, A.; Dariush, A.;

SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

PubMed

Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

2018-05-25

Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

Mesure des champs de radiation dans le detecteur ATLAS et sa caverne avec les detecteurs au silicium a pixels ATLAS-MPX

NASA Astrophysics Data System (ADS)

Bouchami, Jihene

The LHC proton-proton collisions create a hard radiation environment in the ATLAS detector. In order to quantify the effects of this environment on the detector performance and human safety, several Monte Carlo simulations have been performed. However, direct measurement is indispensable to monitor radiation levels in ATLAS and also to verify the simulation predictions. For this purpose, sixteen ATLAS-MPX devices have been installed at various positions in the ATLAS experimental and technical areas. They are composed of a pixelated silicon detector called MPX whose active surface is partially covered with converter layers for the detection of thermal, slow and fast neutrons. The ATLAS-MPX devices perform real-time measurement of radiation fields by recording the detected particle tracks as raster images. The analysis of the acquired images allows the identification of the detected particle types by the shapes of their tracks. For this aim, a pattern recognition software called MAFalda has been conceived. Since the tracks of strongly ionizing particles are influenced by charge sharing between adjacent pixels, a semi-empirical model describing this effect has been developed. Using this model, the energy of strongly ionizing particles can be estimated from the size of their tracks. The converter layers covering each ATLAS-MPX device form six different regions. The efficiency of each region to detect thermal, slow and fast neutrons has been determined by calibration measurements with known sources. The study of the ATLAS-MPX devices response to the radiation produced by proton-proton collisions at a center of mass energy of 7 TeV has demonstrated that the number of recorded tracks is proportional to the LHC luminosity. This result allows the ATLAS-MPX devices to be employed as luminosity monitors. To perform an absolute luminosity measurement and calibration with these devices, the van der Meer method based on the LHC beam parameters has been proposed. Since the ATLAS-MPX devices response and the luminosity are correlated, the results of measuring radiation levels are expressed in terms of particle fluences per unit integrated luminosity. A significant deviation has been obtained when comparing these fluences with those predicted by GCALOR, which is one of the ATLAS detector simulations. In addition, radiation measurements performed at the end of proton-proton collisions have demonstrated that the decay of radionuclides produced during collisions can be observed with the ATLAS-MPX devices. The residual activation of ATLAS components can be measured with these devices by means of ambient dose equivalent calibration. Keywords: pattern recognition, charge sharing effect, neutron detection efficiency, luminosity, van der Meer method, particle fluences, GCALOR simulation, residual activation, ambient dose equivalent.

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

Summary of the ATLAS experiment’s sensitivity to supersymmetry after LHC Run 1 -- interpreted in the phenomenological MSSM

DOE PAGES

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

2015-10-21

A summary of the constraints from the ATLAS experiment on R -parity-conserving supersymmetry is presented. Results from 22 separate ATLAS searches are considered, each based on analysis of up to 20.3 fb –1 of proton-proton collision data at centre-of-mass energies of √s =7 and 8 TeV at the Large Hadron Collider. The results are interpreted in the context of the 19-parameter phenomenological minimal supersymmetric standard model, in which the lightest supersymmetric particle is a neutralino, taking into account constraints from previous precision electroweak and flavour measurements as well as from dark matter related measurements. The results are presented in termsmore » of constraints on supersymmetric particle masses and are compared to limits from simplified models. The impact of ATLAS searches on parameters such as the dark matter relic density, the couplings of the observed Higgs boson, and the degree of electroweak fine-tuning is also shown. As a result, spectra for surviving supersymmetry model points with low fine-tunings are presented.« less

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.

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.

A high performance hierarchical storage management system for the Canadian tier-1 centre at TRIUMF

NASA Astrophysics Data System (ADS)

Deatrich, D. C.; Liu, S. X.; Tafirout, R.

2010-04-01

We describe in this paper the design and implementation of Tapeguy, a high performance non-proprietary Hierarchical Storage Management (HSM) system which is interfaced to dCache for efficient tertiary storage operations. The system has been successfully implemented at the Canadian Tier-1 Centre at TRIUMF. The ATLAS experiment will collect a large amount of data (approximately 3.5 Petabytes each year). An efficient HSM system will play a crucial role in the success of the ATLAS Computing Model which is driven by intensive large-scale data analysis activities that will be performed on the Worldwide LHC Computing Grid infrastructure continuously. Tapeguy is Perl-based. It controls and manages data and tape libraries. Its architecture is scalable and includes Dataset Writing control, a Read-back Queuing mechanism and I/O tape drive load balancing as well as on-demand allocation of resources. A central MySQL database records metadata information for every file and transaction (for audit and performance evaluation), as well as an inventory of library elements. Tapeguy Dataset Writing was implemented to group files which are close in time and of similar type. Optional dataset path control dynamically allocates tape families and assign tapes to it. Tape flushing is based on various strategies: time, threshold or external callbacks mechanisms. Tapeguy Read-back Queuing reorders all read requests by using an elevator algorithm, avoiding unnecessary tape loading and unloading. Implementation of priorities will guarantee file delivery to all clients in a timely manner.

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

A registration-based segmentation method with application to adiposity analysis of mice microCT images

NASA Astrophysics Data System (ADS)

Bai, Bing; Joshi, Anand; Brandhorst, Sebastian; Longo, Valter D.; Conti, Peter S.; Leahy, Richard M.

2014-04-01

Obesity is a global health problem, particularly in the U.S. where one third of adults are obese. A reliable and accurate method of quantifying obesity is necessary. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) are two measures of obesity that reflect different associated health risks, but accurate measurements in humans or rodent models are difficult. In this paper we present an automatic, registration-based segmentation method for mouse adiposity studies using microCT images. We co-register the subject CT image and a mouse CT atlas. Our method is based on surface matching of the microCT image and an atlas. Surface-based elastic volume warping is used to match the internal anatomy. We acquired a whole body scan of a C57BL6/J mouse injected with contrast agent using microCT and created a whole body mouse atlas by manually delineate the boundaries of the mouse and major organs. For method verification we scanned a C57BL6/J mouse from the base of the skull to the distal tibia. We registered the obtained mouse CT image to our atlas. Preliminary results show that we can warp the atlas image to match the posture and shape of the subject CT image, which has significant differences from the atlas. We plan to use this software tool in longitudinal obesity studies using mouse models.

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

On the coverage of the pMSSM by simplified model results

NASA Astrophysics Data System (ADS)

Ambrogi, Federico; Kraml, Sabine; Kulkarni, Suchita; Laa, Ursula; Lessa, Andre; Waltenberger, Wolfgang

2018-03-01

We investigate to which extent the SUSY search results published by ATLAS and CMS in the context of simplified models actually cover the more realistic scenarios of a full model. Concretely, we work within the phenomenological MSSM (pMSSM) with 19 free parameters and compare the constraints obtained from SModelS v1.1.1 with those from the ATLAS pMSSM study in arXiv:1508.06608. We find that about 40-45% of the points excluded by ATLAS escape the currently available simplified model constraints. For these points we identify the most relevant topologies which are not tested by the current simplified model results. In particular, we find that topologies with asymmetric branches, including 3-jet signatures from gluino-squark associated production, could be important for improving the current constraining power of simplified models results. Furthermore, for a better coverage of light stops and sbottoms, constraints for decays via heavier neutralinos and charginos, which subsequently decay visibly to the lightest neutralino are also needed.

The North American Drought Atlas: Tree-Ring Reconstructions of Drought Variability for Climate Modeling and Assessment

NASA Astrophysics Data System (ADS)

Cook, E. R.

2007-05-01

The North American Drought Atlas describes a detailed reconstruction of drought variability from tree rings over most of North America for the past 500-1000 years. The first version of it, produced over three years ago, was based on a network of 835 tree-ring chronologies and a 286-point grid of instrumental Palmer Drought Severity Indices (PDSI). These gridded PDSI reconstructions have been used in numerous published studies now that range from modeling fire in the American West, to the impact of drought on palaeo-Indian societies, and to the determination of the primary causes of drought over North America through climate modeling experiments. Some examples of these applications will be described to illustrate the scientific value of these large-scale reconstructions of drought. Since the development and free public release of Version 1 of the North American Drought Atlas (see http:iridl.ldeo.columbia.edu/SOURCES/.LDEO/.TRL/.NADA2004/.pdsi-atlas.html), great improvements have been made in the critical tree-ring network used to reconstruct PDSI at each grid point. This network has now been enlarged to 1743 annual tree-ring chronologies, which greatly improves the density of tree-ring records in certain parts of the grid, especially in Canada and Mexico. In addition, the number of tree-ring records that extend back before AD 1400 has been substantially increased. These developments justify the creation of Version 2 of the North American Drought Atlas. In this talk I will describe this new version of the drought atlas and some of its properties that make it a significant improvement over the previous version. The new product provides enhanced resolution of the spatial and temporal variability of prolonged drought such as the late 16th century event that impacted regions of both Mexico and the United States. I will also argue for the North American Drought Atlas being used as a template for the development of large-scale drought reconstructions in other land areas of the Northern Hemisphere where sufficient tree-ring data exist. By doing so, the importance of this product to the modeling community will be significantly enhanced.

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain.

PubMed

Arganda-Carreras, Ignacio; Manoliu, Tudor; Mazuras, Nicolas; Schulze, Florian; Iglesias, Juan E; Bühler, Katja; Jenett, Arnim; Rouyer, François; Andrey, Philippe

2018-01-01

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila , one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species.

Atlas-Centaur Separation Test in the Space Power Chambers

NASA Image and Video Library

1963-11-21

An Atlas/Centaur mass model undergoes a separation test inside the Space Power Chambers at NASA Lewis Research Center. Lewis was in the midst of an extensive effort to prepare the Centaur second-stage rocket for its missions to send the Surveyor spacecraft to the moon as a precursor to the Apollo missions. As part of these preparations, Lewis management decided to convert its Altitude Wind Tunnel into two large test chambers—the Space Power Chambers. The conversion included the removal of the tunnel’s internal components and the insertion of bulkheads to seal off the new chambers within the tunnel. One chamber could simulate conditions found at 100 miles altitude, while this larger chamber simulated the upper atmosphere. In this test series, researchers wanted to verify that the vehicle’s retrorockets would properly separate the Centaur from the Atlas. The model was suspended horizontally on a trolley system inside chamber. A net was hung at one end to catch the jettisoned Atlas model. The chamber atmosphere was reduced to a pressure altitude of 100,000 feet, and high-speed cameras were synchronized to the ignition of the retrorockets. The simulated Centaur is seen here jettisoning from the Atlas out of view to the right. The study resulted in a new jettison method that would significantly reduce the separation time and thus minimize the danger of collision between the two stages during separation.

Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis

NASA Astrophysics Data System (ADS)

Evans, Alan C.; Dai, Weiqian; Collins, D. Louis; Neelin, Peter; Marrett, Sean

1991-06-01

We describe the implementation, experience and preliminary results obtained with a 3-D computerized brain atlas for topographical and functional analysis of brain sub-regions. A volume-of-interest (VOI) atlas was produced by manual contouring on 64 adjacent 2 mm-thick MRI slices to yield 60 brain structures in each hemisphere which could be adjusted, originally by global affine transformation or local interactive adjustments, to match individual MRI datasets. We have now added a non-linear deformation (warp) capability (Bookstein, 1989) into the procedure for fitting the atlas to the brain data. Specific target points are identified in both atlas and MRI spaces which define a continuous 3-D warp transformation that maps the atlas on to the individual brain image. The procedure was used to fit MRI brain image volumes from 16 young normal volunteers. Regional volume and positional variability were determined, the latter in such a way as to assess the extent to which previous linear models of brain anatomical variability fail to account for the true variation among normal individuals. Using a linear model for atlas deformation yielded 3-D fits of the MRI data which, when pooled across subjects and brain regions, left a residual mis-match of 6 - 7 mm as compared to the non-linear model. The results indicate a substantial component of morphometric variability is not accounted for by linear scaling. This has profound implications for applications which employ stereotactic coordinate systems which map individual brains into a common reference frame: quantitative neuroradiology, stereotactic neurosurgery and cognitive mapping of normal brain function with PET. In the latter case, the combination of a non-linear deformation algorithm would allow for accurate measurement of individual anatomic variations and the inclusion of such variations in inter-subject averaging methodologies used for cognitive mapping with PET.

Combining registration and active shape models for the automatic segmentation of the lymph node regions in head and neck CT images

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

Chen Antong; Deeley, Matthew A.; Niermann, Kenneth J.

2010-12-15

Purpose: Intensity-modulated radiation therapy (IMRT) is the state of the art technique for head and neck cancer treatment. It requires precise delineation of the target to be treated and structures to be spared, which is currently done manually. The process is a time-consuming task of which the delineation of lymph node regions is often the longest step. Atlas-based delineation has been proposed as an alternative, but, in the authors' experience, this approach is not accurate enough for routine clinical use. Here, the authors improve atlas-based segmentation results obtained for level II-IV lymph node regions using an active shape model (ASM)more » approach. Methods: An average image volume was first created from a set of head and neck patient images with minimally enlarged nodes. The average image volume was then registered using affine, global, and local nonrigid transformations to the other volumes to establish a correspondence between surface points in the atlas and surface points in each of the other volumes. Once the correspondence was established, the ASMs were created for each node level. The models were then used to first constrain the results obtained with an atlas-based approach and then to iteratively refine the solution. Results: The method was evaluated through a leave-one-out experiment. The ASM- and atlas-based segmentations were compared to manual delineations via the Dice similarity coefficient (DSC) for volume overlap and the Euclidean distance between manual and automatic 3D surfaces. The mean DSC value obtained with the ASM-based approach is 10.7% higher than with the atlas-based approach; the mean and median surface errors were decreased by 13.6% and 12.0%, respectively. Conclusions: The ASM approach is effective in reducing segmentation errors in areas of low CT contrast where purely atlas-based methods are challenged. Statistical analysis shows that the improvements brought by this approach are significant.« less

SU-E-I-71: Quality Assessment of Surrogate Metrics in Multi-Atlas-Based Image Segmentation

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

Zhao, T; Ruan, D

Purpose: With the ever-growing data of heterogeneous quality, relevance assessment of atlases becomes increasingly critical for multi-atlas-based image segmentation. However, there is no universally recognized best relevance metric and even a standard to compare amongst candidates remains elusive. This study, for the first time, designs a quantification to assess relevance metrics’ quality, based on a novel perspective of the metric as surrogate for inferring the inaccessible oracle geometric agreement. Methods: We first develop an inference model to relate surrogate metrics in image space to the underlying oracle relevance metric in segmentation label space, with a monotonically non-decreasing function subject tomore » random perturbations. Subsequently, we investigate model parameters to reveal key contributing factors to surrogates’ ability in prognosticating the oracle relevance value, for the specific task of atlas selection. Finally, we design an effective contract-to-noise ratio (eCNR) to quantify surrogates’ quality based on insights from these analyses and empirical observations. Results: The inference model was specialized to a linear function with normally distributed perturbations, with surrogate metric exemplified by several widely-used image similarity metrics, i.e., MSD/NCC/(N)MI. Surrogates’ behaviors in selecting the most relevant atlases were assessed under varying eCNR, showing that surrogates with high eCNR dominated those with low eCNR in retaining the most relevant atlases. In an end-to-end validation, NCC/(N)MI with eCNR of 0.12 compared to MSD with eCNR of 0.10 resulted in statistically better segmentation with mean DSC of about 0.85 and the first and third quartiles of (0.83, 0.89), compared to MSD with mean DSC of 0.84 and the first and third quartiles of (0.81, 0.89). Conclusion: The designed eCNR is capable of characterizing surrogate metrics’ quality in prognosticating the oracle relevance value. It has been demonstrated to be correlated with the performance of relevant atlas selection and ultimate label fusion.« less

Generation of an Atlas of the Proximal Femur and Its Application to Trabecular Bone Analysis

PubMed Central

Carballido-Gamio, Julio; Folkesson, Jenny; Karampinos, Dimitrios C.; Baum, Thomas; Link, Thomas M.; Majumdar, Sharmila; Krug, Roland

2013-01-01

Automatic placement of anatomically corresponding volumes of interest and comparison of parameters against a standard of reference are essential components in studies of trabecular bone. Only recently, in vivo MR images of the proximal femur, an important fracture site, could be acquired with high-spatial resolution. The purpose of this MRI trabecular bone study was two-fold: (1) to generate an atlas of the proximal femur to automatically place anatomically corresponding volumes of interest in a population study and (2) to demonstrate how mean models of geodesic topological analysis parameters can be generated to be used as potential standard of reference. Ten females were used to generate the atlas and geodesic topological analysis models, and 10 females were used to demonstrate the atlas-based trabecular bone analysis. All alignments were based on three-dimensional (3D) multiresolution affine transformations followed by 3D multiresolution free-form deformations. Mean distances less than 1 mm between aligned femora, and sharp edges in the atlas and in fused gray-level images of registered femora indicated that the anatomical variability was well accommodated and explained by the free-form deformations. PMID:21432904

The effects of the exhaust plume on the lightning triggering conditions for launch vehicles

NASA Technical Reports Server (NTRS)

Eriksen, Frederick J.; Rudolph, Terence H.; Perala, Rodney A.

1991-01-01

Apollo 12 and Atlas Centaur 67 are two launch vehicles that have experienced triggered lightning strikes. Serious consequences resulted from the events; in the case of Atlas Centaur 67, the vehicle and the payload were lost. These events indicate that it is necessary to develop launch rules which would prevent such occurrences. In order to develop valid lightning related rules, it is necessary to understand the effects of the plume. Some have assumed that the plume can be treated as a perfect conductor, and have computed electric field enhancement factors on that basis. The authors have looked at the plume, and believe that these models are not correct, because they ignore the fluid motion of the conducting plates. The authors developed a model which includes this flow character. In this model, the external field is excluded from the plume as it would be for any good conductor, but, in addition, the charge must distribute so that the charge density is zero at some location in the exhaust. When this condition is included in the calculation of triggering enhancement factors, they can be two to three times larger than calculated by other methods which include a conductive plume but don't include the correct boundary conditions. Here, the authors review the relevant features of rocket exhausts for the triggered lightning problem, present an approach for including flowing conductive gases, and present preliminary calculations to demonstrate the effect that the plume has on enhancement factors.

Utah optrode array customization using stereotactic brain atlases and 3-D CAD modeling for optogenetic neocortical interrogation in small rodents and nonhuman primates.

PubMed

Boutte, Ronald W; Merlin, Sam; Yona, Guy; Griffiths, Brandon; Angelucci, Alessandra; Kahn, Itamar; Shoham, Shy; Blair, Steve

2017-10-01

As the optogenetic field expands, the need for precise targeting of neocortical circuits only grows more crucial. This work demonstrates a technique for using Solidworks ® computer-aided design (CAD) and readily available stereotactic brain atlases to create a three-dimensional (3-D) model of the dorsal region of area visual cortex 4 (V4D) of the macaque monkey ( Macaca fascicularis ) visual cortex. The 3-D CAD model of the brain was used to customize an [Formula: see text] Utah optrode array (UOA) after it was determined that a high-density ([Formula: see text]) UOA caused extensive damage to marmoset ( Callithrix jacchus ) primary visual cortex as assessed by electrophysiological recording of spiking activity through a 1.5-mm-diameter through glass via. The [Formula: see text] UOA was customized for optrode length ([Formula: see text]), optrode width ([Formula: see text]), optrode pitch ([Formula: see text]), backplane thickness ([Formula: see text]), and overall form factor ([Formula: see text]). Two [Formula: see text] UOAs were inserted into layer VI of macaque V4D cortices with minimal damage as assessed in fixed tissue cytochrome oxidase staining in nonrecoverable surgeries. Additionally, two [Formula: see text] arrays were implanted in mice ( Mus musculus ) motor cortices, providing early evidence for long-term tolerability (over 6 months), and for the ability to integrate the UOA with a Holobundle light delivery system toward patterned optogenetic stimulation of cortical networks.

EnviroAtlas - Austin, TX - BenMAP Results by Block Group

EPA Pesticide Factsheets

This EnviroAtlas dataset demonstrates the effect of changes in pollution concentration on local populations in 750 block groups in Austin, Texas. The US EPA's Environmental Benefits Mapping and Analysis Program (BenMAP) was used to estimate the incidence of adverse health effects (i.e., mortality and morbidity) and associated monetary value that result from changes in pollution concentrations for Travis and Williamson Counties, TX. Incidence and value estimates for the block groups are calculated using i-Tree models (www.itreetools.org), local weather data, pollution data, and U.S. Census derived population data. This dataset was produced by the US Forest Service 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).

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

Three-dimensional stereotactic atlas of the extracranial vasculature correlated with the intracranial vasculature, cranial nerves, skull and muscles.

PubMed

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

2015-04-01

Our objective was to construct a 3D, interactive, and reference atlas of the extracranial vasculature spatially correlated with the intracranial blood vessels, cranial nerves, skull, glands, and head muscles.The atlas has been constructed from multiple 3T and 7T magnetic resonance angiogram (MRA) brain scans, and 3T phase contrast and inflow MRA neck scans of the same specimen in the following steps: vessel extraction from the scans, building 3D tubular models of the vessels, spatial registration of the extra- and intracranial vessels, vessel editing, vessel naming and color-coding, vessel simplification, and atlas validation.This new atlas contains 48 names of the extracranial vessels (25 arterial and 23 venous) and it has been integrated with the existing brain atlas.The atlas is valuable for medical students and residents to easily get familiarized with the extracranial vasculature with a few clicks; is useful for educators to prepare teaching materials; and potentially can serve as a reference in the diagnosis of vascular disease and treatment, including craniomaxillofacial surgeries and radiologic interventions of the face and neck. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

Chaotic dynamics outside Saturn’s main rings: The case of Atlas

NASA Astrophysics Data System (ADS)

Renner, Stéfan; Cooper, Nicholas J.; El Moutamid, Maryame; Evans, Mike W.; Murray, Carl D.; Sicardy, Bruno

2014-11-01

We revisit in detail the dynamics of Atlas. From a fit to new Cassini ISS astrometric observations spanning February 2004 to August 2013, we estimate GM_Atlas=0.384+/-0.001 x 10^(-3)km^3s^(-2), a value 13% smaller than the previously published estimate but with an order of magnitude reduction in the uncertainty. Our numerically-derived orbit shows that Atlas is currently librating in both a 54:53 corotation eccentricity resonance (CER) and a 54:53 Lindblad eccentricity resonance (LER) with Prometheus. We demonstrate that the orbit of Atlas is chaotic, with a Lyapunov time of order 10 years, as a direct consequence of the coupled resonant interaction (CER/LER) with Prometheus. The interactions between the two resonances is investigated using the CoraLin analytical model (El Moutamid et al., 2014), showing that the chaotic zone fills almost all the corotation site occupied by the satellite’s orbit. Four 70 :67 apse-type mean motion resonances with Pandora are also overlapping, but these resonances have a much weaker effect on Atlas.We estimate the capture probabilities of Atlas into resonances with Prometheus as the orbits expand through tidal effects, and discuss the implications for the orbital evolution.

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 I/O performance optimization in as-deployed environments

NASA Astrophysics Data System (ADS)

Maier, T.; Benjamin, D.; Bhimji, W.; Elmsheuser, J.; van Gemmeren, P.; Malon, D.; Krumnack, N.

2015-12-01

This paper provides an overview of an integrated program of work underway within the ATLAS experiment to optimise I/O performance for large-scale physics data analysis in a range of deployment environments. It proceeds to examine in greater detail one component of that work, the tuning of job-level I/O parameters in response to changes to the ATLAS event data model, and considers the implications of such tuning for a number of measures of I/O performance.

A Comparison of Response Surface Methodology and a One-Factor-At-A-Time Approach as Calibration Techniques for the Bioplume-II Simulation Model of Contaminant Biodegradation

DTIC Science & Technology

1995-12-01

34 Environmental Science and Technology, 26:1404-1410 (July 1992). 4. Atlas , Ronald M. and Richard Bartha . Microbial Ecology , Fundamentals and Applica...the impact of physical factors on microbial activity. They cite research by Atlas and Bartha observing that low temperatures inhibit microbial activity...mixture. Atlas and Bartha (4:393-394) explain that a typical petroleum mixture includes aliphatics, alicyclics, aromatics and other organics. The

Progress toward a circulation atlas for application to coastal water siting problems

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.; Gordon, H. H.

1978-01-01

Circulation data needed to resolve coastal siting problems are assembled from historical hydrographic and remote sensing studies in the form of a Circulation Atlas. Empirical data are used instead of numerical model simulations to achieve fine resolution and include fronts and convergence zones. Eulerian and Langrangian data are collected, transformed, and combined into trajectory maps and current vector maps as a function of tidal phase and wind vector. Initial Atlas development is centered on the Elizabeth River, Hampton Roads, Virgina.

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.

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.

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

Searching for confining hidden valleys at LHCb, ATLAS, and CMS

NASA Astrophysics Data System (ADS)

Pierce, Aaron; Shakya, Bibhushan; Tsai, Yuhsin; Zhao, Yue

2018-05-01

We explore strategies for probing hidden valley scenarios exhibiting confinement. Such scenarios lead to a moderate multiplicity of light hidden hadrons for generic showering and hadronization similar to QCD. Their decays are typically soft and displaced, making them challenging to probe with traditional LHC searches. We show that the low trigger requirements and excellent track and vertex reconstruction at LHCb provide a favorable environment to search for such signals. We propose novel search strategies in both muonic and hadronic channels. We also study existing ATLAS and CMS searches and compare them with our proposals at LHCb. We find that the reach at LHCb is generically better in the parameter space we consider here, even with optimistic background estimations for ATLAS and CMS searches. We discuss potential modifications at ATLAS and CMS that might make these experiments competitive with the LHCb reach. Our proposed searches can be applied to general hidden valley models as well as exotic Higgs boson decays, such as in twin Higgs models.

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.

An Atlas of annotations of Hydra vulgaris transcriptome.

PubMed

Evangelista, Daniela; Tripathi, Kumar Parijat; Guarracino, Mario Rosario

2016-09-22

RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological information is still a key issue, reason for which the creation of web-resources useful for their analysis is highly desiderable. Starting from a previous work, Transcriptator, we present the Atlas of Hydra's vulgaris, an extensible web tool in which its complete transcriptome is annotated. In order to provide to the users an advantageous resource that include the whole functional annotated transcriptome of Hydra vulgaris water polyp, we implemented the Atlas web-tool contains 31.988 accesible and downloadable transcripts of this non-reference model organism. Atlas, as a freely available resource, can be considered a valuable tool to rapidly retrieve functional annotation for transcripts differentially expressed in Hydra vulgaris exposed to the distinct experimental treatments. WEB RESOURCE URL: http://www-labgtp.na.icar.cnr.it/Atlas .

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.

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.

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.

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

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.

Lithospheric structure of northwest Africa: Insights into the tectonic history and influence of mantle flow on large-scale deformation

NASA Astrophysics Data System (ADS)

Miller, Meghan S.; Becker, Thorsten

2014-05-01

Northwest Africa is affected by late stage convergence of Africa with Eurasia, the Canary Island hotspot, and bounded by the Proterozoic-age West African craton. We present seismological evidence from receiver functions and shear-wave splitting along with geodynamic modeling to show how the interactions of these tectonic features resulted in dramatic deformation of the lithosphere. We interpret seismic discontinuities from the receiver functions and find evidence for localized, near vertical-offset deformation of both crust-mantle and lithosphere-asthenosphere interfaces at the flanks of the High Atlas. These offsets coincide with the locations of Jurassic-aged normal faults that have been reactivated during the Cenozoic, further suggesting that inherited, lithospheric-scale zones of weakness were involved in the formation of the Atlas. Another significant step in lithospheric thickness is inferred within the Middle Atlas. Its location corresponds to the source of regional Quaternary alkali volcanism, where the influx of melt induced by the shallow asthenosphere appears restricted to a lithospheric-scale fault on the northern side of the mountain belt. Inferred stretching axes from shear-wave splitting are aligned with the topographic grain in the High Atlas, suggesting along-strike asthenospheric shearing in a mantle channel guided by the lithospheric topography. Isostatic modeling based on our improved lithospheric constraints indicates that lithospheric thinning alone does not explain the anomalous Atlas topography. Instead, an mantle upwelling induced by a hot asthenospheric anomaly appears required, likely guided by the West African craton and perhaps sucked northward by subducted lithosphere beneath the Alboran. This dynamic support scenario for the Atlas also suggests that the timing of uplift is contemporaneous with the recent volcanismin the Middle Atlas.

A 3D MRI-based atlas of a lizard brain.

PubMed

Hoops, Daniel; Desfilis, Ester; Ullmann, Jeremy F P; Janke, Andrew L; Stait-Gardner, Timothy; Devenyi, Gabriel A; Price, William S; Medina, Loreta; Whiting, Martin J; Keogh, J Scott

2018-06-22

Magnetic resonance imaging (MRI) is an established technique for neuroanatomical analysis, being particularly useful in the medical sciences. However, the application of MRI to evolutionary neuroscience is still in its infancy. Few magnetic resonance brain atlases exist outside the standard model organisms in neuroscience and no magnetic resonance atlas has been produced for any reptile brain. A detailed understanding of reptilian brain anatomy is necessary to elucidate the evolutionary origin of enigmatic brain structures such as the cerebral cortex. Here, we present a magnetic resonance atlas for the brain of a representative squamate reptile, the Australian tawny dragon (Agamidae: Ctenophorus decresii), which has been the object of numerous ecological and behavioral studies. We used a high-field 11.74T magnet, a paramagnetic contrasting-enhancing agent and minimum-deformation modeling of the brains of thirteen adult male individuals. From this, we created a high-resolution three-dimensional model of a lizard brain . The 3D-MRI model can be freely downloaded and allows a better comprehension of brain areas, nuclei, and fiber tracts, facilitating comparison with other species and setting the basis for future comparative evolution imaging studies. The MRI model of a tawny dragon brain (Ctenophorus decresii) can be viewed online and downloaded using the Wiley Biolucida Server at wiley.biolucida.net. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Mapping heritability and molecular genetic associations with cortical features using probabilistic brain atlases: methods and applications to schizophrenia.

PubMed

Cannon, Tyrone D; Thompson, Paul M; van Erp, Theo G M; Huttunen, Matti; Lonnqvist, Jouko; Kaprio, Jaakko; Toga, Arthur W

2006-01-01

There is an urgent need to decipher the complex nature of genotype-phenotype relationships within the multiple dimensions of brain structure and function that are compromised in neuropsychiatric syndromes such as schizophrenia. Doing so requires sophisticated methodologies to represent population variability in neural traits and to probe their heritable and molecular genetic bases. We have recently developed and applied computational algorithms to map the heritability of, as well as genetic linkage and association to, neural features encoded using brain imaging in the context of three-dimensional (3D), populationbased, statistical brain atlases. One set of algorithms builds on our prior work using classical twin study methods to estimate heritability by fitting biometrical models for additive genetic, unique, and common environmental influences. Another set of algorithms performs regression-based (Haseman-Elston) identical-bydescent linkage analysis and genetic association analysis of DNA polymorphisms in relation to neural traits of interest in the same 3D population-based brain atlas format. We demonstrate these approaches using samples of healthy monozygotic (MZ) and dizygotic (DZ) twin pairs, as well as MZ and DZ twin pairs discordant for schizophrenia, but the methods can be generalized to other classes of relatives and to other diseases. The results confirm prior evidence of genetic influences on gray matter density in frontal brain regions. They also provide converging evidence that the chromosome 1q42 region is relevant to schizophrenia by demonstrating linkage and association of markers of the Transelin-Associated-Factor-X and Disrupted-In- Schizophrenia-1 genes with prefrontal cortical gray matter deficits in twins discordant for schizophrenia.

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain

PubMed Central

Arganda-Carreras, Ignacio; Manoliu, Tudor; Mazuras, Nicolas; Schulze, Florian; Iglesias, Juan E.; Bühler, Katja; Jenett, Arnim; Rouyer, François; Andrey, Philippe

2018-01-01

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila, one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species. PMID:29628885

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.

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

Evolution of grid-wide access to database resident information in ATLAS using Frontier

NASA Astrophysics Data System (ADS)

Barberis, D.; Bujor, F.; de Stefano, J.; Dewhurst, A. L.; Dykstra, D.; Front, D.; Gallas, E.; Gamboa, C. F.; Luehring, F.; Walker, R.

2012-12-01

The ATLAS experiment deployed Frontier technology worldwide during the initial year of LHC collision data taking to enable user analysis jobs running on the Worldwide LHC Computing Grid to access database resident data. Since that time, the deployment model has evolved to optimize resources, improve performance, and streamline maintenance of Frontier and related infrastructure. In this presentation we focus on the specific changes in the deployment and improvements undertaken, such as the optimization of cache and launchpad location, the use of RPMs for more uniform deployment of underlying Frontier related components, improvements in monitoring, optimization of fail-over, and an increasing use of a centrally managed database containing site specific information (for configuration of services and monitoring). In addition, analysis of Frontier logs has allowed us a deeper understanding of problematic queries and understanding of use cases. Use of the system has grown beyond user analysis and subsystem specific tasks such as calibration and alignment, extending into production processing areas, such as initial reconstruction and trigger reprocessing. With a more robust and tuned system, we are better equipped to satisfy the still growing number of diverse clients and the demands of increasingly sophisticated processing and analysis.

Integrating atlas and graph cut methods for right ventricle blood-pool segmentation from cardiac cine MRI

NASA Astrophysics Data System (ADS)

Dangi, Shusil; Linte, Cristian A.

2017-03-01

Segmentation of right ventricle from cardiac MRI images can be used to build pre-operative anatomical heart models to precisely identify regions of interest during minimally invasive therapy. Furthermore, many functional parameters of right heart such as right ventricular volume, ejection fraction, myocardial mass and thickness can also be assessed from the segmented images. To obtain an accurate and computationally efficient segmentation of right ventricle from cardiac cine MRI, we propose a segmentation algorithm formulated as an energy minimization problem in a graph. Shape prior obtained by propagating label from an average atlas using affine registration is incorporated into the graph framework to overcome problems in ill-defined image regions. The optimal segmentation corresponding to the labeling with minimum energy configuration of the graph is obtained via graph-cuts and is iteratively refined to produce the final right ventricle blood pool segmentation. We quantitatively compare the segmentation results obtained from our algorithm to the provided gold-standard expert manual segmentation for 16 cine-MRI datasets available through the MICCAI 2012 Cardiac MR Right Ventricle Segmentation Challenge according to several similarity metrics, including Dice coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.

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.

Search for Dark Matter in events with a hight- pT photon and high missing transverse momentum in ATLAS

NASA Astrophysics Data System (ADS)

Ratti, M. G.

2016-01-01

We present the results of a search for new particles in events with a high-pT photon and high missing transverse momentum with the ATLAS experiment at the LHC. The analysis is performed on the data collected by ATLAS at a centre of mass energy of 8TeV and corresponding to a total integrated luminosity of 20.3 fb-1 . No excess has been found with respect to the Standard Model expectation. A model-independent upper limit on the fiducial cross section for the production of events with a photon and large missing transverse momentum is set. Exclusion limits on the direct pair production of dark matter candidates are presented.

Integration of Russian Tier-1 Grid Center with High Performance Computers at NRC-KI for LHC experiments and beyond HENP

NASA Astrophysics Data System (ADS)

Belyaev, A.; Berezhnaya, A.; Betev, L.; Buncic, P.; De, K.; Drizhuk, D.; Klimentov, A.; Lazin, Y.; Lyalin, I.; Mashinistov, R.; Novikov, A.; Oleynik, D.; Polyakov, A.; Poyda, A.; Ryabinkin, E.; Teslyuk, A.; Tkachenko, I.; Yasnopolskiy, L.

2015-12-01

The LHC experiments are preparing for the precision measurements and further discoveries that will be made possible by higher LHC energies from April 2015 (LHC Run2). The need for simulation, data processing and analysis would overwhelm the expected capacity of grid infrastructure computing facilities deployed by the Worldwide LHC Computing Grid (WLCG). To meet this challenge the integration of the opportunistic resources into LHC computing model is highly important. The Tier-1 facility at Kurchatov Institute (NRC-KI) in Moscow is a part of WLCG and it will process, simulate and store up to 10% of total data obtained from ALICE, ATLAS and LHCb experiments. In addition Kurchatov Institute has supercomputers with peak performance 0.12 PFLOPS. The delegation of even a fraction of supercomputing resources to the LHC Computing will notably increase total capacity. In 2014 the development a portal combining a Tier-1 and a supercomputer in Kurchatov Institute was started to provide common interfaces and storage. The portal will be used not only for HENP experiments, but also by other data- and compute-intensive sciences like biology with genome sequencing analysis; astrophysics with cosmic rays analysis, antimatter and dark matter search, etc.

EnviroAtlas - Phoenix, AZ - Ecosystem Services by Block Group

EPA Pesticide Factsheets

This dataset presents environmental benefits of the urban forest in 2,434 block groups in Phoenix, Arizona. Carbon attributes, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. Temperature reduction values for Phoenix will be added when they become available. This dataset was produced by the US Forest Service 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).

The 0.125 degree finite-volume General Circulation Model on the NASA Columbia Supercomputer: Preliminary Simulations of Mesoscale Vortices

NASA Technical Reports Server (NTRS)

Shen, B.-W.; Atlas, R.; Chern, J.-D.; Reale, O.; Lin, S.-J.; Lee, T.; Chang, J.

2005-01-01

The NASA Columbia supercomputer was ranked second on the TOP500 List in November, 2004. Such a quantum jump in computing power provides unprecedented opportunities to conduct ultra-high resolution simulations with the finite-volume General Circulation Model (fvGCM). During 2004, the model was run in realtime experimentally at 0.25 degree resolution producing remarkable hurricane forecasts [Atlas et al., 2005]. In 2005, the horizontal resolution was further doubled, which makes the fvGCM comparable to the first mesoscale resolving General Circulation Model at the Earth Simulator Center [Ohfuchi et al., 2004]. Nine 5-day 0.125 degree simulations of three hurricanes in 2004 are presented first for model validation. Then it is shown how the model can simulate the formation of the Catalina eddies and Hawaiian lee vortices, which are generated by the interaction of the synoptic-scale flow with surface forcing, and have never been reproduced in a GCM before.)

Track finding in ATLAS using GPUs

NASA Astrophysics Data System (ADS)

Mattmann, J.; Schmitt, C.

2012-12-01

The reconstruction and simulation of collision events is a major task in modern HEP experiments involving several ten thousands of standard CPUs. On the other hand the graphics processors (GPUs) have become much more powerful and are by far outperforming the standard CPUs in terms of floating point operations due to their massive parallel approach. The usage of these GPUs could therefore significantly reduce the overall reconstruction time per event or allow for the usage of more sophisticated algorithms. In this paper the track finding in the ATLAS experiment will be used as an example on how the GPUs can be used in this context: the implementation on the GPU requires a change in the algorithmic flow to allow the code to work in the rather limited environment on the GPU in terms of memory, cache, and transfer speed from and to the GPU and to make use of the massive parallel computation. Both, the specific implementation of parts of the ATLAS track reconstruction chain and the performance improvements obtained will be discussed.

Modélisation magnétique de la suture ophiolitique de Bou Azzer El Graara (Anti-Atlas central, Maroc). Implications sur la reconstitution géodynamique panafricaine

NASA Astrophysics Data System (ADS)

Soulaimani, Abderrahmane; Jaffal, Mohammed; Maacha, Lhou; Kchikach, Azzouz; Najine, Abdessamad; Saidi, Abdellatif

2006-02-01

Aeromagnetic data of the Anti-Atlas Mountains show an important magnetic anomaly along the 'Major Anti-Atlas Fault', produced by different mafic and ultramafic rocks of a Neoproterozoic ophiolite complex. The magnetic modelling of Bou Azzer-El Graara ophiolitic suture shows a deep-seated anomaly through the upper continental crust corresponding to a north-dipping subduction. The polarity of the Pan-African subduction in the Anti-Atlas is therefore compatible with the contemporaneous Pan-African orogenic belts, where polarity of subduction dipped away from the West African Craton during the amalgamation of Western Gondwana. To cite this article: A. Soulaimani et al., C. R. Geoscience 338 (2006).

Patch forest: a hybrid framework of random forest and patch-based segmentation

NASA Astrophysics Data System (ADS)

Xie, Zhongliu; Gillies, Duncan

2016-03-01

The development of an accurate, robust and fast segmentation algorithm has long been a research focus in medical computer vision. State-of-the-art practices often involve non-rigidly registering a target image with a set of training atlases for label propagation over the target space to perform segmentation, a.k.a. multi-atlas label propagation (MALP). In recent years, the patch-based segmentation (PBS) framework has gained wide attention due to its advantage of relaxing the strict voxel-to-voxel correspondence to a series of pair-wise patch comparisons for contextual pattern matching. Despite a high accuracy reported in many scenarios, computational efficiency has consistently been a major obstacle for both approaches. Inspired by recent work on random forest, in this paper we propose a patch forest approach, which by equipping the conventional PBS with a fast patch search engine, is able to boost segmentation speed significantly while retaining an equal level of accuracy. In addition, a fast forest training mechanism is also proposed, with the use of a dynamic grid framework to efficiently approximate data compactness computation and a 3D integral image technique for fast box feature retrieval.

Gaudi Evolution for Future Challenges

NASA Astrophysics Data System (ADS)

Clemencic, M.; Hegner, B.; Leggett, C.

2017-10-01

The LHCb Software Framework Gaudi was initially designed and developed almost twenty years ago, when computing was very different from today. It has also been used by a variety of other experiments, including ATLAS, Daya Bay, GLAST, HARP, LZ, and MINERVA. Although it has been always actively developed all these years, stability and backward compatibility have been favoured, reducing the possibilities of adopting new techniques, like multithreaded processing. R&D efforts like GaudiHive have however shown its potential to cope with the new challenges. In view of the LHC second Long Shutdown approaching and to prepare for the computing challenges for the Upgrade of the collider and the detectors, now is a perfect moment to review the design of Gaudi and plan future developments of the project. To do this LHCb, ATLAS and the Future Circular Collider community joined efforts to bring Gaudi forward and prepare it for the upcoming needs of the experiments. We present here how Gaudi will evolve in the next years and the long term development plans.

CASTp 3.0: computed atlas of surface topography of proteins.

PubMed

Tian, Wei; Chen, Chang; Lei, Xue; Zhao, Jieling; Liang, Jie

2018-06-01

Geometric and topological properties of protein structures, including surface pockets, interior cavities and cross channels, are of fundamental importance for proteins to carry out their functions. Computed Atlas of Surface Topography of proteins (CASTp) is a web server that provides online services for locating, delineating and measuring these geometric and topological properties of protein structures. It has been widely used since its inception in 2003. In this article, we present the latest version of the web server, CASTp 3.0. CASTp 3.0 continues to provide reliable and comprehensive identifications and quantifications of protein topography. In addition, it now provides: (i) imprints of the negative volumes of pockets, cavities and channels, (ii) topographic features of biological assemblies in the Protein Data Bank, (iii) improved visualization of protein structures and pockets, and (iv) more intuitive structural and annotated information, including information of secondary structure, functional sites, variant sites and other annotations of protein residues. The CASTp 3.0 web server is freely accessible at http://sts.bioe.uic.edu/castp/.

Challenges to Software/Computing for Experimentation at the LHC

NASA Astrophysics Data System (ADS)

Banerjee, Sunanda

The demands of future high energy physics experiments towards software and computing have led the experiments to plan the related activities as a full-fledged project and to investigate new methodologies and languages to meet the challenges. The paths taken by the four LHC experiments ALICE, ATLAS, CMS and LHCb are coherently put together in an LHC-wide framework based on Grid technology. The current status and understandings have been broadly outlined.

Polyphased Inversions of an Intracontinental Rift: Case Study of the Marrakech High Atlas, Morocco

NASA Astrophysics Data System (ADS)

Leprêtre, R.; Missenard, Y.; Barbarand, J.; Gautheron, C.; Jouvie, I.; Saddiqi, O.

2018-03-01

The High and Middle Atlas intraplate belts in Morocco correspond to Mesozoic rifted basins inverted during the Cenozoic during Africa/Eurasia convergence. The Marrakech High Atlas lies at a key location between Atlantic and Tethyan influences during the Mesozoic rifting phase but represents today high reliefs. Age and style of deformation and the mechanisms underlying the Cenozoic inversion are nevertheless still debated. To solve this issue, we produced new low-temperature thermochronology data (fission track and [U-Th]/He on apatite). Two cross sections were investigated in the western and eastern Marrakech High Atlas. Results of inverse modeling allow recognizing five cooling events attributed to erosion since Early Jurassic. Apart from a first erosional event from Middle/Late Jurassic to Early Cretaceous, four stages can be related to the convergence processes between Africa and Europe since the Late Cretaceous. Our data and thermal modeling results suggest that the inversion processes are guided at first order by the fault network inherited from the rifting episodes. The sedimentary cover and the Neogene lithospheric thinning produced a significant thermal weakening that facilitated the inversion of this ancient rift. Our data show that the Marrakech High Atlas has been behaving as a giant pop-up since the beginning of Cenozoic inversion stages.

The Pig PeptideAtlas: A resource for systems biology in animal production and biomedicine.

PubMed

Hesselager, Marianne O; Codrea, Marius C; Sun, Zhi; Deutsch, Eric W; Bennike, Tue B; Stensballe, Allan; Bundgaard, Louise; Moritz, Robert L; Bendixen, Emøke

2016-02-01

Biological research of Sus scrofa, the domestic pig, is of immediate relevance for food production sciences, and for developing pig as a model organism for human biomedical research. Publicly available data repositories play a fundamental role for all biological sciences, and protein data repositories are in particular essential for the successful development of new proteomic methods. Cumulative proteome data repositories, including the PeptideAtlas, provide the means for targeted proteomics, system-wide observations, and cross-species observational studies, but pigs have so far been underrepresented in existing repositories. We here present a significantly improved build of the Pig PeptideAtlas, which includes pig proteome data from 25 tissues and three body fluid types mapped to 7139 canonical proteins. The content of the Pig PeptideAtlas reflects actively ongoing research within the veterinary proteomics domain, and this article demonstrates how the expression of isoform-unique peptides can be observed across distinct tissues and body fluids. The Pig PeptideAtlas is a unique resource for use in animal proteome research, particularly biomarker discovery and for preliminary design of SRM assays, which are equally important for progress in research that supports farm animal production and veterinary health, as for developing pig models with relevance to human health research. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Pig PeptideAtlas: a resource for systems biology in animal production and biomedicine

PubMed Central

Hesselager, Marianne O.; Codrea, Marius C.; Sun, Zhi; Deutsch, Eric W.; Bennike, Tue B.; Stensballe, Allan; Bundgaard, Louise; Moritz, Robert L.; Bendixen, Emøke

2016-01-01

Biological research of Sus scrofa, the domestic pig, is of immediate relevance for food production sciences, and for developing pig as a model organism for human biomedical research. Publicly available data repositories play a fundamental role for all biological sciences, and protein data repositories are in particular essential for the successful development of new proteomic methods. Cumulative proteome data repositories, including the PeptideAtlas, provide the means for targeted proteomics, system wide observations, and cross species observational studies, but pigs have so far been underrepresented in existing repositories. We here present a significantly improved build of the Pig PeptideAtlas, which includes pig proteome data from 25 tissues and three body fluid types mapped to 7139 canonical proteins. The content of the Pig PeptideAtlas reflects actively ongoing research within the veterinary proteomics domain, and this manuscript demonstrates how the expression of isoform-unique peptides can be observed across distinct tissues and body fluids. The Pig PeptideAtlas is a unique resource for use in animal proteome research, particularly biomarker discovery and for preliminary design of SRM assays, which are equally important for progress in research that supports farm animal production and veterinary health, as for developing pig models with relevance to human health research. PMID:26699206

Atlas 1.1: An Update to the Theory of Effective Systems Engineers

DTIC Science & Technology

2018-01-16

Proficiency Model ........................................................................................................... 21 5.1.1 Area 1: Math ... Math /Science/General Engineering: Foundational concepts from mathematics, physical sciences, and general engineering; 2. System’s Domain...Table 5. Atlas Proficiency Areas, Categories, and Topics Area Category Topic 1. Math / Science / General Engineering 1.1. Natural Science

New H-band Stellar Spectral Libraries for the SDSS-III/APOGEE Survey

NASA Astrophysics Data System (ADS)

Zamora, O.; García-Hernández, D. A.; Allende Prieto, C.; Carrera, R.; Koesterke, L.; Edvardsson, B.; Castelli, F.; Plez, B.; Bizyaev, D.; Cunha, K.; García Pérez, A. E.; Gustafsson, B.; Holtzman, J. A.; Lawler, J. E.; Majewski, S. R.; Manchado, A.; Mészáros, Sz.; Shane, N.; Shetrone, M.; Smith, V. V.; Zasowski, G.

2015-06-01

The Sloan Digital Sky Survey-III (SDSS-III) Apache Point Observatory Galactic Evolution Experiment (APOGEE) has obtained high-resolution (R ˜ 22,500), high signal-to-noise ratio (\\gt 100) spectra in the H-band (˜1.5-1.7 μm) for about 146,000 stars in the Milky Way galaxy. We have computed spectral libraries with effective temperature ({{T}eff}) ranging from 3500 to 8000 K for the automated chemical analysis of the survey data. The libraries, used to derive stellar parameters and abundances from the APOGEE spectra in the SDSS-III data release 12 (DR12), are based on ATLAS9 model atmospheres and the ASSɛT spectral synthesis code. We present a second set of libraries based on MARCS model atmospheres and the spectral synthesis code Turbospectrum. The ATLAS9/ASSɛT ({{T}eff} = 3500-8000 K) and MARCS/Turbospectrum ({{T}eff} = 3500-5500 K) grids cover a wide range of metallicity (-2.5 ≤slant [M/H] ≤slant +0.5 dex), surface gravity (0 ≤ log g ≤slant 5 dex), microturbulence (0.5 ≤slant ξ ≤slant 8 km s-1), carbon (-1 ≤slant [C/M] ≤slant +1 dex), nitrogen (-1 ≤slant [N/M] ≤slant +1 dex), and α-element (-1 ≤slant [α/M] ≤slant +1 dex) variations, having thus seven dimensions. We compare the ATLAS9/ASSɛT and MARCS/Turbospectrum libraries and apply both of them to the analysis of the observed H-band spectra of the Sun and the K2 giant Arcturus, as well as to a selected sample of well-known giant stars observed at very high resolution. The new APOGEE libraries are publicly available and can be employed for chemical studies in the H-band using other high-resolution spectrographs.

Study of CPM Device used for Rehabilitation and Effective Pain Management Following Knee Alloplasty

NASA Astrophysics Data System (ADS)

Trochimczuk, R.; Kuźmierowski, T.; Anchimiuk, P.

2017-02-01

This paper defines the design assumptions for the construction of an original demonstration of a CPM device, based on which a solid virtual model will be created in a CAD software environment. The overall dimensions and other input parameters for the design were determined for the entire patient population according to an anatomical atlas of human measures. The medical and physiotherapeutic community were also consulted with respect to the proposed engineering solutions. The virtual model of the CPM device that will be created will be used for computer simulations of changes in motion parameters as a function of time, accounting for loads and static states. The results obtained from computer simulation will be used to confirm the correctness of the design adopted assumptions and of the accepted structure of the CPM mechanism, and potentially to introduce necessary corrections. They will also provide a basis for the development of a control strategy for the laboratory prototype and for the selection of the strategy of the patient's rehabilitation in the future. This paper will be supplemented with identification of directions of further research.

T.D.S. spectroscopic databank for spherical tops: DOS version

NASA Astrophysics Data System (ADS)

Tyuterev, V. G.; Babikov, Yu. L.; Tashkun, S. A.; Perevalov, V. I.; Nikitin, A.; Champion, J.-P.; Wenger, C.; Pierre, C.; Pierre, G.; Hilico, J.-C.; Loete, M.

1994-10-01

T.D.S. (Traitement de Donnees Spectroscopiques or Tomsk-Dijon-Spectroscopy project) is a computer package concerned with high resolution spectroscopy of spherical top molecules like CH4, CF4, SiH4, SiF4, SnH4, GeH4, SF6, etc. T.D.S. contains information, fundamental spectroscopic data (energies, transition moments, spectroscopic constants) recovered from comprehensive modeling and simultaneous fitting of experimental spectra, and associated software written in C. The T.D.S. goal is to provide an access to all available information on vibration-rotation molecular states and transitions including various spectroscopic processes (Stark, Raman, etc.) under extended conditions based on extrapolations of laboratory measurements using validated theoretical models. Applications for T.D.S. may include: education/training in molecular physics, quantum chemistry, laser physics; spectroscopic applications (analysis, laser spectroscopy, atmospheric optics, optical standards, spectroscopic atlases); applications to environment studies and atmospheric physics (remote sensing); data supply for specific databases; and to photochemistry (laser excitation, multiphoton processes). The reported DOS-version is designed for IBM and compatible personal computers.

The Herschel ATLAS

NASA Technical Reports Server (NTRS)

Eales, S.; Dunne, L.; Clements, D.; Cooray, A.; De Zotti, G.; Dye, S.; Ivison, R.; Jarvis, M.; Lagache, G.; Maddox, S.;

SpS1-The Spitzer atlas of stellar spectra

NASA Astrophysics Data System (ADS)

Ardila, David R.; Makowiecki, W.; van Dyk, S.; Song, I.; Stauffer, J.; Rho, J.; Fajardo-Acosta, S.; Hoard, D. W.; Wachter, S.

2010-11-01

We present Spitzer Space Telescope spectra of 147 stars (R~64 - 128, λλ = 5 - 35 μm, S/N~100) covering most spectral and luminosity classes within the HR diagram. The spectra are available from the NASA/IPAC Infrared Science Archive (IRSA) and from the first author's webpage (http://web.ipac.caltech.edu/staff/ardila/Atlas/). The Atlas contains spectra of ‘typical’ stars, which may serve to refine galactic synthesis models, study stellar atmospheres, and establish a legacy for future IR missions, such as JWST.

EnviroAtlas - Minimum Temperature 1950 - 2099 for the Conterminous United States

EPA Pesticide Factsheets

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly minimum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly minimum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. 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).

EnviroAtlas - Precipitation 1950 - 2099 for the Conterminous United States

EPA Pesticide Factsheets

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly precipitation rate for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly precipitation rate for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. 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).

EnviroAtlas - Maximum Temperature 1950 - 2099 for the Conterminous United States

EPA Pesticide Factsheets

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly maximum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly maximum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. 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).

Atlas-based segmentation technique incorporating inter-observer delineation uncertainty for whole breast

NASA Astrophysics Data System (ADS)

Bell, L. R.; Dowling, J. A.; Pogson, E. M.; Metcalfe, P.; Holloway, L.

2017-01-01

Accurate, efficient auto-segmentation methods are essential for the clinical efficacy of adaptive radiotherapy delivered with highly conformal techniques. Current atlas based auto-segmentation techniques are adequate in this respect, however fail to account for inter-observer variation. An atlas-based segmentation method that incorporates inter-observer variation is proposed. This method is validated for a whole breast radiotherapy cohort containing 28 CT datasets with CTVs delineated by eight observers. To optimise atlas accuracy, the cohort was divided into categories by mean body mass index and laterality, with atlas’ generated for each in a leave-one-out approach. Observer CTVs were merged and thresholded to generate an auto-segmentation model representing both inter-observer and inter-patient differences. For each category, the atlas was registered to the left-out dataset to enable propagation of the auto-segmentation from atlas space. Auto-segmentation time was recorded. The segmentation was compared to the gold-standard contour using the dice similarity coefficient (DSC) and mean absolute surface distance (MASD). Comparison with the smallest and largest CTV was also made. This atlas-based auto-segmentation method incorporating inter-observer variation was shown to be efficient (<4min) and accurate for whole breast radiotherapy, with good agreement (DSC>0.7, MASD <9.3mm) between the auto-segmented contours and CTV volumes.

Bayesian longitudinal segmentation of hippocampal substructures in brain MRI using subject-specific atlases.

PubMed

Iglesias, Juan Eugenio; Van Leemput, Koen; Augustinack, Jean; Insausti, Ricardo; Fischl, Bruce; Reuter, Martin

2016-11-01

The hippocampal formation is a complex, heterogeneous structure that consists of a number of distinct, interacting subregions. Atrophy of these subregions is implied in a variety of neurodegenerative diseases, most prominently in Alzheimer's disease (AD). Thanks to the increasing resolution of MR images and computational atlases, automatic segmentation of hippocampal subregions is becoming feasible in MRI scans. Here we introduce a generative model for dedicated longitudinal segmentation that relies on subject-specific atlases. The segmentations of the scans at the different time points are jointly computed using Bayesian inference. All time points are treated the same to avoid processing bias. We evaluate this approach using over 4700 scans from two publicly available datasets (ADNI and MIRIAD). In test-retest reliability experiments, the proposed method yielded significantly lower volume differences and significantly higher Dice overlaps than the cross-sectional approach for nearly every subregion (average across subregions: 4.5% vs. 6.5%, Dice overlap: 81.8% vs. 75.4%). The longitudinal algorithm also demonstrated increased sensitivity to group differences: in MIRIAD (69 subjects: 46 with AD and 23 controls), it found differences in atrophy rates between AD and controls that the cross sectional method could not detect in a number of subregions: right parasubiculum, left and right presubiculum, right subiculum, left dentate gyrus, left CA4, left HATA and right tail. In ADNI (836 subjects: 369 with AD, 215 with early cognitive impairment - eMCI - and 252 controls), all methods found significant differences between AD and controls, but the proposed longitudinal algorithm detected differences between controls and eMCI and differences between eMCI and AD that the cross sectional method could not find: left presubiculum, right subiculum, left and right parasubiculum, left and right HATA. Moreover, many of the differences that the cross-sectional method already found were detected with higher significance. The presented algorithm will be made available as part of the open-source neuroimaging package FreeSurfer. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

An Atlas of ShakeMaps and population exposure catalog for earthquake loss modeling

USGS Publications Warehouse

Allen, T.I.; Wald, D.J.; Earle, P.S.; Marano, K.D.; Hotovec, A.J.; Lin, K.; Hearne, M.G.

2009-01-01

We present an Atlas of ShakeMaps and a catalog of human population exposures to moderate-to-strong ground shaking (EXPO-CAT) for recent historical earthquakes (1973-2007). The common purpose of the Atlas and exposure catalog is to calibrate earthquake loss models to be used in the US Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER). The full ShakeMap Atlas currently comprises over 5,600 earthquakes from January 1973 through December 2007, with almost 500 of these maps constrained-to varying degrees-by instrumental ground motions, macroseismic intensity data, community internet intensity observations, and published earthquake rupture models. The catalog of human exposures is derived using current PAGER methodologies. Exposure to discrete levels of shaking intensity is obtained by correlating Atlas ShakeMaps with a global population database. Combining this population exposure dataset with historical earthquake loss data, such as PAGER-CAT, provides a useful resource for calibrating loss methodologies against a systematically-derived set of ShakeMap hazard outputs. We illustrate two example uses for EXPO-CAT; (1) simple objective ranking of country vulnerability to earthquakes, and; (2) the influence of time-of-day on earthquake mortality. In general, we observe that countries in similar geographic regions with similar construction practices tend to cluster spatially in terms of relative vulnerability. We also find little quantitative evidence to suggest that time-of-day is a significant factor in earthquake mortality. Moreover, earthquake mortality appears to be more systematically linked to the population exposed to severe ground shaking (Modified Mercalli Intensity VIII+). Finally, equipped with the full Atlas of ShakeMaps, we merge each of these maps and find the maximum estimated peak ground acceleration at any grid point in the world for the past 35 years. We subsequently compare this "composite ShakeMap" with existing global hazard models, calculating the spatial area of the existing hazard maps exceeded by the combined ShakeMap ground motions. In general, these analyses suggest that existing global, and regional, hazard maps tend to overestimate hazard. Both the Atlas of ShakeMaps and EXPO-CAT have many potential uses for examining earthquake risk and epidemiology. All of the datasets discussed herein are available for download on the PAGER Web page ( http://earthquake.usgs.gov/ eqcenter/pager/prodandref/ ). ?? 2009 Springer Science+Business Media B.V.

Search for strong production of supersymmetric particles in final states with missing transverse momentum and at least three b-jets at $$ \\sqrt{s} = 8 $$ TeV proton-proton collisions with the ATLAS detector

DOE PAGES

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

2014-10-03

We report the results of a search for strong production of supersymmetric particles in 20.1 fb ₋1 of proton-proton collisions at a centre-of-mass energy of 8TeV using the ATLAS detector at the LHC. The search is performed separately in events with either zero or at least one high-p T lepton (electron or muon), large missing transverse momentum, high jet multiplicity and at least three jets identified as originated from the fragmentation of a b-quark. No excess is observed with respect to the Standard Model predictions. The results are interpreted in the context of several supersymmetric models involving gluinos and scalarmore » top and bottom quarks, as well as a mSUGRA/CMSSM model. Lastly, gluino masses up to 1340 GeV are excluded, depending on the model, significantly extending the previous ATLAS limits.« less

The Las Vegas Sustainability Atlas: Modeling Place-based Interactions and Implications in the Las Vegas Valley Bioregion

NASA Astrophysics Data System (ADS)

Ego, H.; McCown, K.; Saghafi, N.; Gross, E.; Hunter, W.; Zawarus, P.; Gann, A.; Piechota, T. C.

2014-12-01

Las Vegas, Nevada, with 2 million residents and 40 million annual visitors, is one of the driest metropolitan environments of its size in the world. The metro imports nearly all of its resources, including energy, water and food. Rapid population increases, drought, and temperature increases due to climate change create challenges for planning resilient systems in the Las Vegas Valley. Because of its growth rate, aridity, Las Vegas, Nevada is a significant and relevant region for the study of the water, energy, food and climate nexus. Cities in the United States and the world are seeing increasing trends in urbanization and water scarcity. How does the water-energy-climate-food nexus affect each metropolitan area? How can this complex information be used for resiliency planning? How can it be related to the public, so they can understand the issues in a way that makes them meaningful participants in the planning process? The topic of our presentation is a 'resiliency atlas.' The atlas is a place-based model tested in Las Vegas to explore bioregional distinctiveness of the water-energy-climate-food nexus, including regional transportation systems. The atlas integrates the systems within a utilitarian organization of information. Systems in this place-based model demonstrate how infrastructure services are efficiently provided for the Las Vegas Valley population. This resiliency atlas can clarify how the nexus applies to place; and how it can be used to spur geographically germane adaption strategies. In the Las Vegas Valley, climate change (drought and high sustained temperatures) and population affect water, energy, and food systems. This clarity of a place based model can help educate the public about the resilience of their place, and facilitate and organize the planning process in the face of uncertainty.