A report on the Academic Emergency Medicine 2015 consensus conference "Diagnostic imaging in the emergency department: a research agenda to optimize utilization".

PubMed

Gunn, Martin L; Marin, Jennifer R; Mills, Angela M; Chong, Suzanne T; Froemming, Adam T; Johnson, Jamlik O; Kumaravel, Manickam; Sodickson, Aaron D

2016-08-01

In May 2015, the Academic Emergency Medicine consensus conference "Diagnostic imaging in the emergency department: a research agenda to optimize utilization" was held. The goal of the conference was to develop a high-priority research agenda regarding emergency diagnostic imaging on which to base future research. In addition to representatives from the Society of Academic Emergency Medicine, the multidisciplinary conference included members of several radiology organizations: American Society for Emergency Radiology, Radiological Society of North America, the American College of Radiology, and the American Association of Physicists in Medicine. The specific aims of the conference were to (1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging utilization and identify key opportunities, limitations, and gaps in knowledge; (2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and (3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Through a multistep consensus process, participants developed targeted research questions for future research in six content areas within emergency diagnostic imaging: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use.

The influence of stimulus format on drawing--a functional imaging study of decision making in portrait drawing.

PubMed

Miall, R C; Nam, Se-Ho; Tchalenko, J

2014-11-15

To copy a natural visual image as a line drawing, visual identification and extraction of features in the image must be guided by top-down decisions, and is usually influenced by prior knowledge. In parallel with other behavioral studies testing the relationship between eye and hand movements when drawing, we report here a functional brain imaging study in which we compared drawing of faces and abstract objects: the former can be strongly guided by prior knowledge, the latter less so. To manipulate the difficulty in extracting features to be drawn, each original image was presented in four formats including high contrast line drawings and silhouettes, and as high and low contrast photographic images. We confirmed the detailed eye-hand interaction measures reported in our other behavioral studies by using in-scanner eye-tracking and recording of pen movements with a touch screen. We also show that the brain activation pattern reflects the changes in presentation formats. In particular, by identifying the ventral and lateral occipital areas that were more highly activated during drawing of faces than abstract objects, we found a systematic increase in differential activation for the face-drawing condition, as the presentation format made the decisions more challenging. This study therefore supports theoretical models of how prior knowledge may influence perception in untrained participants, and lead to experience-driven perceptual modulation by trained artists. Copyright © 2014. Published by Elsevier Inc.

Accelerated T1ρ acquisition for knee cartilage quantification using compressed sensing and data-driven parallel imaging: A feasibility study.

PubMed

Pandit, Prachi; Rivoire, Julien; King, Kevin; Li, Xiaojuan

2016-03-01

Quantitative T1ρ imaging is beneficial for early detection for osteoarthritis but has seen limited clinical use due to long scan times. In this study, we evaluated the feasibility of accelerated T1ρ mapping for knee cartilage quantification using a combination of compressed sensing (CS) and data-driven parallel imaging (ARC-Autocalibrating Reconstruction for Cartesian sampling). A sequential combination of ARC and CS, both during data acquisition and reconstruction, was used to accelerate the acquisition of T1ρ maps. Phantom, ex vivo (porcine knee), and in vivo (human knee) imaging was performed on a GE 3T MR750 scanner. T1ρ quantification after CS-accelerated acquisition was compared with non CS-accelerated acquisition for various cartilage compartments. Accelerating image acquisition using CS did not introduce major deviations in quantification. The coefficient of variation for the root mean squared error increased with increasing acceleration, but for in vivo measurements, it stayed under 5% for a net acceleration factor up to 2, where the acquisition was 25% faster than the reference (only ARC). To the best of our knowledge, this is the first implementation of CS for in vivo T1ρ quantification. These early results show that this technique holds great promise in making quantitative imaging techniques more accessible for clinical applications. © 2015 Wiley Periodicals, Inc.

Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends.

PubMed

Geerts, Hugo; Hofmann-Apitius, Martin; Anastasio, Thomas J

2017-11-01

Neurodegenerative diseases such as Alzheimer's disease (AD) follow a slowly progressing dysfunctional trajectory, with a large presymptomatic component and many comorbidities. Using preclinical models and large-scale omics studies ranging from genetics to imaging, a large number of processes that might be involved in AD pathology at different stages and levels have been identified. The sheer number of putative hypotheses makes it almost impossible to estimate their contribution to the clinical outcome and to develop a comprehensive view on the pathological processes driving the clinical phenotype. Traditionally, bioinformatics approaches have provided correlations and associations between processes and phenotypes. Focusing on causality, a new breed of advanced and more quantitative modeling approaches that use formalized domain expertise offer new opportunities to integrate these different modalities and outline possible paths toward new therapeutic interventions. This article reviews three different computational approaches and their possible complementarities. Process algebras, implemented using declarative programming languages such as Maude, facilitate simulation and analysis of complicated biological processes on a comprehensive but coarse-grained level. A model-driven Integration of Data and Knowledge, based on the OpenBEL platform and using reverse causative reasoning and network jump analysis, can generate mechanistic knowledge and a new, mechanism-based taxonomy of disease. Finally, Quantitative Systems Pharmacology is based on formalized implementation of domain expertise in a more fine-grained, mechanism-driven, quantitative, and predictive humanized computer model. We propose a strategy to combine the strengths of these individual approaches for developing powerful modeling methodologies that can provide actionable knowledge for rational development of preventive and therapeutic interventions. Development of these computational approaches is likely to be required for further progress in understanding and treating AD. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

Object localization in handheld thermal images for fireground understanding

NASA Astrophysics Data System (ADS)

Vandecasteele, Florian; Merci, Bart; Jalalvand, Azarakhsh; Verstockt, Steven

2017-05-01

Despite the broad application of the handheld thermal imaging cameras in firefighting, its usage is mostly limited to subjective interpretation by the person carrying the device. As remedies to overcome this limitation, object localization and classification mechanisms could assist the fireground understanding and help with the automated localization, characterization and spatio-temporal (spreading) analysis of the fire. An automated understanding of thermal images can enrich the conventional knowledge-based firefighting techniques by providing the information from the data and sensing-driven approaches. In this work, transfer learning is applied on multi-labeling convolutional neural network architectures for object localization and recognition in monocular visual, infrared and multispectral dynamic images. Furthermore, the possibility of analyzing fire scene images is studied and their current limitations are discussed. Finally, the understanding of the room configuration (i.e., objects location) for indoor localization in reduced visibility environments and the linking with Building Information Models (BIM) are investigated.

Set-relevance determines the impact of distractors on episodic memory retrieval.

PubMed

Kwok, Sze Chai; Shallice, Tim; Macaluso, Emiliano

2014-09-01

We investigated the interplay between stimulus-driven attention and memory retrieval with a novel interference paradigm that engaged both systems concurrently on each trial. Participants encoded a 45-min movie on Day 1 and, on Day 2, performed a temporal order judgment task during fMRI. Each retrieval trial comprised three images presented sequentially, and the task required participants to judge the temporal order of the first and the last images ("memory probes") while ignoring the second image, which was task irrelevant ("attention distractor"). We manipulated the content relatedness and the temporal proximity between the distractor and the memory probes, as well as the temporal distance between two probes. Behaviorally, short temporal distances between the probes led to reduced retrieval performance. Distractors that at encoding were temporally close to the first probe image reduced these costs, specifically when the distractor was content unrelated to the memory probes. The imaging results associated the distractor probe temporal proximity with activation of the right ventral attention network. By contrast, the precuneus was activated for high-content relatedness between distractors and probes and in trials including a short distance between the two memory probes. The engagement of the right ventral attention network by specific types of distractors suggests a link between stimulus-driven attention control and episodic memory retrieval, whereas the activation pattern of the precuneus implicates this region in memory search within knowledge/content-based hierarchies.

Histogram-driven cupping correction (HDCC) in CT

NASA Astrophysics Data System (ADS)

Kyriakou, Y.; Meyer, M.; Lapp, R.; Kalender, W. A.

2010-04-01

Typical cupping correction methods are pre-processing methods which require either pre-calibration measurements or simulations of standard objects to approximate and correct for beam hardening and scatter. Some of them require the knowledge of spectra, detector characteristics, etc. The aim of this work was to develop a practical histogram-driven cupping correction (HDCC) method to post-process the reconstructed images. We use a polynomial representation of the raw-data generated by forward projection of the reconstructed images; forward and backprojection are performed on graphics processing units (GPU). The coefficients of the polynomial are optimized using a simplex minimization of the joint entropy of the CT image and its gradient. The algorithm was evaluated using simulations and measurements of homogeneous and inhomogeneous phantoms. For the measurements a C-arm flat-detector CT (FD-CT) system with a 30×40 cm2 detector, a kilovoltage on board imager (radiation therapy simulator) and a micro-CT system were used. The algorithm reduced cupping artifacts both in simulations and measurements using a fourth-order polynomial and was in good agreement to the reference. The minimization algorithm required less than 70 iterations to adjust the coefficients only performing a linear combination of basis images, thus executing without time consuming operations. HDCC reduced cupping artifacts without the necessity of pre-calibration or other scan information enabling a retrospective improvement of CT image homogeneity. However, the method can work with other cupping correction algorithms or in a calibration manner, as well.

Knowledge-based segmentation and feature analysis of hand and wrist radiographs

NASA Astrophysics Data System (ADS)

Efford, Nicholas D.

1993-07-01

The segmentation of hand and wrist radiographs for applications such as skeletal maturity assessment is best achieved by model-driven approaches incorporating anatomical knowledge. The reasons for this are discussed, and a particular frame-based or 'blackboard' strategy for the simultaneous segmentation of the hand and estimation of bone age via the TW2 method is described. The new approach is structured for optimum robustness and computational efficiency: features of interest are detected and analyzes in order of their size and prominence in the image, the largest and most distinctive being dealt with first, and the evidence generated by feature analysis is used to update a model of hand anatomy and hence guide later stages of the segmentation. Closed bone boundaries are formed by a hybrid technique combining knowledge-based, one-dimensional edge detection with model-assisted heuristic tree searching.

Diagnostic imaging for chronic orofacial pain, maxillofacial osseous and soft tissue pathology and temporomandibular disorders.

PubMed

Shintaku, Werner; Enciso, Reyes; Broussard, Jack; Clark, Glenn T

2006-08-01

Since dentists can be faced by unusual cases during their professional life, this article reviews the common orofacial disorders that are of concern to a dentist trying to diagnose the source of pain or dysfunction symptoms, providing an overview of the essential knowledge and usage of nowadays available advanced diagnostic imaging modalities. In addition to symptom-driven diagnostic dilemmas, where such imaging is utilized, occasionally there are asymptomatic anomalies discovered by routine clinical care and/or on dental or panoramic images that need more discussion. The correct selection criteria of an image exam should be based on the individual characteristics of the patient, and the type of imaging technique should be selected depending on the specific clinical problem, the kind of tissue to be visualized, the information obtained from the imaging modality, radiation exposure, and the cost of the examination. The usage of more specialized imaging modalities such as magnetic resonance imaging, computed tomography, ultrasound, as well as single photon computed tomography, positron electron tomography, and their hybrid machines, SPECT/ CT and PET/CT, are discussed.

Evaluation in the Design of Complex Systems

ERIC Educational Resources Information Center

Ho, Li-An; Schwen, Thomas M.

2006-01-01

We identify literature that argues the process of creating knowledge-based system is often imbalanced. In most knowledge-based systems, development is often technology-driven instead of requirement-driven. Therefore, we argue designers must recognize that evaluation is a critical link in the application of requirement-driven development models…

Explosive Chromospheric Evaporation Driven by Nonthermal Electrons around One Footpoint of a Solar Flare Loop

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

Li, D.; Ning, Z. J.; Huang, Y.

We explore the temporal relationship between microwave/hard X-ray (HXR) emission and Doppler velocity during the impulsive phase of a solar flare on 2014 October 27 (SOL2014-10-27) that displays a pulse on the light curves in the microwave (34 GHz) and HXR (25–50 keV) bands before the flare maximum. Imaging observation shows that this pulse mainly comes from one footpoint of a solar flare loop. The slit of the Interface Region Imaging Spectrograph ( IRIS ) stays at this footpoint during this solar flare. The Doppler velocities of Fe xxi 1354.09 Å and Si iv 1402.77 Å are extracted from themore » Gaussian fitting method. We find that the hot line of Fe xxi 1354.09 Å (log T ∼ 7.05) in the corona exhibits blueshift, while the cool line of Si iv 1402.77 Å (log T ∼ 4.8) in the transition region exhibits redshift, indicating explosive chromospheric evaporation. Evaporative upflows along the flare loop are also observed in the AIA 131 Å image. To our knowledge, this is the first report of chromospheric evaporation evidence from both spectral and imaging observations in the same flare. Both microwave and HXR pulses are well correlated with the Doppler velocities, suggesting that the chromospheric evaporation is driven by nonthermal electrons around this footpoint of a solar flare loop.« less

Developing a Research Agenda to Optimize Diagnostic Imaging in the Emergency Department: An Executive Summary of the 2015 Academic Emergency Medicine Consensus Conference.

PubMed

Marin, Jennifer R; Mills, Angela M

2015-12-01

The 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization" was held on May 12, 2015, with the goal of developing a high-priority research agenda on which to base future research. The specific aims of the conference were to (1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging use and identify key opportunities, limitations, and gaps in knowledge; (2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and (3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Over a 2-year period, the executive committee and other experts in the field convened regularly to identify specific areas in need of future research. Six content areas within emergency diagnostic imaging were identified before the conference and served as the breakout groups on which consensus was achieved: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use. The executive committee invited key stakeholders to assist with the planning and to participate in the consensus conference to generate a multidisciplinary agenda. There were a total of 164 individuals involved in the conference and spanned various specialties, including general emergency medicine, pediatric emergency medicine, radiology, surgery, medical physics, and the decision sciences.

Receptive fields selection for binary feature description.

PubMed

Fan, Bin; Kong, Qingqun; Trzcinski, Tomasz; Wang, Zhiheng; Pan, Chunhong; Fua, Pascal

2014-06-01

Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning-based methods for designing local descriptor become more and more popular because of their good performance and data-driven property. This paper proposes a novel data-driven method for designing binary feature descriptor, which we call receptive fields descriptor (RFD). Technically, RFD is constructed by thresholding responses of a set of receptive fields, which are selected from a large number of candidates according to their distinctiveness and correlations in a greedy way. Using two different kinds of receptive fields (namely rectangular pooling area and Gaussian pooling area) for selection, we obtain two binary descriptors RFDR and RFDG .accordingly. Image matching experiments on the well-known patch data set and Oxford data set demonstrate that RFD significantly outperforms the state-of-the-art binary descriptors, and is comparable with the best float-valued descriptors at a fraction of processing time. Finally, experiments on object recognition tasks confirm that both RFDR and RFDG successfully bridge the performance gap between binary descriptors and their floating-point competitors.

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

The semiotics of medical image Segmentation.

PubMed

Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M

2018-02-01

As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

Knowledge-driven institutional change: an empirical study on combating desertification in northern China from 1949 to 2004.

PubMed

Yang, Lihua; Wu, Jianguo

2012-11-15

Understanding institutional changes is crucial for environmental management. Here we investigated how institutional changes influenced the process and result of desertification control in northern China between 1949 and 2004. Our analysis was based on a case study of 21 field sites and a meta-analysis of additional 29 sites reported in the literature. Our results show that imposed knowledge-driven institutional change was often perceived as a more progressive, scientific, and rational type of institutional change by entrepreneurs, scholars, experts, and technicians, while voluntary, knowledge-driven institutional change based on indigenous knowledge and experiences of local populations was discouraged. Our findings also demonstrate that eight working rules of imposed knowledge-driven institutional change can be applied to control desertification effectively. These rules address the issues of perception of potential gains, entrepreneurs' appeals and support, coordination of multiple goals, collaboration among multiple organizations, interest distribution and conflict resolution, incremental institutional change, external intervention, and coordination among the myriad institutions involved. Imposed knowledge-driven institutional change tended to be more successful when these rules were thoroughly implemented. These findings provide an outline for implementing future institutional changes and policy making to combat desertification and other types of ecological and environmental management. Copyright © 2012 Elsevier Ltd. All rights reserved.

Detection of changes in semi-natural grasslands by cross correlation analysis with WorldView-2 images and new Landsat 8 data.

PubMed

Tarantino, Cristina; Adamo, Maria; Lucas, Richard; Blonda, Palma

2016-03-15

Focusing on a Mediterranean Natura 2000 site in Italy, the effectiveness of the cross correlation analysis (CCA) technique for quantifying change in the area of semi-natural grasslands at different spatial resolutions (grain) was evaluated. In a fine scale analysis (2 m), inputs to the CCA were a) a semi-natural grasslands layer extracted from an existing validated land cover/land use (LC/LU) map (1:5000, time T 1 ) and b) a more recent single date very high resolution (VHR) WorldView-2 image (time T 2 ), with T 2  > T 1 . The changes identified through the CCA were compared against those detected by applying a traditional post-classification comparison (PCC) technique to the same reference T 1 map and an updated T 2 map obtained by a knowledge driven classification of four multi-seasonal Worldview-2 input images. Specific changes observed were those associated with agricultural intensification and fires. The study concluded that prior knowledge (spectral class signatures, awareness of local agricultural practices and pressures) was needed for the selection of the most appropriate image (in terms of seasonality) to be acquired at T 2 . CCA was also applied to the comparison of the existing T 1 map with recent high resolution (HR) Landsat 8 OLS images. The areas of change detected at VHR and HR were broadly similar with larger error values in HR change images.

Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

PubMed

Gang, Grace J; Siewerdsen, Jeffrey H; Stayman, J Webster

2017-12-01

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index ( ) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum by at least 17.8%, but yielded higher over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed . The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.

Stimulus-driven and knowledge-driven processes in attention to warbles

NASA Astrophysics Data System (ADS)

Dowling, W. Jay; Tillmann, Barbara

2003-10-01

Listeners identified warbles differing in amplitude-modulation rate (3-10 Hz). And measured RT while listeners maintained above 90% correct responses. After a practice session listeners identified target warbles following stimulus-driven or knowledge-driven cues. The stimulus-driven cue was a 250-ms ``beep'' at the target pitch (valid) or another pitch (invalid); the knowledge-driven cue was a midrange ``melody'' pointing to the target pitch (always valid). A 500-ms target warble followed the cue after delays of 0-500 ms (250-750 ms SOA). The listener pressed a key to indicate ``slow'' or ``fast.'' RTs were shortest at the briefest delay. In contrast to results from a memory task, RTs here were much shorter, and we found no evidence for IOR or attentional blink. Listeners began generating responses while the target was still sounding. Invalid ``beeps'' slowed responses at the briefest (but not the longer) delays; adding a valid ``beep'' to the valid ``melody'' did not speed responses.

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

Design of a Knowledge Driven HIS

PubMed Central

Pryor, T. Allan; Clayton, Paul D.; Haug, Peter J.; Wigertz, Ove

1987-01-01

Design of the software architecture for a knowledge driven HIS is presented. In our design the frame has been used as the basic unit of knowledge representation. The structure of the frame is being designed to be sufficiently universal to contain knowledge required to implement not only expert systems, but almost all traditional HIS functions including ADT, order entry and results review. The design incorporates a two level format for the knowledge. The first level as ASCII records is used to maintain the knowledge base while the second level converted by special knowledge compilers to standard computer languages is used for efficient implementation of the knowledge applications.

Chocolate smells pink and stripy: Exploring olfactory-visual synesthesia

PubMed Central

Russell, Alex; Stevenson, Richard J.; Rich, Anina N.

2015-01-01

Odors are often difficult to identify, and can be perceived either via the nose or mouth (“flavor”; not usually perceived as a “smell”). These features provide a unique opportunity to contrast conceptual and perceptual accounts of synesthesia. We presented six olfactory-visual synesthetes with a range of odorants. They tried to identify each smell, evaluate its attributes and illustrate their elicited visual experience. Judges rated the similarity of each synesthetes’ illustrations over time (test-retest reliability). Synesthetic images were most similar from the same odor named consistently, but even inconsistently named same odors generated more similar images than different odors. This was driven by hedonic similarity. Odors presented as flavors only resulted in similar images when consistently named. Thus, the primary factor in generating a reliable synesthetic image is the name, with some influence of odor hedonics. Hedonics are a basic form of semantic knowledge, making this consistent with a conceptual basis for synaesthetic links. PMID:25895152

Task-based data-acquisition optimization for sparse image reconstruction systems

NASA Astrophysics Data System (ADS)

Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

2017-03-01

Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

Blocking fatty acid-fueled mROS production within macrophages alleviates acute gouty inflammation.

PubMed

Hall, Christopher J; Sanderson, Leslie E; Lawrence, Lisa M; Pool, Bregina; van der Kroef, Maarten; Ashimbayeva, Elina; Britto, Denver; Harper, Jacquie L; Lieschke, Graham J; Astin, Jonathan W; Crosier, Kathryn E; Dalbeth, Nicola; Crosier, Philip S

2018-05-01

Gout is the most common inflammatory arthritis affecting men. Acute gouty inflammation is triggered by monosodium urate (MSU) crystal deposition in and around joints that activates macrophages into a proinflammatory state, resulting in neutrophil recruitment. A complete understanding of how MSU crystals activate macrophages in vivo has been difficult because of limitations of live imaging this process in traditional animal models. By live imaging the macrophage and neutrophil response to MSU crystals within an intact host (larval zebrafish), we reveal that macrophage activation requires mitochondrial ROS (mROS) generated through fatty acid oxidation. This mitochondrial source of ROS contributes to NF-κB-driven production of IL-1β and TNF-α, which promote neutrophil recruitment. We demonstrate the therapeutic utility of this discovery by showing that this mechanism is conserved in human macrophages and, via pharmacologic blockade, that it contributes to neutrophil recruitment in a mouse model of acute gouty inflammation. To our knowledge, this study is the first to uncover an immunometabolic mechanism of macrophage activation that operates during acute gouty inflammation. Targeting this pathway holds promise in the management of gout and, potentially, other macrophage-driven diseases.

Developing a Research Agenda to Optimize Diagnostic Imaging in the Emergency Department: An Executive Summary of the 2015 Academic Emergency Medicine Consensus Conference.

PubMed

Marin, Jennifer R; Mills, Angela M

2015-12-01

The 2015 Academic Emergency Medicine (AEM) consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization," was held on May 12, 2015, with the goal of developing a high-priority research agenda on which to base future research. The specific aims of the conference were to: 1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging utilization and identify key opportunities, limitations, and gaps in knowledge; 2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and 3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Over a 2-year period, the executive committee and other experts in the field convened regularly to identify specific areas in need of future research. Six content areas within emergency diagnostic imaging were identified prior to the conference and served as the breakout groups on which consensus was achieved: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use. The executive committee invited key stakeholders to assist with planning and to participate in the consensus conference to generate a multidisciplinary agenda. There were 164 individuals involved in the conference spanning various specialties, including emergency medicine (EM), radiology, surgery, medical physics, and the decision sciences. This issue of AEM is dedicated to the proceedings of the 16th annual AEM consensus conference as well as original research related to emergency diagnostic imaging. © 2015 by the Society for Academic Emergency Medicine.

Human body segmentation via data-driven graph cut.

PubMed

Li, Shifeng; Lu, Huchuan; Shao, Xingqing

2014-11-01

Human body segmentation is a challenging and important problem in computer vision. Existing methods usually entail a time-consuming training phase for prior knowledge learning with complex shape matching for body segmentation. In this paper, we propose a data-driven method that integrates top-down body pose information and bottom-up low-level visual cues for segmenting humans in static images within the graph cut framework. The key idea of our approach is first to exploit human kinematics to search for body part candidates via dynamic programming for high-level evidence. Then, by using the body parts classifiers, obtaining bottom-up cues of human body distribution for low-level evidence. All the evidence collected from top-down and bottom-up procedures are integrated in a graph cut framework for human body segmentation. Qualitative and quantitative experiment results demonstrate the merits of the proposed method in segmenting human bodies with arbitrary poses from cluttered backgrounds.

Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer's disease.

PubMed

Kim, Dokyoon; Basile, Anna O; Bang, Lisa; Horgusluoglu, Emrin; Lee, Seunggeun; Ritchie, Marylyn D; Saykin, Andrew J; Nho, Kwangsik

2017-05-18

Rapid advancement of next generation sequencing technologies such as whole genome sequencing (WGS) has facilitated the search for genetic factors that influence disease risk in the field of human genetics. To identify rare variants associated with human diseases or traits, an efficient genome-wide binning approach is needed. In this study we developed a novel biological knowledge-based binning approach for rare-variant association analysis and then applied the approach to structural neuroimaging endophenotypes related to late-onset Alzheimer's disease (LOAD). For rare-variant analysis, we used the knowledge-driven binning approach implemented in Bin-KAT, an automated tool, that provides 1) binning/collapsing methods for multi-level variant aggregation with a flexible, biologically informed binning strategy and 2) an option of performing unified collapsing and statistical rare variant analyses in one tool. A total of 750 non-Hispanic Caucasian participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort who had both WGS data and magnetic resonance imaging (MRI) scans were used in this study. Mean bilateral cortical thickness of the entorhinal cortex extracted from MRI scans was used as an AD-related neuroimaging endophenotype. SKAT was used for a genome-wide gene- and region-based association analysis of rare variants (MAF (minor allele frequency) < 0.05) and potential confounding factors (age, gender, years of education, intracranial volume (ICV) and MRI field strength) for entorhinal cortex thickness were used as covariates. Significant associations were determined using FDR adjustment for multiple comparisons. Our knowledge-driven binning approach identified 16 functional exonic rare variants in FANCC significantly associated with entorhinal cortex thickness (FDR-corrected p-value < 0.05). In addition, the approach identified 7 evolutionary conserved regions, which were mapped to FAF1, RFX7, LYPLAL1 and GOLGA3, significantly associated with entorhinal cortex thickness (FDR-corrected p-value < 0.05). In further analysis, the functional exonic rare variants in FANCC were also significantly associated with hippocampal volume and cerebrospinal fluid (CSF) Aβ 1-42 (p-value < 0.05). Our novel binning approach identified rare variants in FANCC as well as 7 evolutionary conserved regions significantly associated with a LOAD-related neuroimaging endophenotype. FANCC (fanconi anemia complementation group C) has been shown to modulate TLR and p38 MAPK-dependent expression of IL-1β in macrophages. Our results warrant further investigation in a larger independent cohort and demonstrate that the biological knowledge-driven binning approach is a powerful strategy to identify rare variants associated with AD and other complex disease.

An Adaptation of the Distance Driven Projection Method for Single Pinhole Collimators in SPECT Imaging

NASA Astrophysics Data System (ADS)

Ihsani, Alvin; Farncombe, Troy

2016-02-01

The modelling of the projection operator in tomographic imaging is of critical importance especially when working with algebraic methods of image reconstruction. This paper proposes a distance-driven projection method which is targeted to single-pinhole single-photon emission computed tomograghy (SPECT) imaging since it accounts for the finite size of the pinhole, and the possible tilting of the detector surface in addition to other collimator-specific factors such as geometric sensitivity. The accuracy and execution time of the proposed method is evaluated by comparing to a ray-driven approach where the pinhole is sub-sampled with various sampling schemes. A point-source phantom whose projections were generated using OpenGATE was first used to compare the resolution of reconstructed images with each method using the full width at half maximum (FWHM). Furthermore, a high-activity Mini Deluxe Phantom (Data Spectrum Corp., Durham, NC, USA) SPECT resolution phantom was scanned using a Gamma Medica X-SPECT system and the signal-to-noise ratio (SNR) and structural similarity of reconstructed images was compared at various projection counts. Based on the reconstructed point-source phantom, the proposed distance-driven approach results in a lower FWHM than the ray-driven approach even when using a smaller detector resolution. Furthermore, based on the Mini Deluxe Phantom, it is shown that the distance-driven approach has consistently higher SNR and structural similarity compared to the ray-driven approach as the counts in measured projections deteriorates.

Task-driven imaging in cone-beam computed tomography.

PubMed

Gang, G J; Stayman, J W; Ouadah, S; Ehtiati, T; Siewerdsen, J H

Conventional workflow in interventional imaging often ignores a wealth of prior information of the patient anatomy and the imaging task. This work introduces a task-driven imaging framework that utilizes such information to prospectively design acquisition and reconstruction techniques for cone-beam CT (CBCT) in a manner that maximizes task-based performance in subsequent imaging procedures. The framework is employed in jointly optimizing tube current modulation, orbital tilt, and reconstruction parameters in filtered backprojection reconstruction for interventional imaging. Theoretical predictors of noise and resolution relates acquisition and reconstruction parameters to task-based detectability. Given a patient-specific prior image and specification of the imaging task, an optimization algorithm prospectively identifies the combination of imaging parameters that maximizes task-based detectability. Initial investigations were performed for a variety of imaging tasks in an elliptical phantom and an anthropomorphic head phantom. Optimization of tube current modulation and view-dependent reconstruction kernel was shown to have greatest benefits for a directional task (e.g., identification of device or tissue orientation). The task-driven approach yielded techniques in which the dose and sharp kernels were concentrated in views contributing the most to the signal power associated with the imaging task. For example, detectability of a line pair detection task was improved by at least three fold compared to conventional approaches. For radially symmetric tasks, the task-driven strategy yielded results similar to a minimum variance strategy in the absence of kernel modulation. Optimization of the orbital tilt successfully avoided highly attenuating structures that can confound the imaging task by introducing noise correlations masquerading at spatial frequencies of interest. This work demonstrated the potential of a task-driven imaging framework to improve image quality and reduce dose beyond that achievable with conventional imaging approaches.

Understanding MRI: basic MR physics for physicians.

PubMed

Currie, Stuart; Hoggard, Nigel; Craven, Ian J; Hadjivassiliou, Marios; Wilkinson, Iain D

2013-04-01

More frequently hospital clinicians are reviewing images from MR studies of their patients before seeking formal radiological opinion. This practice is driven by a multitude of factors, including an increased demand placed on hospital services, the wide availability of the picture archiving and communication system, time pressures for patient treatment (eg, in the management of acute stroke) and an inherent desire for the clinician to learn. Knowledge of the basic physical principles behind MRI is essential for correct image interpretation. This article, written for the general hospital physician, describes the basic physics of MRI taking into account the machinery, contrast weighting, spin- and gradient-echo techniques and pertinent safety issues. Examples provided are primarily referenced to neuroradiology reflecting the subspecialty for which MR currently has the greatest clinical application.

CMOS Active-Pixel Image Sensor With Intensity-Driven Readout

NASA Technical Reports Server (NTRS)

Langenbacher, Harry T.; Fossum, Eric R.; Kemeny, Sabrina

1996-01-01

Proposed complementary metal oxide/semiconductor (CMOS) integrated-circuit image sensor automatically provides readouts from pixels in order of decreasing illumination intensity. Sensor operated in integration mode. Particularly useful in number of image-sensing tasks, including diffractive laser range-finding, three-dimensional imaging, event-driven readout of sparse sensor arrays, and star tracking.

Brain magnetic resonance imaging: perception and expectations of neurologists, neurosurgeons and psychiatrists.

PubMed

Branco, Paulo; Ayres-Basto, Margarida; Portugal, Pedro; Ramos, Isabel; Seixas, Daniela

2014-06-01

Magnetic resonance imaging (MRI) has rapidly become an essential diagnostic tool in modern medicine. Understanding the objectives, perception and expectations of the different medical specialties towards MRI is therefore important to improve the quality of the examinations. Our aim was to better comprehend the reasons and expectations of neurologists, neurosurgeons and psychiatrists when requesting brain MRI scans for their patients, and also to perceive the degree of confidence of these specialists in the images and respective reports. Sixty-three specialists were recruited from two tertiary hospitals and answered a tailored questionnaire. Neurosurgeons were more concerned with the images themselves; neurologists lacked confidence in both MRI images and reports, and one third of the psychiatrists only read the report and were the most confident of the specialties in MRI findings. These results possibly reflect the idiosyncrasies of each of these medical specialties. This knowledge, driven by efficient communication between neuroradiologists and neurosurgeons, neurologists and psychiatrists, may contribute to improve the quality of MRI examinations and consequently patient care and management of health resources.

Brain Magnetic Resonance Imaging: Perception and Expectations of Neurologists, Neurosurgeons and Psychiatrists

PubMed Central

Branco, Paulo; Ayres-Basto, Margarida; Portugal, Pedro; Ramos, Isabel; Seixas, Daniela

2014-01-01

Summary Magnetic resonance imaging (MRI) has rapidly become an essential diagnostic tool in modern medicine. Understanding the objectives, perception and expectations of the different medical specialties towards MRI is therefore important to improve the quality of the examinations. Our aim was to better comprehend the reasons and expectations of neurologists, neurosurgeons and psychiatrists when requesting brain MRI scans for their patients, and also to perceive the degree of confidence of these specialists in the images and respective reports. Sixty-three specialists were recruited from two tertiary hospitals and answered a tailored questionnaire. Neurosurgeons were more concerned with the images themselves; neurologists lacked confidence in both MRI images and reports, and one third of the psychiatrists only read the report and were the most confident of the specialties in MRI findings. These results possibly reflect the idiosyncrasies of each of these medical specialties. This knowledge, driven by efficient communication between neuroradiologists and neurosurgeons, neurologists and psychiatrists, may contribute to improve the quality of MRI examinations and consequently patient care and management of health resources. PMID:24976192

Velocity of mist droplets and suspending gas imaged separately

NASA Astrophysics Data System (ADS)

Kuethe, Dean O.; McBride, Amber; Altobelli, Stephen A.

2012-03-01

Nuclear Magnetic Resonance Images (MRIs) of the velocity of water droplets and velocity of the suspending gas, hexafluoroethane, are presented for a vertical and horizontal mist pipe flow. In the vertical flow, the upward velocity of the droplets is clearly slower than the upward velocity of the gas. The average droplet size calculated from the average falling velocity in the upward flow is larger than the average droplet size of mist drawn from the top of the pipe measured with a multi-stage aerosol impactor. Vertical flow concentrates larger particles because they have a longer transit time through the pipe. In the horizontal flow there is a gravity-driven circulation with high-velocity mist in the lower portion of the pipe and low-velocity gas in the upper portion. MRI has the advantages that it can image both phases and that it is unperturbed by optical opacity. A drawback is that the droplet phase of mist is difficult to image because of low average spin density and because the signal from water coalesced on the pipe walls is high. To our knowledge these are the first NMR images of mist.

Imaging of the native inversion layer in Silicon-On-Insulator wafers via Scanning Surface Photovoltage: Implications for RF device performance

NASA Astrophysics Data System (ADS)

Dahanayaka, Daminda; Wong, Andrew; Kaszuba, Philip; Moszkowicz, Leon; Slinkman, James; IBM SPV Lab Team

2014-03-01

Silicon-On-Insulator (SOI) technology has proved beneficial for RF cell phone technologies, which have equivalent performance to GaAs technologies. However, there is evident parasitic inversion layer under the Buried Oxide (BOX) at the interface with the high resistivity Si substrate. The latter is inferred from capacitance-voltage measurements on MOSCAPs. The inversion layer has adverse effects on RF device performance. We present data which, for the first time, show the extent of the inversion layer in the underlying substrate. This knowledge has driven processing techniques to suppress the inversion.

C-arm technique using distance driven method for nephrolithiasis and kidney stones detection

NASA Astrophysics Data System (ADS)

Malalla, Nuhad; Sun, Pengfei; Chen, Ying; Lipkin, Michael E.; Preminger, Glenn M.; Qin, Jun

2016-04-01

Distance driven represents a state of art method that used for reconstruction for x-ray techniques. C-arm tomography is an x-ray imaging technique that provides three dimensional information of the object by moving the C-shaped gantry around the patient. With limited view angle, C-arm system was investigated to generate volumetric data of the object with low radiation dosage and examination time. This paper is a new simulation study with two reconstruction methods based on distance driven including: simultaneous algebraic reconstruction technique (SART) and Maximum Likelihood expectation maximization (MLEM). Distance driven is an efficient method that has low computation cost and free artifacts compared with other methods such as ray driven and pixel driven methods. Projection images of spherical objects were simulated with a virtual C-arm system with a total view angle of 40 degrees. Results show the ability of limited angle C-arm technique to generate three dimensional images with distance driven reconstruction.

Concept of operations for knowledge discovery from Big Data across enterprise data warehouses

NASA Astrophysics Data System (ADS)

Sukumar, Sreenivas R.; Olama, Mohammed M.; McNair, Allen W.; Nutaro, James J.

2013-05-01

The success of data-driven business in government, science, and private industry is driving the need for seamless integration of intra and inter-enterprise data sources to extract knowledge nuggets in the form of correlations, trends, patterns and behaviors previously not discovered due to physical and logical separation of datasets. Today, as volume, velocity, variety and complexity of enterprise data keeps increasing, the next generation analysts are facing several challenges in the knowledge extraction process. Towards addressing these challenges, data-driven organizations that rely on the success of their analysts have to make investment decisions for sustainable data/information systems and knowledge discovery. Options that organizations are considering are newer storage/analysis architectures, better analysis machines, redesigned analysis algorithms, collaborative knowledge management tools, and query builders amongst many others. In this paper, we present a concept of operations for enabling knowledge discovery that data-driven organizations can leverage towards making their investment decisions. We base our recommendations on the experience gained from integrating multi-agency enterprise data warehouses at the Oak Ridge National Laboratory to design the foundation of future knowledge nurturing data-system architectures.

The TWINS Science Data System after the launch of TWINS 1

NASA Astrophysics Data System (ADS)

Goldstein, J.; Valek, P.; Skoug, R.; Delapp, D.; Redfern, J.; Carruth, B.; McComas, D.

2007-05-01

The Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) 1 satellite is in orbit and science data are expected to commence in the near future. TWINS-1 comprises half of the TWINS stereoscopic neutral atom imaging system that will advance our knowledge of the Earth's ring current. To support the expected data return, we have developed a Science Data System (SDS) for the TWINS mission. The TWINS SDS is an IDL- and Java- driven data interface that operates primarily via a web browser, and has as its spine an SQL-queryable database. Through this interface, TWINS science data will be provided to the TWINS team, the space science community, and the public. In this paper we present the current and future capabilities of the TWINS SDS, as well as how the SDS fits into virtual observatory infrastructure.

Atlas-based segmentation of 3D cerebral structures with competitive level sets and fuzzy control.

PubMed

Ciofolo, Cybèle; Barillot, Christian

2009-06-01

We propose a novel approach for the simultaneous segmentation of multiple structures with competitive level sets driven by fuzzy control. To this end, several contours evolve simultaneously toward previously defined anatomical targets. A fuzzy decision system combines the a priori knowledge provided by an anatomical atlas with the intensity distribution of the image and the relative position of the contours. This combination automatically determines the directional term of the evolution equation of each level set. This leads to a local expansion or contraction of the contours, in order to match the boundaries of their respective targets. Two applications are presented: the segmentation of the brain hemispheres and the cerebellum, and the segmentation of deep internal structures. Experimental results on real magnetic resonance (MR) images are presented, quantitatively assessed and discussed.

Aeolian sedimentary processes at the Bagnold Dunes, Mars: Implications for modern dune dynamics and sedimentary structures in the aeolian stratigraphic record of Mars

NASA Astrophysics Data System (ADS)

Ewing, Ryan C.; Bridges, Nathan T.; Sullivan, Rob; Lapotre, Mathieu G. A.; Fischer, Woodward W.; Lamb, Mike P.; Rubin, David M.; Lewis, Kevin W.; Gupta, Sanjeev

2016-04-01

Wind-blown sand dunes are ubiquitous on the surface of Mars and are a recognized component of the martian stratigraphic record. Our current knowledge of the aeolian sedimentary processes that determine dune morphology, drive dune dynamics, and create aeolian cross-stratification are based upon orbital studies of ripple and dune morphodynamics, rover observations of stratification on Mars, Earth analogs, and experimental and theoretical studies of sand movement under Martian conditions. In-situ observations of sand dunes (informally called the Bagnold Dunes) by Curiosity Rover in Gale Crater, Mars provide the first opportunity to make observations of dunes from the grain-to-dune scale thereby filling the gap in knowledge between theory and orbital observations and refining our understanding of the martian aeolian stratigraphic record. We use the suite of cameras on Curiosity, including Navigation Camera (Navcam), Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI), to make observations of the Bagnold Dunes. Measurements of sedimentary structures are made where stereo images are available. Observations indicate that structures generated by gravity-driven processes on the dune lee slopes, such as grainflow and grainfall, are similar to the suite of aeolian sedimentary structures observed on Earth and should be present and recognizable in Mars' aeolian stratigraphic record. Structures formed by traction-driven processes deviate significantly from those found on Earth. The dune hosts centimeter-scale wind ripples and large, meter-scale ripples, which are not found on Earth. The large ripples migrate across the depositional, lee slopes of the dune, which implies that these structures should be present in Mars' stratigraphic record and may appear similar to compound-dune stratification.The Mars Science Laboratory Curiosity Rover Team is acknowledged for their support of this work.

Application-Driven No-Reference Quality Assessment for Dermoscopy Images With Multiple Distortions.

PubMed

Xie, Fengying; Lu, Yanan; Bovik, Alan C; Jiang, Zhiguo; Meng, Rusong

2016-06-01

Dermoscopy images often suffer from blur and uneven illumination distortions that occur during acquisition, which can adversely influence consequent automatic image analysis results on potential lesion objects. The purpose of this paper is to deploy an algorithm that can automatically assess the quality of dermoscopy images. Such an algorithm could be used to direct image recapture or correction. We describe an application-driven no-reference image quality assessment (IQA) model for dermoscopy images affected by possibly multiple distortions. For this purpose, we created a multiple distortion dataset of dermoscopy images impaired by varying degrees of blur and uneven illumination. The basis of this model is two single distortion IQA metrics that are sensitive to blur and uneven illumination, respectively. The outputs of these two metrics are combined to predict the quality of multiply distorted dermoscopy images using a fuzzy neural network. Unlike traditional IQA algorithms, which use human subjective score as ground truth, here ground truth is driven by the application, and generated according to the degree of influence of the distortions on lesion analysis. The experimental results reveal that the proposed model delivers accurate and stable quality prediction results for dermoscopy images impaired by multiple distortions. The proposed model is effective for quality assessment of multiple distorted dermoscopy images. An application-driven concept for IQA is introduced, and at the same time, a solution framework for the IQA of multiple distortions is proposed.

Image segmentation with a novel regularized composite shape prior based on surrogate study

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

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

Purpose: Incorporating training into image segmentation is a good approach to achieve additional robustness. This work aims to develop an effective strategy to utilize shape prior knowledge, so that the segmentation label evolution can be driven toward the desired global optimum. Methods: In the variational image segmentation framework, a regularization for the composite shape prior is designed to incorporate the geometric relevance of individual training data to the target, which is inferred by an image-based surrogate relevance metric. Specifically, this regularization is imposed on the linear weights of composite shapes and serves as a hyperprior. The overall problem is formulatedmore » in a unified optimization setting and a variational block-descent algorithm is derived. Results: The performance of the proposed scheme is assessed in both corpus callosum segmentation from an MR image set and clavicle segmentation based on CT images. The resulted shape composition provides a proper preference for the geometrically relevant training data. A paired Wilcoxon signed rank test demonstrates statistically significant improvement of image segmentation accuracy, when compared to multiatlas label fusion method and three other benchmark active contour schemes. Conclusions: This work has developed a novel composite shape prior regularization, which achieves superior segmentation performance than typical benchmark schemes.« less

Designing Cognitively Diagnostic Assessment for Algebraic Content Knowledge and Thinking Skills

ERIC Educational Resources Information Center

Zhang, Zhidong

2018-01-01

This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…

Global-constrained hidden Markov model applied on wireless capsule endoscopy video segmentation

NASA Astrophysics Data System (ADS)

Wan, Yiwen; Duraisamy, Prakash; Alam, Mohammad S.; Buckles, Bill

2012-06-01

Accurate analysis of wireless capsule endoscopy (WCE) videos is vital but tedious. Automatic image analysis can expedite this task. Video segmentation of WCE into the four parts of the gastrointestinal tract is one way to assist a physician. The segmentation approach described in this paper integrates pattern recognition with statiscal analysis. Iniatially, a support vector machine is applied to classify video frames into four classes using a combination of multiple color and texture features as the feature vector. A Poisson cumulative distribution, for which the parameter depends on the length of segments, models a prior knowledge. A priori knowledge together with inter-frame difference serves as the global constraints driven by the underlying observation of each WCE video, which is fitted by Gaussian distribution to constrain the transition probability of hidden Markov model.Experimental results demonstrated effectiveness of the approach.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: Initial investigation of a combined model- and image-driven approach

PubMed Central

Uneri, Ali; Nithiananthan, Sajendra; Schafer, Sebastian; Otake, Yoshito; Stayman, J. Webster; Kleinszig, Gerhard; Sussman, Marc S.; Prince, Jerry L.; Siewerdsen, Jeffrey H.

2013-01-01

Purpose: Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. Methods: The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process. Results: The combined model- and image-driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (∼3–5 mm within the target wedge) and critical structure avoidance (∼1–2 mm). The model-driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image-driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed. Conclusions: The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within ∼1–2 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes in vivo testing, optimization of workflow, and integration with a CBCT image guidance system. PMID:23298134

Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: initial investigation of a combined model- and image-driven approach.

PubMed

Uneri, Ali; Nithiananthan, Sajendra; Schafer, Sebastian; Otake, Yoshito; Stayman, J Webster; Kleinszig, Gerhard; Sussman, Marc S; Prince, Jerry L; Siewerdsen, Jeffrey H

2013-01-01

Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process. The combined model- and image-driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (∼3-5 mm within the target wedge) and critical structure avoidance (∼1-2 mm). The model-driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image-driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed. The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within ∼1-2 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes in vivo testing, optimization of workflow, and integration with a CBCT image guidance system.

Microcontroller-driven fluid-injection system for atomic force microscopy.

PubMed

Kasas, S; Alonso, L; Jacquet, P; Adamcik, J; Haeberli, C; Dietler, G

2010-01-01

We present a programmable microcontroller-driven injection system for the exchange of imaging medium during atomic force microscopy. Using this low-noise system, high-resolution imaging can be performed during this process of injection without disturbance. This latter circumstance was exemplified by the online imaging of conformational changes in DNA molecules during the injection of anticancer drug into the fluid chamber.

A new optical post-equalization based on self-imaging

NASA Astrophysics Data System (ADS)

Guizani, S.; Cheriti, A.; Razzak, M.; Boulslimani, Y.; Hamam, H.

2005-09-01

Driven by the world's growing need for communication bandwidth, progress is constantly being reported in building newer fibers that are capable of handling the rapid increase in traffic. However, building an optical fiber link is a major investment, one that is very expensive to replace. A major impairment that restricts the achievement of higher bit rates with standard single mode fiber is chromatic dispersion. This is particularly problematic for systems operating in the 1550 nm band, where the chromatic dispersion limit decreases rapidly in inverse proportion to the square of the bit rate. For the first time, to the best of our knowledge, this document illustrates a new optical technique to post compensate optically the chromatic dispersion in fiber using temporal Talbot effect in ranges exceeding the 40G bit/s. We propose a new optical post equalization solutions based on the self imaging of Talbot effect.

Diffusion-weighted magnetic resonance imaging of extraocular muscles in patients with Grave's ophthalmopathy using turbo field echo with diffusion-sensitized driven-equilibrium preparation.

PubMed

Hiwatashi, A; Togao, O; Yamashita, K; Kikuchi, K; Momosaka, D; Honda, H

2018-03-20

The purpose of this study was to correlate diffusivity of extraocular muscles, measured by three-dimensional turbo field echo (3DTFE) magnetic resonance (MR) imaging using diffusion-sensitized driven-equilibrium preparation, with their size and activity in patients with Grave's ophthalmopathy. Twenty-three patients with Grave's ophthalmopathy were included. There were 17 women and 6 men with a mean age of 55.8±12.6 (SD) years (range: 26-83 years). 3DTFE with diffusion-sensitized driven-equilibrium MR images were obtained with b-values of 0 and 500s/mm 2 . The apparent diffusion coefficient (ADC) of extraocular muscles was measured on coronal reformatted MR images. Signal intensities of extraocular muscles on conventional MR images were compared to those of normal-appearing white matter, and cross-sectional areas of the muscles were also measured. The clinical activity score was also evaluated. Statistical analyses were performed with Pearson correlation and Mann-Whitney U tests. On 3DTFE with diffusion-sensitized driven-equilibrium preparation, the mean ADC of the extraocular muscles was 2.23±0.37 (SD)×10 -3 mm2/s (range: 1.70×10 -3 -3.11×10 -3 mm 2 /s). There was a statistically significant moderate correlation between ADC and the size of the muscles (r=0.61). There were no statistically significant correlations between ADC and signal intensity on conventional MR and the clinical activity score. 3DTFE with diffusion-sensitized driven-equilibrium preparation technique allows quantifying diffusivity of extraocular muscles in patients with Grave's ophthalmopathy. The diffusivity of the extraocular muscles on 3DTFE with diffusion-sensitized driven-equilibrium preparation MR images moderately correlates with their size. Copyright © 2018. Published by Elsevier Masson SAS.

Cognitive algorithms: dynamic logic, working of the mind, evolution of consciousness and cultures

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2007-04-01

The paper discusses evolution of consciousness driven by the knowledge instinct, a fundamental mechanism of the mind which determines its higher cognitive functions. Dynamic logic mathematically describes the knowledge instinct. It overcomes past mathematical difficulties encountered in modeling intelligence and relates it to mechanisms of concepts, emotions, instincts, consciousness and unconscious. The two main aspects of the knowledge instinct are differentiation and synthesis. Differentiation is driven by dynamic logic and proceeds from vague and unconscious states to more crisp and conscious states, from less knowledge to more knowledge at each hierarchical level of the mind. Synthesis is driven by dynamic logic operating in a hierarchical organization of the mind; it strives to achieve unity and meaning of knowledge: every concept finds its deeper and more general meaning at a higher level. These mechanisms are in complex relationship of symbiosis and opposition, which leads to complex dynamics of evolution of consciousness and cultures. Modeling this dynamics in a population leads to predictions for the evolution of consciousness, and cultures. Cultural predictive models can be compared to experimental data and used for improvement of human conditions. We discuss existing evidence and future research directions.

Concept of Operations for Collaboration and Discovery from Big Data Across Enterprise Data Warehouses

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

Olama, Mohammed M; Nutaro, James J; Sukumar, Sreenivas R

2013-01-01

The success of data-driven business in government, science, and private industry is driving the need for seamless integration of intra and inter-enterprise data sources to extract knowledge nuggets in the form of correlations, trends, patterns and behaviors previously not discovered due to physical and logical separation of datasets. Today, as volume, velocity, variety and complexity of enterprise data keeps increasing, the next generation analysts are facing several challenges in the knowledge extraction process. Towards addressing these challenges, data-driven organizations that rely on the success of their analysts have to make investment decisions for sustainable data/information systems and knowledge discovery. Optionsmore » that organizations are considering are newer storage/analysis architectures, better analysis machines, redesigned analysis algorithms, collaborative knowledge management tools, and query builders amongst many others. In this paper, we present a concept of operations for enabling knowledge discovery that data-driven organizations can leverage towards making their investment decisions. We base our recommendations on the experience gained from integrating multi-agency enterprise data warehouses at the Oak Ridge National Laboratory to design the foundation of future knowledge nurturing data-system architectures.« less

Flexible cue combination in the guidance of attention in visual search

PubMed Central

Brand, John; Oriet, Chris; Johnson, Aaron P.; Wolfe, Jeremy M.

2014-01-01

Hodsoll and Humphreys (2001) have assessed the relative contributions of stimulus-driven and user-driven knowledge on linearly- and nonlinearly separable search. However, the target feature used to determine linear separability in their task (i.e., target size) was required to locate the target. In the present work, we investigated the contributions of stimulus-driven and user-driven knowledge when a linearly- or nonlinearly-separable feature is available but not required for target identification. We asked observers to complete a series of standard color X orientation conjunction searches in which target size was either linearly- or nonlinearly separable from the size of the distractors. When guidance by color X orientation and by size information are both available, observers rely on whichever information results in the best search efficiency. This is the case irrespective of whether we provide target foreknowledge by blocking stimulus conditions, suggesting that feature information is used in both a stimulus-driven and user-driven fashion. PMID:25463553

Knowledge enabled plan of care and documentation prototype.

PubMed

DaDamio, Rebecca; Gugerty, Brian; Kennedy, Rosemary

2006-01-01

There exist significant challenges in integrating the plan of care into documentation and point of care operational processes. A plan of care is often a static artifact that meets regulatory standards with limited influence on supporting goal-directed care delivery processes. Although this prototype is applicable to many clinical disciplines, we will highlight nursing processes in demonstrating a knowledge-driven computerized solution that fully integrates the plan of care within documentation. The knowledge-driven solution reflects evidenced-based practice; is an effective tool for managing problems, orders/interventions, and the patient's progress towards expected outcomes; meets regulatory standards; and drives quality and process improvement. The knowledge infrastructure consists of fully represented terminology, structured clinical expressions utilizing the controlled terminology and clinical knowledge representing evidence-based practice.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Task-Driven Tube Current Modulation and Regularization Design in Computed Tomography with Penalized-Likelihood Reconstruction.

PubMed

Gang, G J; Siewerdsen, J H; Stayman, J W

2016-02-01

This work applies task-driven optimization to design CT tube current modulation and directional regularization in penalized-likelihood (PL) reconstruction. The relative performance of modulation schemes commonly adopted for filtered-backprojection (FBP) reconstruction were also evaluated for PL in comparison. We adopt a task-driven imaging framework that utilizes a patient-specific anatomical model and information of the imaging task to optimize imaging performance in terms of detectability index ( d' ). This framework leverages a theoretical model based on implicit function theorem and Fourier approximations to predict local spatial resolution and noise characteristics of PL reconstruction as a function of the imaging parameters to be optimized. Tube current modulation was parameterized as a linear combination of Gaussian basis functions, and regularization was based on the design of (directional) pairwise penalty weights for the 8 in-plane neighboring voxels. Detectability was optimized using a covariance matrix adaptation evolutionary strategy algorithm. Task-driven designs were compared to conventional tube current modulation strategies for a Gaussian detection task in an abdomen phantom. The task-driven design yielded the best performance, improving d' by ~20% over an unmodulated acquisition. Contrary to FBP, PL reconstruction using automatic exposure control and modulation based on minimum variance (in FBP) performed worse than the unmodulated case, decreasing d' by 16% and 9%, respectively. This work shows that conventional tube current modulation schemes suitable for FBP can be suboptimal for PL reconstruction. Thus, the proposed task-driven optimization provides additional opportunities for improved imaging performance and dose reduction beyond that achievable with conventional acquisition and reconstruction.

Probabilistic sparse matching for robust 3D/3D fusion in minimally invasive surgery.

PubMed

Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan

2015-01-01

Classical surgery is being overtaken by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm computed tomography (CT) and C-arm fluoroscopy are routinely used in clinical practice for intraoperative guidance. However, due to constraints regarding acquisition time and device configuration, intraoperative modalities have limited soft tissue image quality and reliable assessment of the cardiac anatomy typically requires contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a probabilistic sparse matching approach to fuse high-quality preoperative CT images and nongated, noncontrast intraoperative C-arm CT images by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the preoperative CT and mapped to the intraoperative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments on 95 clinical datasets demonstrate that our model-based fusion approach has an average execution time of 1.56 s, while the accuracy of 5.48 mm between the anchor anatomy in both images lies within expert user confidence intervals. In direct comparison with image-to-image registration based on an open-source state-of-the-art medical imaging library and a recently proposed quasi-global, knowledge-driven multi-modal fusion approach for thoracic-abdominal images, our model-based method exhibits superior performance in terms of registration accuracy and robustness with respect to both target anatomy and anchor anatomy alignment errors.

Knowledge management in healthcare: towards 'knowledge-driven' decision-support services.

PubMed

Abidi, S S

2001-09-01

In this paper, we highlight the involvement of Knowledge Management in a healthcare enterprise. We argue that the 'knowledge quotient' of a healthcare enterprise can be enhanced by procuring diverse facets of knowledge from the seemingly placid healthcare data repositories, and subsequently operationalising the procured knowledge to derive a suite of Strategic Healthcare Decision-Support Services that can impact strategic decision-making, planning and management of the healthcare enterprise. In this paper, we firstly present a reference Knowledge Management environment-a Healthcare Enterprise Memory-with the functionality to acquire, share and operationalise the various modalities of healthcare knowledge. Next, we present the functional and architectural specification of a Strategic Healthcare Decision-Support Services Info-structure, which effectuates a synergy between knowledge procurement (vis-à-vis Data Mining) and knowledge operationalisation (vis-à-vis Knowledge Management) techniques to generate a suite of strategic knowledge-driven decision-support services. In conclusion, we argue that the proposed Healthcare Enterprise Memory is an attempt to rethink the possible sources of leverage to improve healthcare delivery, hereby providing a valuable strategic planning and management resource to healthcare policy makers.

Knowledge Sharing at Work: An Examination of Organizational Antecedents

ERIC Educational Resources Information Center

Behnke, Tricia M.

2010-01-01

With the rapid pace of today's knowledge-driven industries, organizations are turning to successful knowledge management initiatives to obtain sustainable competitive advantage. As a result, one facet of knowledge management, knowledge sharing at work, has received increased researcher and practitioner attention in the last decade. However, in the…

Medical sieve: a cognitive assistant for radiologists and cardiologists

NASA Astrophysics Data System (ADS)

Syeda-Mahmood, T.; Walach, E.; Beymer, D.; Gilboa-Solomon, F.; Moradi, M.; Kisilev, P.; Kakrania, D.; Compas, C.; Wang, H.; Negahdar, R.; Cao, Y.; Baldwin, T.; Guo, Y.; Gur, Y.; Rajan, D.; Zlotnick, A.; Rabinovici-Cohen, S.; Ben-Ari, R.; Guy, Amit; Prasanna, P.; Morey, J.; Boyko, O.; Hashoul, S.

2016-03-01

Radiologists and cardiologists today have to view large amounts of imaging data relatively quickly leading to eye fatigue. Further, they have only limited access to clinical information relying mostly on their visual interpretation of imaging studies for their diagnostic decisions. In this paper, we present Medical Sieve, an automated cognitive assistant for radiologists and cardiologists designed to help in their clinical decision-making. The sieve is a clinical informatics system that collects clinical, textual and imaging data of patients from electronic health records systems. It then analyzes multimodal content to detect anomalies if any, and summarizes the patient record collecting all relevant information pertinent to a chief complaint. The results of anomaly detection are then fed into a reasoning engine which uses evidence from both patient-independent clinical knowledge and large-scale patient-driven similar patient statistics to arrive at potential differential diagnosis to help in clinical decision making. In compactly summarizing all relevant information to the clinician per chief complaint, the system still retains links to the raw data for detailed review providing holistic summaries of patient conditions. Results of clinical studies in the domains of cardiology and breast radiology have already shown the promise of the system in differential diagnosis and imaging studies summarization.

Spurting Plasma

NASA Image and Video Library

2014-06-16

A stream of plasma burst out from the sun, but since it lacked enough force to break away, most of it fell back into the sun (May 27, 2014). This eruption was minor and such events occur almost every day on the sun and suggest the kind of dynamic activity being driven by powerful magnetic forces near the sun's surface. Credit: NASA/Goddard/Solar Dynamics Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Seeking Optimal Region-Of-Interest (ROI) Single-Value Summary Measures for fMRI Studies in Imaging Genetics

PubMed Central

Tong, Yunxia; Chen, Qiang; Nichols, Thomas E.; Rasetti, Roberta; Callicott, Joseph H.; Berman, Karen F.; Weinberger, Daniel R.; Mattay, Venkata S.

2016-01-01

A data-driven hypothesis-free genome-wide association (GWA) approach in imaging genetics studies allows screening the entire genome to discover novel genes that modulate brain structure, chemistry, and function. However, a whole brain voxel-wise analysis approach in such genome-wide based imaging genetic studies can be computationally intense and also likely has low statistical power since a stringent multiple comparisons correction is needed for searching over the entire genome and brain. In imaging genetics with functional magnetic resonance imaging (fMRI) phenotypes, since many experimental paradigms activate focal regions that can be pre-specified based on a priori knowledge, reducing the voxel-wise search to single-value summary measures within a priori ROIs could prove efficient and promising. The goal of this investigation is to evaluate the sensitivity and reliability of different single-value ROI summary measures and provide guidance in future work. Four different fMRI databases were tested and comparisons across different groups (patients with schizophrenia, their siblings, vs. normal control subjects; across genotype groups) were conducted. Our results show that four of these measures, particularly those that represent values from the top most-activated voxels within an ROI are more powerful at reliably detecting group differences and generating greater effect sizes than the others. PMID:26974435

Using Program Theory-Driven Evaluation Science to Crack the Da Vinci Code

ERIC Educational Resources Information Center

Donaldson, Stewart I.

2005-01-01

Program theory-driven evaluation science uses substantive knowledge, as opposed to method proclivities, to guide program evaluations. It aspires to update, clarify, simplify, and make more accessible the evolving theory of evaluation practice commonly referred to as theory-driven or theory-based evaluation. The evaluator in this chapter provides a…

Schematic driven layout of Reed Solomon encoders

NASA Technical Reports Server (NTRS)

Arave, Kari; Canaris, John; Miles, Lowell; Whitaker, Sterling

1992-01-01

Two Reed Solomon error correcting encoders are presented. Schematic driven layout tools were used to create the encoder layouts. Special consideration had to be given to the architecture and logic to provide scalability of the encoder designs. Knowledge gained from these projects was used to create a more flexible schematic driven layout system.

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Retinotopy and attention to the face and house images in the human visual cortex.

PubMed

Wang, Bin; Yan, Tianyi; Ohno, Seiichiro; Kanazawa, Susumu; Wu, Jinglong

2016-06-01

Attentional modulation of the neural activities in human visual areas has been well demonstrated. However, the retinotopic activities that are driven by face and house images and attention to face and house images remain unknown. In the present study, we used images of faces and houses to estimate the retinotopic activities that were driven by both the images and attention to the images, driven by attention to the images, and driven by the images. Generally, our results show that both face and house images produced similar retinotopic activities in visual areas, which were only observed in the attention + stimulus and the attention conditions, but not in the stimulus condition. The fusiform face area (FFA) responded to faces that were presented on the horizontal meridian, whereas parahippocampal place area (PPA) rarely responded to house at any visual field. We further analyzed the amplitudes of the neural responses to the target wedge. In V1, V2, V3, V3A, lateral occipital area 1 (LO-1), and hV4, the neural responses to the attended target wedge were significantly greater than those to the unattended target wedge. However, in LO-2, ventral occipital areas 1 and 2 (VO-1 and VO-2) and FFA and PPA, the differences were not significant. We proposed that these areas likely have large fields of attentional modulation for face and house images and exhibit responses to both the target wedge and the background stimuli. In addition, we proposed that the absence of retinotopic activity in the stimulus condition might imply no perceived difference between the target wedge and the background stimuli.

Knowledge Management Systems: Linking Contribution, Refinement and Use

ERIC Educational Resources Information Center

Chung, Ting-ting

2009-01-01

Electronic knowledge repositories represent one of the fundamental tools for knowledge management (KM) initiatives. Existing research, however, has largely focused on supply-side driven research questions, such as employee motivation to contribute knowledge to a repository. This research turns attention to the dynamic relationship between the…

RADC Multi-Dimensional Signal-Processing Research Program.

DTIC Science & Technology

1980-09-30

Formulation 7 3.2.2 Methods of Accelerating Convergence 8 3.2.3 Application to Image Deblurring 8 3.2.4 Extensions 11 3.3 Convergence of Iterative Signal... noise -driven linear filters, permit development of the joint probability density function oz " kelihood function for the image. With an expression...spatial linear filter driven by white noise (see Fig. i). If the probability density function for the white noise is known, Fig. t. Model for image

Learning deep similarity in fundus photography

NASA Astrophysics Data System (ADS)

Chudzik, Piotr; Al-Diri, Bashir; Caliva, Francesco; Ometto, Giovanni; Hunter, Andrew

2017-02-01

Similarity learning is one of the most fundamental tasks in image analysis. The ability to extract similar images in the medical domain as part of content-based image retrieval (CBIR) systems has been researched for many years. The vast majority of methods used in CBIR systems are based on hand-crafted feature descriptors. The approximation of a similarity mapping for medical images is difficult due to the big variety of pixel-level structures of interest. In fundus photography (FP) analysis, a subtle difference in e.g. lesions and vessels shape and size can result in a different diagnosis. In this work, we demonstrated how to learn a similarity function for image patches derived directly from FP image data without the need of manually designed feature descriptors. We used a convolutional neural network (CNN) with a novel architecture adapted for similarity learning to accomplish this task. Furthermore, we explored and studied multiple CNN architectures. We show that our method can approximate the similarity between FP patches more efficiently and accurately than the state-of- the-art feature descriptors, including SIFT and SURF using a publicly available dataset. Finally, we observe that our approach, which is purely data-driven, learns that features such as vessels calibre and orientation are important discriminative factors, which resembles the way how humans reason about similarity. To the best of authors knowledge, this is the first attempt to approximate a visual similarity mapping in FP.

Neurosurgical hand-held optical coherence tomography (OCT) forward-viewing probe

NASA Astrophysics Data System (ADS)

Sun, Cuiru; Lee, Kenneth K. C.; Vuong, Barry; Cusimano, Michael; Brukson, Alexander; Mariampillai, Adrian; Standish, Beau A.; Yang, Victor X. D.

2012-02-01

A prototype neurosurgical hand-held optical coherence tomography (OCT) imaging probe has been developed to provide micron resolution cross-sectional images of subsurface tissue during open surgery. This new ergonomic hand-held probe has been designed based on our group's previous work on electrostatically driven optical fibers. It has been packaged into a catheter probe in the familiar form factor of the clinically accepted Bayonet shaped neurosurgical non-imaging Doppler ultrasound probes. The optical design was optimized using ZEMAX simulation. Optical properties of the probe were tested to yield an ~20 um spot size, 5 mm working distance and a 3.5 mm field of view. The scan frequency can be increased or decreased by changing the applied voltage. Typically a scan frequency of less than 60Hz is chosen to keep the applied voltage to less than 2000V. The axial resolution of the probe was ~15 um (in air) as determined by the OCT system. A custom-triggering methodology has been developed to provide continuous stable imaging, which is crucial for clinical utility. Feasibility of this probe, in combination with a 1310 nm swept source OCT system was tested and images are presented to highlight the usefulness of such a forward viewing handheld OCT imaging probe. Knowledge gained from this research will lay the foundation for developing new OCT technologies for endovascular management of cerebral aneurysms and transsphenoidal neuroendoscopic treatment of pituitary tumors.

Ultra high-speed x-ray imaging of laser-driven shock compression using synchrotron light

NASA Astrophysics Data System (ADS)

Olbinado, Margie P.; Cantelli, Valentina; Mathon, Olivier; Pascarelli, Sakura; Grenzer, Joerg; Pelka, Alexander; Roedel, Melanie; Prencipe, Irene; Laso Garcia, Alejandro; Helbig, Uwe; Kraus, Dominik; Schramm, Ulrich; Cowan, Tom; Scheel, Mario; Pradel, Pierre; De Resseguier, Thibaut; Rack, Alexander

2018-02-01

A high-power, nanosecond pulsed laser impacting the surface of a material can generate an ablation plasma that drives a shock wave into it; while in situ x-ray imaging can provide a time-resolved probe of the shock-induced material behaviour on macroscopic length scales. Here, we report on an investigation into laser-driven shock compression of a polyurethane foam and a graphite rod by means of single-pulse synchrotron x-ray phase-contrast imaging with MHz frame rate. A 6 J, 10 ns pulsed laser was used to generate shock compression. Physical processes governing the laser-induced dynamic response such as elastic compression, compaction, pore collapse, fracture, and fragmentation have been imaged; and the advantage of exploiting the partial spatial coherence of a synchrotron source for studying low-density, carbon-based materials is emphasized. The successful combination of a high-energy laser and ultra high-speed x-ray imaging using synchrotron light demonstrates the potentiality of accessing complementary information from scientific studies of laser-driven shock compression.

Making Knowledge Services Work in Higher Education

ERIC Educational Resources Information Center

Norris, Donald M.; Lefrere, Paul; Mason, Jon

2006-01-01

Over the past three years, knowledge-based practices in higher education have advanced, driving the development of low/no-cost, mass-market tools for knowledge sharing and reducing some barriers to change. New investors in higher education are developing strategies to exploit the knowledge-driven value propositions. Existing institutions, anxious…

Adult Age Differences in Knowledge-Driven Reading

ERIC Educational Resources Information Center

Miller, Lisa M. Soederberg; Stine-Morrow, Elizabeth A. L.; Kirkorian, Heather L.; Conroy, Michelle L.

2004-01-01

The authors investigated the effects of domain knowledge on online reading among younger and older adults. Individuals were randomly assigned to either a domain-relevant (i.e., high-knowledge) or domain-irrelevant (i.e., low-knowledge) training condition. Two days later, participants read target passages on a computer that drew on information…

Scientists as writers

NASA Astrophysics Data System (ADS)

Yore, Larry D.; Hand, Brian M.; Prain, Vaughan

2002-09-01

This study attempted to establish an image of a science writer based on a synthesis of writing theory, models, and research literature on academic writing in science and other disciplines and to contrast this image with an actual prototypical image of scientists as writers of science. The synthesis was used to develop a questionnaire to assess scientists' writing habits, beliefs, strategies, and perceptions about print-based language. The questionnaire was administered to 17 scientists from science and applied science departments of a large Midwestern land grant university. Each respondent was interviewed following the completion of the questionnaire with a custom-designed semistructured protocol to elaborate, probe, and extend their written responses. These data were analyzed in a stepwise fashion using the questionnaire responses to establish tentative assertions about the three major foci (type of writing done, criteria of good science writing, writing strategies used) and the interview responses to verify these assertions. Two illustrative cases (a very experienced, male physical scientist and a less experienced, female applied biological scientist) were used to highlight diversity in the sample. Generally, these 17 scientists are driven by the academy's priority of publishing their research results in refereed, peer-reviewed journals. They write their research reports in isolation or as a member of a large research team, target their writing to a few journals that they also read regularly, use writing in their teaching and scholarship to inform and persuade science students and other scientists, but do little border crossing into other discourse communities. The prototypical science writer found in this study did not match the image based on a synthesis of the writing literature in that these scientists perceived writing as knowledge telling not knowledge building, their metacognition of written discourse was tacit, and they used a narrow array of genre, strategies, target audiences, and expectations for their writing.

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

Knowledge diffusion of dynamical network in terms of interaction frequency.

PubMed

Liu, Jian-Guo; Zhou, Qing; Guo, Qiang; Yang, Zhen-Hua; Xie, Fei; Han, Jing-Ti

2017-09-07

In this paper, we present a knowledge diffusion (SKD) model for dynamic networks by taking into account the interaction frequency which always used to measure the social closeness. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that the target node would preferentially select one neighbor node to transfer knowledge with probability p according to their interaction frequency instead of the knowledge distance, otherwise, the target node would build a new link with its second-order neighbor preferentially or select one node in the system randomly with probability 1 - p. The simulation results show that, comparing with the Null model defined by the random selection mechanism and the traditional knowledge diffusion (TKD) model driven by knowledge distance, the knowledge would spread more fast based on SKD driven by interaction frequency. In particular, the network structure of SKD would evolve as an assortative one, which is a fundamental feature of social networks. This work would be helpful for deeply understanding the coevolution of the knowledge diffusion and network structure.

Systematic procedures to promote U.S. HIV medication adherence via Photovoice.

PubMed

Teti, Michelle; Shaffer, Victoria; Majee, Wilson; Farnan, Rose; Gerkovich, Mary

2017-06-21

Medication adherence is essential to promote the health of people living with HIV (PL-HIV) and prevent HIV transmission in the U.S. Novel medication health promotion interventions are needed that address patient-centeredness, understandability, and communication with providers. The aims of this article are to define the systematic stages we used to develop an effective health promotion intervention via the products (e.g. images and stories) of Photovoice. We designed an intervention to improve HIV adherence knowledge, attitudes, and communication with providers through Photovoice. 16 PL-HIV used Photovoice strategies to describe their experiences with medication via images and captions and create an intervention (10 adherence promotion posters) that integrated photo-stories of their adherence motivators, journeys from sickness to health, and how they manage and counter HIV stigma. We outline the systematic process we used to adapt Photovoice to create the effective intervention for replication. The process included six stages: (i) identify scope of the project; (ii) create collaborative project team; (iii) design project materials; (iv) review and revise materials with team members; (v) disseminate materials; and (vi) evaluate materials. Photovoice is used traditionally as a social action research method. In this project, it was adapted to create patient-driven images and stories for health promotion posters. Poster viewers experienced improved self-efficacy for HIV medication adherence. Describing the adaptation of the Photovoice process in a deliberate and transparent way can support fidelity to the essence of the participant-driven method, while also allowing researchers and practitioners to replicate Photovoice as a successful health promotion intervention. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Target volume and artifact evaluation of a new data-driven 4D CT.

PubMed

Martin, Rachael; Pan, Tinsu

Four-dimensional computed tomography (4D CT) is often used to define the internal gross target volume (IGTV) for radiation therapy of lung cancer. Traditionally, this technique requires the use of an external motion surrogate; however, a new image, data-driven 4D CT, has become available. This study aims to describe this data-driven 4D CT and compare target contours created with it to those created using standard 4D CT. Cine CT data of 35 patients undergoing stereotactic body radiation therapy were collected and sorted into phases using standard and data-driven 4D CT. IGTV contours were drawn using a semiautomated method on maximum intensity projection images of both 4D CT methods. Errors resulting from reproducibility of the method were characterized. A comparison of phase image artifacts was made using a normalized cross-correlation method that assigned a score from +1 (data-driven "better") to -1 (standard "better"). The volume difference between the data-driven and standard IGTVs was not significant (data driven was 2.1 ± 1.0% smaller, P = .08). The Dice similarity coefficient showed good similarity between the contours (0.949 ± 0.006). The mean surface separation was 0.4 ± 0.1 mm and the Hausdorff distance was 3.1 ± 0.4 mm. An average artifact score of +0.37 indicated that the data-driven method had significantly fewer and/or less severe artifacts than the standard method (P = 1.5 × 10 -5 for difference from 0). On average, the difference between IGTVs derived from data-driven and standard 4D CT was not clinically relevant or statistically significant, suggesting data-driven 4D CT can be used in place of standard 4D CT without adjustments to IGTVs. The relatively large differences in some patients were usually attributed to limitations in automatic contouring or differences in artifacts. Artifact reduction and setup simplicity suggest a clinical advantage to data-driven 4D CT. Published by Elsevier Inc.

Image reconstruction by domain-transform manifold learning.

PubMed

Zhu, Bo; Liu, Jeremiah Z; Cauley, Stephen F; Rosen, Bruce R; Rosen, Matthew S

2018-03-21

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Image reconstruction by domain-transform manifold learning

NASA Astrophysics Data System (ADS)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Education and research in medical optronics in France

NASA Astrophysics Data System (ADS)

Demongeot, Jacques; Fleute, M.; Herve, T.; Lavallee, Stephane

2000-06-01

First we present here the main post-graduate courses proposed in France both for physicians and engineers in medical optronics. After we explain which medical domains are concerned by this teaching, essentially computer assisted surgery, telemedicine and functional exploration. Then we show the main research axes in these fields, in which new jobs have to be invented and new educational approaches have to be prepared in order to satisfy the demand coming both from hospitals (mainly referent hospitals) and from industry (essentially medical imaging and instrumentation companies). Finally we will conclude that medical optronics is an important step in an entire chain of acquisition and processing of medical data, capable to create the medical knowledge a surgeon or a physician needs for diagnosis or therapy purposes. Optimizing the teaching of medical optronics needs a complete integration from acquiring to modeling the medical reality. This tendency to give a holistic education in medical imaging and instrumentation is called `Model driven Acquisition' learning.

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Image routing via atomic spin coherence

PubMed Central

Wang, Lei; Sun, Jia-Xiang; Luo, Meng-Xi; Sun, Yuan-Hang; Wang, Xiao-Xiao; Chen, Yi; Kang, Zhi-Hui; Wang, Hai-Hua; Wu, Jin-Hui; Gao, Jin-Yue

2015-01-01

Coherent storage of optical image in a coherently-driven medium is a promising method with possible applications in many fields. In this work, we experimentally report a controllable spatial-frequency routing of image via atomic spin coherence in a solid-state medium driven by electromagnetically induced transparency (EIT). Under the EIT-based light-storage regime, a transverse spatial image carried by the probe field is stored into atomic spin coherence. By manipulating the frequency and spatial propagation direction of the read control field, the stored image is transferred into a new spatial-frequency channel. When two read control fields are used to retrieve the stored information, the image information is converted into a superposition of two spatial-frequency modes. Through this technique, the image is manipulated coherently and all-optically in a controlled fashion. PMID:26658846

Local Knowledge Brokerage for Data-Driven Policy and Practice in Education

ERIC Educational Resources Information Center

Vanhoof, Jan; Mahieu, Paul

2013-01-01

The concept of "knowledge brokerage" focuses on promoting the integration of the best available evidence into policy and practice-related decisions. In this study, emphasis is put on the knowledge brokerage role of cities. The study aims at finding similarities and differences in existing educational knowledge brokerage initiatives, at…

Undisciplining Knowledge Production: Development Driven Higher Education in South Africa

ERIC Educational Resources Information Center

Winberg, Christine

2006-01-01

South African higher education institutions are increasingly under scrutiny to produce knowledge that is more relevant to South Africa's social and economic needs, more representative of the diversity of its knowledge producers, and more inclusive of the variety of the sites where knowledge is produced. Only a small percentage of South Africans…

Multimodal Task-Driven Dictionary Learning for Image Classification

DTIC Science & Technology

2015-12-18

1 Multimodal Task-Driven Dictionary Learning for Image Classification Soheil Bahrampour, Student Member, IEEE, Nasser M. Nasrabadi, Fellow, IEEE...Asok Ray, Fellow, IEEE, and W. Kenneth Jenkins, Life Fellow, IEEE Abstract— Dictionary learning algorithms have been suc- cessfully used for both...reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination of dictionary atoms. While these methods are

Why Engaging in Mathematical Practices May Explain Stronger Outcomes in Affect and Engagement: Comparing Student-Driven with Highly Guided Inquiry

ERIC Educational Resources Information Center

Sengupta-Irving, Tesha; Enyedy, Noel

2015-01-01

This article investigates why students reported liking a student-driven learning design better than a highly guided design despite equivalent gains in knowledge assessments in both conditions. We created two learning designs based on the distinction in the literature between student-driven and teacher-led approaches. One teacher assigned each of…

Grouping of optic flow stimuli during binocular rivalry is driven by monocular information.

PubMed

Holten, Vivian; Stuit, Sjoerd M; Verstraten, Frans A J; van der Smagt, Maarten J

2016-10-01

During binocular rivalry, perception alternates between two dissimilar images, presented dichoptically. Although binocular rivalry is thought to result from competition at a local level, neighboring image parts with similar features tend to be perceived together for longer durations than image parts with dissimilar features. This simultaneous dominance of two image parts is called grouping during rivalry. Previous studies have shown that this grouping depends on a shared eye-of-origin to a much larger extent than on image content, irrespective of the complexity of a static image. In the current study, we examine whether grouping of dynamic optic flow patterns is also primarily driven by monocular (eye-of-origin) information. In addition, we examine whether image parameters, such as optic flow direction, and partial versus full visibility of the optic flow pattern, affect grouping durations during rivalry. The results show that grouping of optic flow is, as is known for static images, primarily affected by its eye-of-origin. Furthermore, global motion can affect grouping durations, but only under specific conditions. Namely, only when the two full optic flow patterns were presented locally. These results suggest that grouping during rivalry is primarily driven by monocular information even for motion stimuli thought to rely on higher-level motion areas. Copyright © 2016 Elsevier Ltd. All rights reserved.

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

Visualization and simulation of density driven convection in porous media using magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Montague, James A.; Pinder, George F.; Gonyea, Jay V.; Hipko, Scott; Watts, Richard

2018-05-01

Magnetic resonance imaging is used to observe solute transport in a 40 cm long, 26 cm diameter sand column that contained a central core of low permeability silica surrounded by higher permeability well-sorted sand. Low concentrations (2.9 g/L) of Magnevist, a gadolinium based contrast agent, produce density driven convection within the column when it starts in an unstable state. The unstable state, for this experiment, exists when higher density contrast agent is present above the lower density water. We implement a numerical model in OpenFOAM to reproduce the observed fluid flow and transport from a density difference of 0.3%. The experimental results demonstrate the usefulness of magnetic resonance imaging in observing three-dimensional gravity-driven convective-dispersive transport behaviors in medium scale experiments.

Segmentation of medical images using explicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

Knowledge-Driven Creative Destruction, or Leveraging Knowledge for Competitive Advantage: Strategic Knowledge Arbitrage and Serendipity as Real Options Drivers Triggered by Co-Opetition, Co-Evolution and Co-Specialization

ERIC Educational Resources Information Center

Carayannis, Elias G.

2008-01-01

In today's globalizing and hypercompetitive marketplace, knowledge and learning are the only capabilities that can provide sustained competitive advantage. "Knowledge" is the content of learning, and a firm gains competitive superiority either by knowing something that its competitors do not know or by having a certain type of knowledge that…

The Knowledge-Based Software Assistant: Beyond CASE

NASA Technical Reports Server (NTRS)

Carozzoni, Joseph A.

1993-01-01

This paper will outline the similarities and differences between two paradigms of software development. Both support the whole software life cycle and provide automation for most of the software development process, but have different approaches. The CASE approach is based on a set of tools linked by a central data repository. This tool-based approach is data driven and views software development as a series of sequential steps, each resulting in a product. The Knowledge-Based Software Assistant (KBSA) approach, a radical departure from existing software development practices, is knowledge driven and centers around a formalized software development process. KBSA views software development as an incremental, iterative, and evolutionary process with development occurring at the specification level.

Mars-Moons Exploration, Reconnaissance and Landed Investigation (MERLIN)

NASA Astrophysics Data System (ADS)

Murchie, S. L.; Chabot, N. L.; Buczkowski, D.; Arvidson, R. E.; Castillo, J. C.; Peplowski, P. N.; Ernst, C. M.; Rivkin, A.; Eng, D.; Chmielewski, A. B.; Maki, J.; trebi-Ollenu, A.; Ehlmann, B. L.; Spence, H. E.; Horanyi, M.; Klingelhoefer, G.; Christian, J. A.

2015-12-01

The Mars-Moons Exploration, Reconnaissance and Landed Investigation (MERLIN) is a NASA Discovery mission proposal to explore the moons of Mars. Previous Mars-focused spacecraft have raised fundamental questions about Mars' moons: What are their origins and compositions? Why do the moons resemble primitive outer solar system D-type objects? How do geologic processes modify their surfaces? MERLIN answers these questions through a combination of orbital and landed measurements, beginning with reconnaissance of Deimos and investigation of the hypothesized Martian dust belts. Orbital reconnaissance of Phobos occurs, followed by low flyovers to characterize a landing site. MERLIN lands on Phobos, conducting a 90-day investigation. Radiation measurements are acquired throughout all mission phases. Phobos' size and mass provide a low-risk landing environment: controlled descent is so slow that the landing is rehearsed, but gravity is high enough that surface operations do not require anchoring. Existing imaging of Phobos reveals low regional slope regions suitable for landing, and provides knowledge for planning orbital and landed investigations. The payload leverages past NASA investments. Orbital imaging is accomplished by a dual multispectral/high-resolution imager rebuilt from MESSENGER/MDIS. Mars' dust environment is measured by the refurbished engineering model of LADEE/LDEX, and the radiation environment by the flight spare of LRO/CRaTER. The landed workspace is characterized by a color stereo imager updated from MER/HazCam. MERLIN's arm deploys landed instrumentation using proven designs from MER, Phoenix, and MSL. Elemental measurements are acquired by a modified version of Rosetta/APXS, and an uncooled gamma-ray spectrometer. Mineralogical measurements are acquired by a microscopic imaging spectrometer developed under MatISSE. MERLIN delivers seminal science traceable to NASA's Strategic Goals and Objectives, Science Plan, and the Decadal Survey. MERLIN's science-driven investigations also provide insight into Mars' particulate and radiation environment, Phobos' composition and regolith properties, and Phobos' inventory of in situ resources, filling strategic knowledge gaps to pioneer the way for future human exploration of the Mars system.

A knowledge-driven approach to cluster validity assessment.

PubMed

Bolshakova, Nadia; Azuaje, Francisco; Cunningham, Pádraig

2005-05-15

This paper presents an approach to assessing cluster validity based on similarity knowledge extracted from the Gene Ontology. The program is freely available for non-profit use on request from the authors.

Task-Driven Orbit Design and Implementation on a Robotic C-Arm System for Cone-Beam CT.

PubMed

Ouadah, S; Jacobson, M; Stayman, J W; Ehtiati, T; Weiss, C; Siewerdsen, J H

2017-03-01

This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d '. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the f z -axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the ( f y , f z ) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. For the f z -axis task, the circle + arc orbit was shown to increase d ' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d ' was increased by a factor of 1.83. This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

Task-driven orbit design and implementation on a robotic C-arm system for cone-beam CT

NASA Astrophysics Data System (ADS)

Ouadah, S.; Jacobson, M.; Stayman, J. W.; Ehtiati, T.; Weiss, C.; Siewerdsen, J. H.

2017-03-01

Purpose: This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. Methods: We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d'. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the fz-axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the (fy, fz) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. Results: For the fz-axis task, the circle + arc orbit was shown to increase d' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d' was increased by a factor of 1.83. Conclusions: This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

Dynamics of Laser-Driven Shock Waves in Solid Targets

NASA Astrophysics Data System (ADS)

Aglitskiy, Y.; Karasik, M.; Velikovich, A. L.; Serlin, V.; Weaver, J.; Schmitt, A. J.; Obenschain, S. P.; Grun, J.; Metzler, N.; Zalesak, S. T.; Gardner, J. H.; Oh, J.; Harding, E. C.

2009-11-01

Accurate shock timing is a key issue of both indirect- and direct-drive laser fusions. The experiments on the Nike laser at NRL presented here were made possible by improvements in the imaging capability of our monochromatic x-ray diagnostics based on Bragg reflection from spherically curved crystals. Side-on imaging implemented on Nike makes it possible to observe dynamics of the shock wave and ablation front in laser-driven solid targets. We can choose to observe a sequence of 2D images or a continuous time evolution of an image resolved in one spatial dimension. A sequence of 300 ps snapshots taken using vanadium backlighter at 5.2 keV reveals propagation of a shock wave in a solid plastic target. The shape of the shock wave reflects the intensity distribution in the Nike beam. The streak records with continuous time resolution show the x-t trajectory of a laser-driven shock wave in a 10% solid density DVB foam.

Visualization and simulation of density driven convection in porous media using magnetic resonance imaging.

PubMed

Montague, James A; Pinder, George F; Gonyea, Jay V; Hipko, Scott; Watts, Richard

2018-05-01

Magnetic resonance imaging is used to observe solute transport in a 40cm long, 26cm diameter sand column that contained a central core of low permeability silica surrounded by higher permeability well-sorted sand. Low concentrations (2.9g/L) of Magnevist, a gadolinium based contrast agent, produce density driven convection within the column when it starts in an unstable state. The unstable state, for this experiment, exists when higher density contrast agent is present above the lower density water. We implement a numerical model in OpenFOAM to reproduce the observed fluid flow and transport from a density difference of 0.3%. The experimental results demonstrate the usefulness of magnetic resonance imaging in observing three-dimensional gravity-driven convective-dispersive transport behaviors in medium scale experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

Developing "My Asthma Diary": a process exemplar of a patient-driven arts-based knowledge translation tool.

PubMed

Archibald, Mandy M; Hartling, Lisa; Ali, Samina; Caine, Vera; Scott, Shannon D

2018-06-05

Although it is well established that family-centered education is critical to managing childhood asthma, the information needs of parents of children with asthma are not being met through current educational approaches. Patient-driven educational materials that leverage the power of the storytelling and the arts show promise in communicating health information and assisting in illness self-management. However, such arts-based knowledge translation approaches are in their infancy, and little is known about how to develop such tools for parents. This paper reports on the development of "My Asthma Diary" - an innovative knowledge translation tool based on rigorous research evidence and tailored to parents' asthma-related information needs. We used a multi-stage process to develop four eBook prototypes of "My Asthma Diary." We conducted formative research on parents' information needs and identified high quality research evidence on childhood asthma, and used these data to inform the development of the asthma eBooks. We established interdisciplinary consulting teams with health researchers, practitioners, and artists to help iteratively create the knowledge translation tools. We describe the iterative, transdisciplinary process of developing asthma eBooks which incorporates: (I) parents' preferences and information needs on childhood asthma, (II) quality evidence on childhood asthma and its management, and (III) the engaging and informative powers of storytelling and visual art as methods to communicate complex health information to parents. We identified four dominant methodological and procedural challenges encountered during this process: (I) working within an inter-disciplinary team, (II) quantity and ordering of information, (III) creating a composite narrative, and (IV) balancing actual and ideal management scenarios. We describe a replicable and rigorous multi-staged approach to developing a patient-driven, creative knowledge translation tool, which can be adapted for use with different populations and contexts. We identified specific procedural and methodological challenges that others conducting comparable work should consider, particularly as creative, patient-driven knowledge translation strategies continue to emerge across health disciplines.

Extraction of the human cerebral ventricular system from MRI: inclusion of anatomical knowledge and clinical perspective

NASA Astrophysics Data System (ADS)

Aziz, Aamer; Hu, Qingmao; Nowinski, Wieslaw L.

2004-04-01

The human cerebral ventricular system is a complex structure that is essential for the well being and changes in which reflect disease. It is clinically imperative that the ventricular system be studied in details. For this reason computer assisted algorithms are essential to be developed. We have developed a novel (patent pending) and robust anatomical knowledge-driven algorithm for automatic extraction of the cerebral ventricular system from MRI. The algorithm is not only unique in its image processing aspect but also incorporates knowledge of neuroanatomy, radiological properties, and variability of the ventricular system. The ventricular system is divided into six 3D regions based on the anatomy and its variability. Within each ventricular region a 2D region of interest (ROI) is defined and is then further subdivided into sub-regions. Various strict conditions that detect and prevent leakage into the extra-ventricular space are specified for each sub-region based on anatomical knowledge. Each ROI is processed to calculate its local statistics, local intensity ranges of cerebrospinal fluid and grey and white matters, set a seed point within the ROI, grow region directionally in 3D, check anti-leakage conditions and correct growing if leakage occurs and connects all unconnected regions grown by relaxing growing conditions. The algorithm was tested qualitatively and quantitatively on normal and pathological MRI cases and worked well. In this paper we discuss in more detail inclusion of anatomical knowledge in the algorithm and usefulness of our approach from clinical perspective.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma.

PubMed

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-07-21

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene's expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma

PubMed Central

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-01-01

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene’s expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment. PMID:27468205

Assessment of anatomical knowledge: Approaches taken by higher education institutions.

PubMed

Choudhury, Bipasha; Freemont, Anthony

2017-04-01

Assessment serves the primary function of determining a student's competence in a subject. Several different assessment formats are available for assessing anatomical skills, knowledge and understanding and, as assessment can drive learning, a careful selection of assessments can help to engender the correct deep learning facility required of the safe clinical practitioner. The aim of this review was to survey the published literature to see whether higher education institutions are taking an andragogical approach to assessment. Five databases (EMBASE, ERIC, Medline, PubMed, and Web of Knowledge) were searched using standardized search terms with two limits applied (English language, and 2000 to the present). Among the 2,094 papers found, 32 were deemed suitable for this review. Current literature on assessment can be categorized into the following themes: assessment driven learning, types of assessments, frequency of assessments, and use of images in assessments. The consensus is to use a variety of methods, written and practical, to assess anatomical knowledge and skill in different domains. Institutions aim for different levels of Bloom's taxonomy for students at similar stages of their medical degree. Formative assessments are used widely, in differing formats, with mostly good effects on the final examination grade. In conclusion, a wide variety of assessments, each aimed at a different level of Bloom's taxonomy, are used by different institutions. Clin. Anat. 30:290-299, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

To Image...or Not to Image?

ERIC Educational Resources Information Center

Bruley, Karina

1996-01-01

Provides a checklist of considerations for installing document image processing with an electronic document management system. Other topics include scanning; indexing; the image file life cycle; benefits of imaging; document-driven workflow; and planning for workplace changes like postsorting, creating a scanning room, redeveloping job tasks and…

ODISEES Data Portal Announcement

Atmospheric Science Data Center

2015-11-13

... larger image The Ontology-Driven Interactive Search Environment for Earth Science, developed at the Atmospheric Science Data Center ... The Ontology-Driven Interactive Search Environment for Earth Science, developed at the Atmospheric Science Data Center ...

Knowledge representation for fuzzy inference aided medical image interpretation.

PubMed

Gal, Norbert; Stoicu-Tivadar, Vasile

2012-01-01

Knowledge defines how an automated system transforms data into information. This paper suggests a representation method of medical imaging knowledge using fuzzy inference systems coded in XML files. The imaging knowledge incorporates features of the investigated objects in linguistic form and inference rules that can transform the linguistic data into information about a possible diagnosis. A fuzzy inference system is used to model the vagueness of the linguistic medical imaging terms. XML files are used to facilitate easy manipulation and deployment of the knowledge into the imaging software. Preliminary results are presented.

[Biomedical publications in Spain on debate (II): the on-going 'revolutions' and their application to neurological journals].

PubMed

González de Dios, J; Sempere, A P; Aleixandre-Benavent, R

To debate about the application of on-going 'revolutions' in medical knowledge to Spanish neurological journals in the 21st century. This article reviews the current status of five revolutions in the field of health sciences, in general, and in neurological sciences, in particular: 1) the knowledge revolution: to translate the scientific investigation to the patient, with knowledge needs-driven research agenda with founder commissioning research to answer questions posed by clinicians, managers and patients, and systematic and critical appraisal reviews as the creator of quality improved knowledge; 2) the evidence based medicine revolution: the pyramid information of '4S', with systems (guidelines and computerized decision support systems), synopses (secondary journals), syntheses (systematic reviews and meta-analysis) and studies (original studies published in journals); 3) the web revolution: the possibility of dissemination of biomedical documentation by means of the Internet network are producing changes in the traditional way of conceiving scientific publication; the Internet represents a great advantage for investigation and also for clinical practice, since it permits free, universal access to databases and the interchange of texts, images and videos; 4) the open access revolution: to take full control over all operations related to the process of publish (to create, publish, communicate, distribute, reproduce and transform) with no need of any intermediaries, and to transform fundamental aspects concerning the circulation of knowledge, its use and availability; and 5) the librarian revolution: the project of a Virtual Health Library in Spain as a tool to access and disseminate scientific and technical knowledge on health through the Internet.

External radioactive markers for PET data-driven respiratory gating in positron emission tomography.

PubMed

Büther, Florian; Ernst, Iris; Hamill, James; Eich, Hans T; Schober, Otmar; Schäfers, Michael; Schäfers, Klaus P

2013-04-01

Respiratory gating is an established approach to overcoming respiration-induced image artefacts in PET. Of special interest in this respect are raw PET data-driven gating methods which do not require additional hardware to acquire respiratory signals during the scan. However, these methods rely heavily on the quality of the acquired PET data (statistical properties, data contrast, etc.). We therefore combined external radioactive markers with data-driven respiratory gating in PET/CT. The feasibility and accuracy of this approach was studied for [(18)F]FDG PET/CT imaging in patients with malignant liver and lung lesions. PET data from 30 patients with abdominal or thoracic [(18)F]FDG-positive lesions (primary tumours or metastases) were included in this prospective study. The patients underwent a 10-min list-mode PET scan with a single bed position following a standard clinical whole-body [(18)F]FDG PET/CT scan. During this scan, one to three radioactive point sources (either (22)Na or (18)F, 50-100 kBq) in a dedicated holder were attached the patient's abdomen. The list mode data acquired were retrospectively analysed for respiratory signals using established data-driven gating approaches and additionally by tracking the motion of the point sources in sinogram space. Gated reconstructions were examined qualitatively, in terms of the amount of respiratory displacement and in respect of changes in local image intensity in the gated images. The presence of the external markers did not affect whole-body PET/CT image quality. Tracking of the markers led to characteristic respiratory curves in all patients. Applying these curves for gated reconstructions resulted in images in which motion was well resolved. Quantitatively, the performance of the external marker-based approach was similar to that of the best intrinsic data-driven methods. Overall, the gain in measured tumour uptake from the nongated to the gated images indicating successful removal of respiratory motion was correlated with the magnitude of the respiratory displacement of the respective tumour lesion, but not with lesion size. Respiratory information can be assessed from list-mode PET/CT through PET data-derived tracking of external radioactive markers. This information can be successfully applied to respiratory gating to reduce motion-related image blurring. In contrast to other previously described PET data-driven approaches, the external marker approach is independent of tumour uptake and thereby applicable even in patients with poor uptake and small tumours.

Mission Driven and Data Informed Leadership

ERIC Educational Resources Information Center

Holter, Anthony C.; Frabutt, James M.

2012-01-01

The contemporary challenges facing Catholic schools and Catholic school leaders are widely known. Effective and systemic solutions to these mounting challenges are less widely known or discussed. This article highlights the skills, knowledge, and dispositions associated with mission driven and data informed leadership--an orientation to school…

Is Sustainability Knowledge Half the Battle? An Examination of Sustainability Knowledge, Attitudes, Norms, and Efficacy to Understand Sustainable Behaviours

ERIC Educational Resources Information Center

Heeren, Alexander John; Singh, Ajay S.; Zwickle, Adam; Koontz, Tomas M.; Slagle, Kristina M.; McCreery, Anna C.

2016-01-01

Purpose: The purpose of this study is to examine the relationship of sustainability knowledge to pro-environmental behaviour. A common misperception is that unsustainable behaviours are largely driven by a lack of knowledge of the underlying societal costs and the contributing factors leading to environmental degradation. Such a perception assumes…

A Projection Quality-Driven Tube Current Modulation Method in Cone-Beam CT for IGRT: Proof of Concept.

PubMed

Men, Kuo; Dai, Jianrong

2017-12-01

To develop a projection quality-driven tube current modulation method in cone-beam computed tomography for image-guided radiotherapy based on the prior attenuation information obtained by the planning computed tomography and then evaluate its effect on a reduction in the imaging dose. The QCKV-1 phantom with different thicknesses (0-400 mm) of solid water upon it was used to simulate different attenuation (μ). Projections were acquired with a series of tube current-exposure time product (mAs) settings, and a 2-dimensional contrast to noise ratio was analyzed for each projection to create a lookup table of mAs versus 2-dimensional contrast to noise ratio, μ. Before a patient underwent computed tomography, the maximum attenuation [Formula: see text] within the 95% range of each projection angle (θ) was estimated according to the planning computed tomography images. Then, a desired 2-dimensional contrast to noise ratio value was selected, and the mAs setting at θ was calculated with the lookup table of mAs versus 2-dimensional contrast to noise ratio,[Formula: see text]. Three-dimensional cone-beam computed tomography images were reconstructed using the projections acquired with the selected mAs. The imaging dose was evaluated with a polymethyl methacrylate dosimetry phantom in terms of volume computed tomography dose index. Image quality was analyzed using a Catphan 503 phantom with an oval body annulus and a pelvis phantom. For the Catphan 503 phantom, the cone-beam computed tomography image obtained by the projection quality-driven tube current modulation method had a similar quality to that of conventional cone-beam computed tomography . However, the proposed method could reduce the imaging dose by 16% to 33% to achieve an equivalent contrast to noise ratio value. For the pelvis phantom, the structural similarity index was 0.992 with a dose reduction of 39.7% for the projection quality-driven tube current modulation method. The proposed method could reduce the additional dose to the patient while not degrading the image quality for cone-beam computed tomography. The projection quality-driven tube current modulation method could be especially beneficial to patients who undergo cone-beam computed tomography frequently during a treatment course.

Evaluation of diffusivity in the anterior lobe of the pituitary gland: 3D turbo field echo with diffusion-sensitized driven-equilibrium preparation.

PubMed

Hiwatashi, A; Yoshiura, T; Togao, O; Yamashita, K; Kikuchi, K; Kobayashi, K; Ohga, M; Sonoda, S; Honda, H; Obara, M

2014-01-01

3D turbo field echo with diffusion-sensitized driven-equilibrium preparation is a non-echo-planar technique for DWI, which enables high-resolution DWI without field inhomogeneity-related image distortion. The purpose of this study was to evaluate the feasibility of diffusion-sensitized driven-equilibrium turbo field echo in evaluating diffusivity in the normal pituitary gland. First, validation of diffusion-sensitized driven-equilibrium turbo field echo was attempted by comparing it with echo-planar DWI. Five healthy volunteers were imaged by using diffusion-sensitized driven-equilibrium turbo field echo and echo-planar DWI. The imaging voxel size was 1.5 × 1.5 × 1.5 mm(3) for diffusion-sensitized driven-equilibrium turbo field echo and 1.5 × 1.9 × 3.0 mm(3) for echo-planar DWI. ADCs measured by the 2 methods in 15 regions of interests (6 in gray matter and 9 in white matter) were compared by using the Pearson correlation coefficient. The ADC in the pituitary anterior lobe was then measured in 10 volunteers by using diffusion-sensitized driven-equilibrium turbo field echo, and the results were compared with those in the pons and vermis by using a paired t test. The ADCs from the 2 methods showed a strong correlation (r = 0.79; P < .0001), confirming the accuracy of the ADC measurement with the diffusion-sensitized driven-equilibrium sequence. The ADCs in the normal pituitary gland were 1.37 ± 0.13 × 10(-3) mm(2)/s, which were significantly higher than those in the pons (1.01 ± 0.24 × 10(-3) mm(2)/s) and the vermis (0.89 ± 0.25 × 10(-3) mm(2)/s, P < .01). We demonstrated that diffusion-sensitized driven-equilibrium turbo field echo is feasible in assessing ADC in the pituitary gland.

Integrative Systems Biology for Data Driven Knowledge Discovery

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2015-01-01

Integrative systems biology is an approach that brings together diverse high throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost effective manner. Using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of yet unknown components of a system of interest and how its malfunction leads to disease. PMID:21044756

Dual-layer electrode-driven liquid crystal lens with electrically tunable focal length and focal plane

NASA Astrophysics Data System (ADS)

Zhang, Y. A.; Lin, C. F.; Lin, J. P.; Zeng, X. Y.; Yan, Q.; Zhou, X. T.; Guo, T. L.

2018-04-01

Electric-field-driven liquid crystal (ELC) lens with tunable focal length and their depth of field has been extensively applied in 3D display and imaging systems. In this work, a dual-layer electrode-driven liquid crystal (DELC) lens with electrically tunable focal length and controllable focal plane is demonstrated. ITO-SiO2-AZO electrodes with the dual-layer staggered structure on the top substrate are used as driven electrodes within a LC cell, which permits the establishment of an alternative controllability. The focal length of the DELC lens can be adjusted from 1.41 cm to 0.29 cm when the operating voltage changes from 15 V to 40 V. Furthermore, the focal plane of the DELC lens can selectively move by changing the driving method of the applied voltage to the next driven electrodes. This work demonstrates that the DELC lens has potential applications in imaging systems because of electrically tunable focal length and controllable focal plane.

Electrokinetic effects on motion of submicron particles in microchannel

NASA Astrophysics Data System (ADS)

Sato, Yohei; Hishida, Koichi

2006-11-01

Two-fluid mixing utilizing electrokinetically driven flow in a micro-channel is investigated by micron-resolution particle image velocimetry and an image processing technique. Submicron particles are transported and mixed with deionized water by electrophoresis. The particle electrophoretic velocity that is proportional to an applied electric field is measured in a closed cell, which is used to calculate the electroosmotic flow velocity. At a constant electric field, addition of pressure-driven flow to electrokinetically driven flow in a T-shaped micro-channel enhances two-fluid mixing because the momentum flux is increased. On the other hand, on application of an alternative sinusoidal electric field, the velocity difference between pressure-driven and electroosmotic flows has a significant effect on increasing the length of interface formed between two fluids. It is concluded from the present experiments that the transport and mixing process in the micro-channel will be enhanced by accurate flow-rate control of both pressure-driven and electroosmotic flows.

Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

PubMed

Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

2014-04-01

In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

Geometry-driven distributed compression of the plenoptic function: performance bounds and constructive algorithms.

PubMed

Gehrig, Nicolas; Dragotti, Pier Luigi

2009-03-01

In this paper, we study the sampling and the distributed compression of the data acquired by a camera sensor network. The effective design of these sampling and compression schemes requires, however, the understanding of the structure of the acquired data. To this end, we show that the a priori knowledge of the configuration of the camera sensor network can lead to an effective estimation of such structure and to the design of effective distributed compression algorithms. For idealized scenarios, we derive the fundamental performance bounds of a camera sensor network and clarify the connection between sampling and distributed compression. We then present a distributed compression algorithm that takes advantage of the structure of the data and that outperforms independent compression algorithms on real multiview images.

Spirit Traverse Map, Sol 680

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Annotated Spirit Traverse Map

This image shows the route that NASA's Mars Exploration Rover Spirit has driven inside Gusev Crater from its first Martian day (sol 1) to its 680th sol (Dec. 1, 2005), more than a complete Martian year. The underlying image (previously released as PIA07849) is a mosaic of images from the Mars Orbiter Camera on NASA's Mars Global Surveyor orbiter. The scale bar at lower left is 500 meters (0.31 mile). As of sol 680, Spirit had driven a total of 5,495 meters (3.41 miles).

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials.

PubMed

Brough, David B; Wheeler, Daniel; Kalidindi, Surya R

2017-03-01

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers.

Abstract knowledge versus direct experience in processing of binomial expressions

PubMed Central

Morgan, Emily; Levy, Roger

2016-01-01

We ask whether word order preferences for binomial expressions of the form A and B (e.g. bread and butter) are driven by abstract linguistic knowledge of ordering constraints referencing the semantic, phonological, and lexical properties of the constituent words, or by prior direct experience with the specific items in questions. Using forced-choice and self-paced reading tasks, we demonstrate that online processing of never-before-seen binomials is influenced by abstract knowledge of ordering constraints, which we estimate with a probabilistic model. In contrast, online processing of highly frequent binomials is primarily driven by direct experience, which we estimate from corpus frequency counts. We propose a trade-off wherein processing of novel expressions relies upon abstract knowledge, while reliance upon direct experience increases with increased exposure to an expression. Our findings support theories of language processing in which both compositional generation and direct, holistic reuse of multi-word expressions play crucial roles. PMID:27776281

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials

PubMed Central

Brough, David B; Wheeler, Daniel; Kalidindi, Surya R.

2017-01-01

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers. PMID:28690971

Are All Clinical Studies Sponsored by Industry Not Valid?

PubMed Central

Heinemann, Lutz

2008-01-01

Industry-sponsored studies have such a bad reputation that some journals require an additional statistical analysis by an independent statistician. This commentary discusses some of the reasons why academic people tend to believe that “academic” science is better than industry-driven science. Most likely, when it comes to publications, the risk of fraud exists in both worlds as the pressure to publish “significant” data is prevalent in both worlds. In contrast to the academic world, the level of control by regulatory bodies for industry-sponsored studies is much higher. Therefore, the quality of industry-driven studies is high, at least when it comes to the quality of data. One of the main reasons why academic people are so skeptical about the pharmaceutical industry is a lack of knowledge about the work done in industry. It is as demanding and scientific as in other industries. In turn, many physicians working in the pharmaceutical industry have low self-esteem. Also, the pharmaceutical industry should improve its self-presentation adequately to get rid of its bad image. There is a clear need for more communication between both worlds in order to better understand the mutual difficulties and needs. PMID:19885307

Experiments in a flighted conveyor comparing shear rates in compressed versus free surface flows

NASA Astrophysics Data System (ADS)

Pohlman, Nicholas; Higgins, Hannah; Krupiarz, Kamila; O'Connor, Ryan

2017-11-01

Uniformity of granular flow rate is critical in industry. Experiments in a flighted conveyor system aim to fill a gap in knowledge of achieving steady mass flow rate by correlating velocity profile data with mass flow rate measurements. High speed images were collected for uniformly-shaped particles in a bottom-driven flow conveyor belt system from which the velocity profiles can be generated. The correlation of mass flow rates from the velocity profiles to the time-dependent mass measurements will determine energy dissipation rates as a function of operating conditions. The velocity profiles as a function of the size of the particles, speed of the belt, and outlet size, will be compared to shear rate relationships found in past experiments that focused on gravity-driven systems. The dimension of the linear shear and type of decaying transition to the stationary bed may appear different due to the compression versus dilation space in open flows. The application of this research can serve to validate simulations in discrete element modeling and physically demonstrate a process that can be further developed and customized for industry applications, such as feeding a biomass conversion reactor. Sponsored by NIU's Office of Student Engagement and Experiential Learning.

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.

English and the Knowledge Economy: A Critical Analysis

ERIC Educational Resources Information Center

Collin, Ross

2014-01-01

This article focuses on knowledge economy discourse and considers the appeal of this discourse to English educators. Knowledge economy discourse is defined as a mode of thought and expression that assumes a broad-based economy driven by innovation will soon emerge in the USA. This discourse, it is argued, offers English teachers solutions to some…

Developing Knowledge Creating Technical Education Institutions through the Voice of Teachers: Content Analysis Approach

ERIC Educational Resources Information Center

Song, Ji Hoon; Kim, Hye Kyoung; Park, Sunyoung; Bae, Sang Hoon

2014-01-01

The purpose of this study was to develop an empirical data-driven model for a knowledge creation school system in career technical education (CTE) by identifying supportive and hindering factors influencing knowledge creation practices in CTE schools. Nonaka and colleagues' (Nonaka & Konno, 1998; Nonaka & Takeuchi, 1995) knowledge…

A Finnish Concept for Academic Entrepreneurship: The Case of Satakunta University of Applied Sciences

ERIC Educational Resources Information Center

Lain, Kari

2008-01-01

In a knowledge-driven economy there is a growing need for deeper and more productive interaction between higher education and industry. The full exploitation of knowledge requires strategies, incentives, appropriate systems and strong interaction between the transfer processes and the main processes in higher education. In a knowledge-based…

Schema-driven facilitation of new hierarchy learning in the transitive inference paradigm

PubMed Central

Kumaran, Dharshan

2013-01-01

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in humans. Here we develop a multiphase experimental scenario aimed at characterizing schema-based effects in the context of a paradigm that has been very widely used across species, the transitive inference task. We show that an associative schema, comprised of prior knowledge of the rank positions of familiar items in the hierarchy, has a marked effect on transitivity performance and the development of relational knowledge of the hierarchy that cannot be accounted for by more general changes in task strategy. Further, we show that participants are capable of deploying prior knowledge to successful effect under surprising conditions (i.e., when corrective feedback is totally absent), but only when the associative schema is robust. Finally, our results provide insights into the cognitive mechanisms underlying such schema-driven effects, and suggest that new hierarchy learning in the transitive inference task can occur through a contextual transfer mechanism that exploits the structure of associative experiences. PMID:23782509

Schema-driven facilitation of new hierarchy learning in the transitive inference paradigm.

PubMed

Kumaran, Dharshan

2013-06-19

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in humans. Here we develop a multiphase experimental scenario aimed at characterizing schema-based effects in the context of a paradigm that has been very widely used across species, the transitive inference task. We show that an associative schema, comprised of prior knowledge of the rank positions of familiar items in the hierarchy, has a marked effect on transitivity performance and the development of relational knowledge of the hierarchy that cannot be accounted for by more general changes in task strategy. Further, we show that participants are capable of deploying prior knowledge to successful effect under surprising conditions (i.e., when corrective feedback is totally absent), but only when the associative schema is robust. Finally, our results provide insights into the cognitive mechanisms underlying such schema-driven effects, and suggest that new hierarchy learning in the transitive inference task can occur through a contextual transfer mechanism that exploits the structure of associative experiences.

Knowledge Transfer between SMEs and Higher Education Institutions: Differences between Universities and Colleges of Higher Education in the Netherlands

ERIC Educational Resources Information Center

Delfmann, Heike; Koster, Sierdjan

2012-01-01

Knowledge transfer (KT) between higher education institutions (HEIs) and businesses is seen as a key element of innovation in knowledge-driven economies: HEIs generate knowledge that can be adopted in the regional economy. This process of valorization has been studied extensively, mainly with a focus on universities. In the Netherlands, there is a…

Data-driven optimal binning for respiratory motion management in PET.

PubMed

Kesner, Adam L; Meier, Joseph G; Burckhardt, Darrell D; Schwartz, Jazmin; Lynch, David A

2018-01-01

Respiratory gating has been used in PET imaging to reduce the amount of image blurring caused by patient motion. Optimal binning is an approach for using the motion-characterized data by binning it into a single, easy to understand/use, optimal bin. To date, optimal binning protocols have utilized externally driven motion characterization strategies that have been tuned with population-derived assumptions and parameters. In this work, we are proposing a new strategy with which to characterize motion directly from a patient's gated scan, and use that signal to create a patient/instance-specific optimal bin image. Two hundred and nineteen phase-gated FDG PET scans, acquired using data-driven gating as described previously, were used as the input for this study. For each scan, a phase-amplitude motion characterization was generated and normalized using principle component analysis. A patient-specific "optimal bin" window was derived using this characterization, via methods that mirror traditional optimal window binning strategies. The resulting optimal bin images were validated by correlating quantitative and qualitative measurements in the population of PET scans. In 53% (n = 115) of the image population, the optimal bin was determined to include 100% of the image statistics. In the remaining images, the optimal binning windows averaged 60% of the statistics and ranged between 20% and 90%. Tuning the algorithm, through a single acceptance window parameter, allowed for adjustments of the algorithm's performance in the population toward conservation of motion or reduced noise-enabling users to incorporate their definition of optimal. In the population of images that were deemed appropriate for segregation, average lesion SUV max were 7.9, 8.5, and 9.0 for nongated images, optimal bin, and gated images, respectively. The Pearson correlation of FWHM measurements between optimal bin images and gated images were better than with nongated images, 0.89 and 0.85, respectively. Generally, optimal bin images had better resolution than the nongated images and better noise characteristics than the gated images. We extended the concept of optimal binning to a data-driven form, updating a traditionally one-size-fits-all approach to a conformal one that supports adaptive imaging. This automated strategy was implemented easily within a large population and encapsulated motion information in an easy to use 3D image. Its simplicity and practicality may make this, or similar approaches ideal for use in clinical settings. © 2017 American Association of Physicists in Medicine.

Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology

PubMed Central

Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S

2017-01-01

Background There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. Objective This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. Methods We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. Results A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Conclusions Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. PMID:29021130

An Ensemble Approach to Building Mercer Kernels with Prior Information

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2005-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

A Model-Driven Approach to e-Course Management

ERIC Educational Resources Information Center

Savic, Goran; Segedinac, Milan; Milenkovic, Dušica; Hrin, Tamara; Segedinac, Mirjana

2018-01-01

This paper presents research on using a model-driven approach to the development and management of electronic courses. We propose a course management system which stores a course model represented as distinct machine-readable components containing domain knowledge of different course aspects. Based on this formally defined platform-independent…

Enhancing Extensive Reading with Data-Driven Learning

ERIC Educational Resources Information Center

Hadley, Gregory; Charles, Maggie

2017-01-01

This paper investigates using data-driven learning (DDL) as a means of stimulating greater lexicogrammatical knowledge and reading speed among lower proficiency learners in an extensive reading program. For 16 weekly 90-minute sessions, an experimental group (12 students) used DDL materials created from a corpus developed from the Oxford Bookworms…

A Decision Fusion Framework for Treatment Recommendation Systems.

PubMed

Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin

2015-01-01

Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.

Contour-Driven Atlas-Based Segmentation

PubMed Central

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

2016-01-01

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

Practice and Learning: Spatiotemporal Differences in Thalamo-Cortical-Cerebellar Networks Engagement across Learning Phases in Schizophrenia.

PubMed

Korostil, Michele; Remington, Gary; McIntosh, Anthony Randal

2016-01-01

Understanding how practice mediates the transition of brain-behavior networks between early and later stages of learning is constrained by the common approach to analysis of fMRI data. Prior imaging studies have mostly relied on a single scan, and parametric, task-related analyses. Our experiment incorporates a multisession fMRI lexicon-learning experiment with multivariate, whole-brain analysis to further knowledge of the distributed networks supporting practice-related learning in schizophrenia (SZ). Participants with SZ were compared with healthy control (HC) participants as they learned a novel lexicon during two fMRI scans over a several day period. All participants were trained to equal task proficiency prior to scanning. Behavioral-Partial Least Squares, a multivariate analytic approach, was used to analyze the imaging data. Permutation testing was used to determine statistical significance and bootstrap resampling to determine the reliability of the findings. With practice, HC participants transitioned to a brain-accuracy network incorporating dorsostriatal regions in late-learning stages. The SZ participants did not transition to this pattern despite comparable behavioral results. Instead, successful learners with SZ were differentiated primarily on the basis of greater engagement of perceptual and perceptual-integration brain regions. There is a different spatiotemporal unfolding of brain-learning relationships in SZ. In SZ, given the same amount of practice, the movement from networks suggestive of effortful learning toward subcortically driven procedural one differs from HC participants. Learning performance in SZ is driven by varying levels of engagement in perceptual regions, which suggests perception itself is impaired and may impact downstream, "higher level" cognition.

Imaging plus X: multimodal models of neurodegenerative disease.

PubMed

Oxtoby, Neil P; Alexander, Daniel C

2017-08-01

This article argues that the time is approaching for data-driven disease modelling to take centre stage in the study and management of neurodegenerative disease. The snowstorm of data now available to the clinician defies qualitative evaluation; the heterogeneity of data types complicates integration through traditional statistical methods; and the large datasets becoming available remain far from the big-data sizes necessary for fully data-driven machine-learning approaches. The recent emergence of data-driven disease progression models provides a balance between imposed knowledge of disease features and patterns learned from data. The resulting models are both predictive of disease progression in individual patients and informative in terms of revealing underlying biological patterns. Largely inspired by observational models, data-driven disease progression models have emerged in the last few years as a feasible means for understanding the development of neurodegenerative diseases. These models have revealed insights into frontotemporal dementia, Huntington's disease, multiple sclerosis, Parkinson's disease and other conditions. For example, event-based models have revealed finer graded understanding of progression patterns; self-modelling regression and differential equation models have provided data-driven biomarker trajectories; spatiotemporal models have shown that brain shape changes, for example of the hippocampus, can occur before detectable neurodegeneration; and network models have provided some support for prion-like mechanistic hypotheses of disease propagation. The most mature results are in sporadic Alzheimer's disease, in large part because of the availability of the Alzheimer's disease neuroimaging initiative dataset. Results generally support the prevailing amyloid-led hypothetical model of Alzheimer's disease, while revealing finer detail and insight into disease progression. The emerging field of disease progression modelling provides a natural mechanism to integrate different kinds of information, for example from imaging, serum and cerebrospinal fluid markers and cognitive tests, to obtain new insights into progressive diseases. Such insights include fine-grained longitudinal patterns of neurodegeneration, from early stages, and the heterogeneity of these trajectories over the population. More pragmatically, such models enable finer precision in patient staging and stratification, prediction of progression rates and earlier and better identification of at-risk individuals. We argue that this will make disease progression modelling invaluable for recruitment and end-points in future clinical trials, potentially ameliorating the high failure rate in trials of, e.g., Alzheimer's disease therapies. We review the state of the art in these techniques and discuss the future steps required to translate the ideas to front-line application.

Ultramap v3 - a Revolution in Aerial Photogrammetry

NASA Astrophysics Data System (ADS)

Reitinger, B.; Sormann, M.; Zebedin, L.; Schachinger, B.; Hoefler, M.; Tomasi, R.; Lamperter, M.; Gruber, B.; Schiester, G.; Kobald, M.; Unger, M.; Klaus, A.; Bernoegger, S.; Karner, K.; Wiechert, A.; Ponticelli, M.; Gruber, M.

2012-07-01

In the last years, Microsoft has driven innovation in the aerial photogrammetry community. Besides the market leading camera technology, UltraMap has grown to an outstanding photogrammetric workflow system which enables users to effectively work with large digital aerial image blocks in a highly automated way. Best example is the project-based color balancing approach which automatically balances images to a homogeneous block. UltraMap V3 continues innovation, and offers a revolution in terms of ortho processing. A fully automated dense matching module strives for high precision digital surface models (DSMs) which are calculated either on CPUs or on GPUs using a distributed processing framework. By applying constrained filtering algorithms, a digital terrain model can be derived which in turn can be used for fully automated traditional ortho texturing. By having the knowledge about the underlying geometry, seamlines can be generated automatically by applying cost functions in order to minimize visual disturbing artifacts. By exploiting the generated DSM information, a DSMOrtho is created using the balanced input images. Again, seamlines are detected automatically resulting in an automatically balanced ortho mosaic. Interactive block-based radiometric adjustments lead to a high quality ortho product based on UltraCam imagery. UltraMap v3 is the first fully integrated and interactive solution for supporting UltraCam images at best in order to deliver DSM and ortho imagery.

High Performance Visualization using Query-Driven Visualizationand Analytics

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

Bethel, E. Wes; Campbell, Scott; Dart, Eli

2006-06-15

Query-driven visualization and analytics is a unique approach for high-performance visualization that offers new capabilities for knowledge discovery and hypothesis testing. The new capabilities akin to finding needles in haystacks are the result of combining technologies from the fields of scientific visualization and scientific data management. This approach is crucial for rapid data analysis and visualization in the petascale regime. This article describes how query-driven visualization is applied to a hero-sized network traffic analysis problem.

Handbook of Research on Innovative Technology Integration in Higher Education

ERIC Educational Resources Information Center

Nafukho, Fredrick Muyia, Ed.; Irby, Beverly J., Ed.

2015-01-01

Our increasingly globalized world is driven by shared knowledge, and nowhere is that knowledge more important than in education. Now more than ever, there is a demand for technology that will assist in the spread of knowledge through customized, self-paced, and on-demand learning. The Handbook of Research on Innovative Technology Integration in…

On the Role of Ionospheric Ions in Sawtooth Events

NASA Astrophysics Data System (ADS)

Lund, E. J.; Nowrouzi, N.; Kistler, L. M.; Cai, X.; Frey, H. U.

2018-01-01

Simulations have suggested that feedback of heavy ions originating in the ionosphere is an important mechanism for driving sawtooth injections. However, this feedback may only be necessary for events driven by coronal mass ejections (CMEs), whereas in events driven by streaming interaction regions (SIRs), solar wind variability may suffice to drive these injections. Here we present case studies of two sawtooth events for which in situ data are available in both the magnetotail (Cluster) and the nightside auroral region (FAST), as well as global auroral images (IMAGE). One event, on 1 October 2001, was driven by a CME; the other, on 24 October 2002, was driven by an SIR. The available data do not support the hypothesis that heavy ion feedback is necessary to drive either event. This result is consistent with simulations of the SIR-driven event but disagrees with simulation results for a different CME-driven event. We also find that in an overwhelming majority of the sawtooth injections for which Cluster tail data are available, the O+ observed in the tail comes from the cusp rather than the nightside auroral region, which further casts doubt on the hypothesis that ionospheric heavy ion feedback is the cause of sawtooth injections.

Non-Cartesian MRI Reconstruction With Automatic Regularization Via Monte-Carlo SURE

PubMed Central

Weller, Daniel S.; Nielsen, Jon-Fredrik; Fessler, Jeffrey A.

2013-01-01

Magnetic resonance image (MRI) reconstruction from undersampled k-space data requires regularization to reduce noise and aliasing artifacts. Proper application of regularization however requires appropriate selection of associated regularization parameters. In this work, we develop a data-driven regularization parameter adjustment scheme that minimizes an estimate (based on the principle of Stein’s unbiased risk estimate—SURE) of a suitable weighted squared-error measure in k-space. To compute this SURE-type estimate, we propose a Monte-Carlo scheme that extends our previous approach to inverse problems (e.g., MRI reconstruction) involving complex-valued images. Our approach depends only on the output of a given reconstruction algorithm and does not require knowledge of its internal workings, so it is capable of tackling a wide variety of reconstruction algorithms and nonquadratic regularizers including total variation and those based on the ℓ1-norm. Experiments with simulated and real MR data indicate that the proposed approach is capable of providing near mean squared-error (MSE) optimal regularization parameters for single-coil undersampled non-Cartesian MRI reconstruction. PMID:23591478

Extending the Life of Virtual Heritage: Reuse of Tls Point Clouds in Synthetic Stereoscopic Spherical Images

NASA Astrophysics Data System (ADS)

Garcia Fernandez, J.; Tammi, K.; Joutsiniemi, A.

2017-02-01

Recent advances in Terrestrial Laser Scanner (TLS), in terms of cost and flexibility, have consolidated this technology as an essential tool for the documentation and digitalization of Cultural Heritage. However, once the TLS data is used, it basically remains stored and left to waste.How can highly accurate and dense point clouds (of the built heritage) be processed for its reuse, especially to engage a broader audience? This paper aims to answer this question by a channel that minimizes the need for expert knowledge, while enhancing the interactivity with the as-built digital data: Virtual Heritage Dissemination through the production of VR content. Driven by the ProDigiOUs project's guidelines on data dissemination (EU funded), this paper advances in a production path to transform the point cloud into virtual stereoscopic spherical images, taking into account the different visual features that produce depth perception, and especially those prompting visual fatigue while experiencing the VR content. Finally, we present the results of the Hiedanranta's scans transformed into stereoscopic spherical animations.

Interpretation of Radiological Images: Towards a Framework of Knowledge and Skills

ERIC Educational Resources Information Center

van der Gijp, A.; van der Schaaf, M. F.; van der Schaaf, I. C.; Huige, J. C. B. M.; Ravesloot, C. J.; van Schaik, J. P. J.; ten Cate, Th. J.

2014-01-01

The knowledge and skills that are required for radiological image interpretation are not well documented, even though medical imaging is gaining importance. This study aims to develop a comprehensive framework of knowledge and skills, required for two-dimensional and multiplanar image interpretation in radiology. A mixed-method study approach was…

Integrating Learner-Driven and Organization-Driven Agendas: A Workplace Study.

ERIC Educational Resources Information Center

Lessard, Richard

For the past 4 years, Alpena Community College (ACC) in Michigan has been involved in the Workplace Partnership Project (WPP), a federally funded program which brings basic skills classes into the worksite to help upgrade employees' math, reading, writing, problem-solving, and science knowledge. The college works with partner companies to help…

Visualising community: using participant-driven photo-elicitation for research and application

Treesearch

Paul M. Van Auken; Svein J. Frisvoll; Susan I. Stewart

2010-01-01

Despite a contemporary socio-culture revolving around cultural consumption of imagery, metaphors, representations and "gaze", photo-elicitation is a rarely used method for social scientists and planners to acquire knowledge. In this paper, we discuss participant-driven photo-elicitation, a process in which participant photos are paired with in-depth...

Task-driven optimization of CT tube current modulation and regularization in model-based iterative reconstruction

NASA Astrophysics Data System (ADS)

Gang, Grace J.; Siewerdsen, Jeffrey H.; Webster Stayman, J.

2017-06-01

Tube current modulation (TCM) is routinely adopted on diagnostic CT scanners for dose reduction. Conventional TCM strategies are generally designed for filtered-backprojection (FBP) reconstruction to satisfy simple image quality requirements based on noise. This work investigates TCM designs for model-based iterative reconstruction (MBIR) to achieve optimal imaging performance as determined by a task-based image quality metric. Additionally, regularization is an important aspect of MBIR that is jointly optimized with TCM, and includes both the regularization strength that controls overall smoothness as well as directional weights that permits control of the isotropy/anisotropy of the local noise and resolution properties. Initial investigations focus on a known imaging task at a single location in the image volume. The framework adopts Fourier and analytical approximations for fast estimation of the local noise power spectrum (NPS) and modulation transfer function (MTF)—each carrying dependencies on TCM and regularization. For the single location optimization, the local detectability index (d‧) of the specific task was directly adopted as the objective function. A covariance matrix adaptation evolution strategy (CMA-ES) algorithm was employed to identify the optimal combination of imaging parameters. Evaluations of both conventional and task-driven approaches were performed in an abdomen phantom for a mid-frequency discrimination task in the kidney. Among the conventional strategies, the TCM pattern optimal for FBP using a minimum variance criterion yielded a worse task-based performance compared to an unmodulated strategy when applied to MBIR. Moreover, task-driven TCM designs for MBIR were found to have the opposite behavior from conventional designs for FBP, with greater fluence assigned to the less attenuating views of the abdomen and less fluence to the more attenuating lateral views. Such TCM patterns exaggerate the intrinsic anisotropy of the MTF and NPS as a result of the data weighting in MBIR. Directional penalty design was found to reinforce the same trend. The task-driven approaches outperform conventional approaches, with the maximum improvement in d‧ of 13% given by the joint optimization of TCM and regularization. This work demonstrates that the TCM optimal for MBIR is distinct from conventional strategies proposed for FBP reconstruction and strategies optimal for FBP are suboptimal and may even reduce performance when applied to MBIR. The task-driven imaging framework offers a promising approach for optimizing acquisition and reconstruction for MBIR that can improve imaging performance and/or dose utilization beyond conventional imaging strategies.

Implementing An Image Understanding System Architecture Using Pipe

NASA Astrophysics Data System (ADS)

Luck, Randall L.

1988-03-01

This paper will describe PIPE and how it can be used to implement an image understanding system. Image understanding is the process of developing a description of an image in order to make decisions about its contents. The tasks of image understanding are generally split into low level vision and high level vision. Low level vision is performed by PIPE -a high performance parallel processor with an architecture specifically designed for processing video images at up to 60 fields per second. High level vision is performed by one of several types of serial or parallel computers - depending on the application. An additional processor called ISMAP performs the conversion from iconic image space to symbolic feature space. ISMAP plugs into one of PIPE's slots and is memory mapped into the high level processor. Thus it forms the high speed link between the low and high level vision processors. The mechanisms for bottom-up, data driven processing and top-down, model driven processing are discussed.

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

Experience-driven plasticity in binocular vision

PubMed Central

Klink, P. Christiaan; Brascamp, Jan W.; Blake, Randolph; van Wezel, Richard J.A.

2010-01-01

Summary Experience-driven neuronal plasticity allows the brain to adapt its functional connectivity to recent sensory input. Here we use binocular rivalry [1], an experimental paradigm where conflicting images are presented to the individual eyes, to demonstrate plasticity in the neuronal mechanisms that convert visual information from two separated retinas into single perceptual experiences. Perception during binocular rivalry tended to initially consist of alternations between exclusive representations of monocularly defined images, but upon prolonged exposure, mixture percepts became more prevalent. The completeness of suppression, reflected in the incidence of mixture percepts, plausibly reflects the strength of inhibition that likely plays a role in binocular rivalry [2]. Recovery of exclusivity was possible, but required highly specific binocular stimulation. Documenting the prerequisites for these observed changes in perceptual exclusivity, our experiments suggest experience-driven plasticity at interocular inhibitory synapses, driven by the (lack of) correlated activity of neurons representing the conflicting stimuli. This form of plasticity is consistent with a previously proposed, but largely untested, anti-Hebbian learning mechanism for inhibitory synapses in vision [3, 4]. Our results implicate experience-driven plasticity as one governing principle in the neuronal organization of binocular vision. PMID:20674360

AstroImageJ: Image Processing and Photometric Extraction for Ultra-precise Astronomical Light Curves

NASA Astrophysics Data System (ADS)

Collins, Karen A.; Kielkopf, John F.; Stassun, Keivan G.; Hessman, Frederic V.

2017-02-01

ImageJ is a graphical user interface (GUI) driven, public domain, Java-based, software package for general image processing traditionally used mainly in life sciences fields. The image processing capabilities of ImageJ are useful and extendable to other scientific fields. Here we present AstroImageJ (AIJ), which provides an astronomy specific image display environment and tools for astronomy specific image calibration and data reduction. Although AIJ maintains the general purpose image processing capabilities of ImageJ, AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to the astrometry.net web portal for plate solving images. AIJ provides research grade image calibration and analysis tools with a GUI driven approach, and easily installed cross-platform compatibility. It enables new users, even at the level of undergraduate student, high school student, or amateur astronomer, to quickly start processing, modeling, and plotting astronomical image data with one tightly integrated software package.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

On uncertainty in information and ignorance in knowledge

NASA Astrophysics Data System (ADS)

Ayyub, Bilal M.

2010-05-01

This paper provides an overview of working definitions of knowledge, ignorance, information and uncertainty and summarises formalised philosophical and mathematical framework for their analyses. It provides a comparative examination of the generalised information theory and the generalised theory of uncertainty. It summarises foundational bases for assessing the reliability of knowledge constructed as a collective set of justified true beliefs. It discusses system complexity for ancestor simulation potentials. It offers value-driven communication means of knowledge and contrarian knowledge using memes and memetics.

Laser Wakefield Acceleration: Structural and Dynamic Studies. Final Technical Report ER40954

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

Downer, Michael C.

2014-04-30

Particle accelerators enable scientists to study the fundamental structure of the universe, but have become the largest and most expensive of scientific instruments. In this project, we advanced the science and technology of laser-plasma accelerators, which are thousands of times smaller and less expensive than their conventional counterparts. In a laser-plasma accelerator, a powerful laser pulse exerts light pressure on an ionized gas, or plasma, thereby driving an electron density wave, which resembles the wake behind a boat. Electrostatic fields within this plasma wake reach tens of billions of volts per meter, fields far stronger than ordinary non-plasma matter (suchmore » as the matter that a conventional accelerator is made of) can withstand. Under the right conditions, stray electrons from the surrounding plasma become trapped within these “wake-fields”, surf them, and acquire energy much faster than is possible in a conventional accelerator. Laser-plasma accelerators thus might herald a new generation of compact, low-cost accelerators for future particle physics, x-ray and medical research. In this project, we made two major advances in the science of laser-plasma accelerators. The first of these was to accelerate electrons beyond 1 gigaelectronvolt (1 GeV) for the first time. In experimental results reported in Nature Communications in 2013, about 1 billion electrons were captured from a tenuous plasma (about 1/100 of atmosphere density) and accelerated to 2 GeV within about one inch, while maintaining less than 5% energy spread, and spreading out less than ½ milliradian (i.e. ½ millimeter per meter of travel). Low energy spread and high beam collimation are important for applications of accelerators as coherent x-ray sources or particle colliders. This advance was made possible by exploiting unique properties of the Texas Petawatt Laser, a powerful laser at the University of Texas at Austin that produces pulses of 150 femtoseconds (1 femtosecond is 10-15 seconds) in duration and 150 Joules in energy (equivalent to the muzzle energy of a small pistol bullet). This duration was well matched to the natural electron density oscillation period of plasma of 1/100 atmospheric density, enabling efficient excitation of a plasma wake, while this energy was sufficient to drive a high-amplitude wake of the right shape to produce an energetic, collimated electron beam. Continuing research is aimed at increasing electron energy even further, increasing the number of electrons captured and accelerated, and developing applications of the compact, multi-GeV accelerator as a coherent, hard x-ray source for materials science, biomedical imaging and homeland security applications. The second major advance under this project was to develop new methods of visualizing the laser-driven plasma wake structures that underlie laser-plasma accelerators. Visualizing these structures is essential to understanding, optimizing and scaling laser-plasma accelerators. Yet prior to work under this project, computer simulations based on estimated initial conditions were the sole source of detailed knowledge of the complex, evolving internal structure of laser-driven plasma wakes. In this project we developed and demonstrated a suite of optical visualization methods based on well-known methods such as holography, streak cameras, and coherence tomography, but adapted to the ultrafast, light-speed, microscopic world of laser-driven plasma wakes. Our methods output images of laser-driven plasma structures in a single laser shot. We first reported snapshots of low-amplitude laser wakes in Nature Physics in 2006. We subsequently reported images of high-amplitude laser-driven plasma “bubbles”, which are important for producing electron beams with low energy spread, in Physical Review Letters in 2010. More recently, we have figured out how to image laser-driven structures that change shape while propagating in a single laser shot. The latter techniques, which use the methods of computerized tomography, were demonstrated on test objects – e.g. laser-driven filaments in air and glass – and reported in Optics Letters in 2013 and Nature Communications in 2014. Their output is a multi-frame movie rather than a snapshot. Continuing research is aimed at applying these tomographic methods directly to evolving laser-driven plasma accelerator structures in our laboratory, then, once perfected, to exporting them to plasma-based accelerator laboratories around the world as standard in-line metrology instruments.« less

Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.

PubMed

Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S; Venkatasubramanian, Venkat

2017-10-11

There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. ©Zhizun Zhang, Mila C Gonzalez, Stephen S Morse, Venkat Venkatasubramanian. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.10.2017.

Professional development for primary science teaching in Thailand: Knowledge, orientations, and practices of professional developers and professional development participants

NASA Astrophysics Data System (ADS)

Musikul, Kusalin

The purpose of this study was to examine an entire PD project as a case to understand the dynamic nature of science PD in a holistic manner. I used a pedagogical content knowledge model by Magnusson, Krajcik, and Borko (1999) as my theoretical framework in examining the professional developers' and teacher participants' knowledge, orientation, and practice for professional development and elementary science teaching. The case study is my research tradition; I used grounded theory for data analysis. The primary data sources were interview, card sort activity, and observation field notes collected during the PD and subsequently in teacher participants' classrooms. Secondary data sources were documents and artifacts that I collected from the professional developers and teachers. An analysis of the data led me to interpret the following findings: (a) the professional developers displayed multiple orientations. These orientations included activity-driven, didactic, discovery, and pedagogy-driven orientations. The orientations that were found among the professional developers deviated from the reformed Thai Science Education Standards; (b) the professional developers had limited PCK for PD, which were knowledge of teachers' learning, knowledge of PD strategies, knowledge of PD curriculum, and knowledge of assessment.; (c) the professional developers' knowledge and orientations influenced their decisions in selecting PD activities and teaching approaches; (d) their orientations and PCK as well as the time factor influenced the design and implementation of the professional development; (e) the elementary teachers displayed didactic, activity-driven, and academic rigor orientations. The orientations that the teachers displayed deviated from the reformed Thai Science Education Standards; and (f) the elementary teachers exhibited limited PCK. It is evident that the limitation of one type of knowledge resulted in an ineffective use of other components of PCK. This study demonstrates the nature of PD in the context of Thailand in a holistic view to understand knowledge, orientation, and implementation of professional developers and professional development participants. Furthermore, the findings have implications for professional development and professional developers in Thailand and include worldwide with respect to promoting sustain and intensive professional development and developing professional developers.

Information Professional or IT Professional?: The Knowledge and Skills Required by Academic Librarians in the Digital Library Environment

ERIC Educational Resources Information Center

Raju, Jaya

2017-01-01

As library and information science (LIS) becomes an increasingly technology-driven profession, particularly in the academic library environment, questions arise as to the extent of information technology (IT) knowledge and skills that LIS professionals require. The purpose of this paper is to ascertain what IT knowledge and skills are needed by…

Integrative pathway knowledge bases as a tool for systems molecular medicine.

PubMed

Liang, Mingyu

2007-08-20

There exists a sense of urgency to begin to generate a cohesive assembly of biomedical knowledge as the pace of knowledge accumulation accelerates. The urgency is in part driven by the emergence of systems molecular medicine that emphasizes the combination of systems analysis and molecular dissection in the future of medical practice and research. A potentially powerful approach is to build integrative pathway knowledge bases that link organ systems function with molecules.

Knowledge Management in Naval Sea Systems Command: A Structure for Performance Driven Knowledge Management Initiative

DTIC Science & Technology

2002-09-01

interested users. The loyalty of the knowledge worker is to his/her knowledge community and not the organization per se [Ref. 40]. Sharing is inherently...Command (NAVSEA). The former commander of NAVSEA, Vice Admiral Pete Nanos (who retired in June 2002), introduced the branding concept in 1999 to...entire organization to embrace the changes. New process initiation actions such as awareness training, storytelling , rewards, new hire

Theory-driven intervention improves calcium intake, osteoporosis knowledge, and self-efficacy in community-dwelling older Black adults.

PubMed

Babatunde, Oyinlola T; Himburg, Susan P; Newman, Frederick L; Campa, Adriana; Dixon, Zisca

2011-01-01

To assess the effectiveness of an osteoporosis education program to improve calcium intake, knowledge, and self-efficacy in community-dwelling older Black adults. Randomized repeated measures experimental design. Churches and community-based organizations. Men and women (n = 110) 50 years old and older from 3 south Florida counties. Participants randomly assigned to either of 2 groups: Group 1 (experimental group) or Group 2 (wait-list control group). Group 1 participated in 6 weekly education program sessions immediately following baseline assessment, and Group 2 started the program following Group 1's program completion. A tested curriculum was adapted to meet the needs of the target population. Dietary calcium intake, osteoporosis knowledge, health beliefs, and self-efficacy. Descriptive and summary statistics, repeated measures analysis of variance, and regression analysis. Of the total participants, 84.6% completed the study (mean age = 70.2 years). Overall, an educational program developed with a theoretical background was associated with improvement in calcium intake, knowledge, and self-efficacy, with no effect on most health belief subscales. Assigned group was the major predictor of change in calcium intake. A theory-driven approach is valuable in improving behavior to promote bone health in this population. Health professionals should consider using more theory-driven approaches in intervention studies. Copyright © 2011 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Sparsity-driven coupled imaging and autofocusing for interferometric SAR

NASA Astrophysics Data System (ADS)

Zengin, Oǧuzcan; Khwaja, Ahmed Shaharyar; ćetin, Müjdat

2018-04-01

We propose a sparsity-driven method for coupled image formation and autofocusing based on multi-channel data collected in interferometric synthetic aperture radar (IfSAR). Relative phase between SAR images contains valuable information. For example, it can be used to estimate the height of the scene in SAR interferometry. However, this relative phase could be degraded when independent enhancement methods are used over SAR image pairs. Previously, Ramakrishnan et al. proposed a coupled multi-channel image enhancement technique, based on a dual descent method, which exhibits better performance in phase preservation compared to independent enhancement methods. Their work involves a coupled optimization formulation that uses a sparsity enforcing penalty term as well as a constraint tying the multichannel images together to preserve the cross-channel information. In addition to independent enhancement, the relative phase between the acquisitions can be degraded due to other factors as well, such as platform location uncertainties, leading to phase errors in the data and defocusing in the formed imagery. The performance of airborne SAR systems can be affected severely by such errors. We propose an optimization formulation that combines Ramakrishnan et al.'s coupled IfSAR enhancement method with the sparsity-driven autofocus (SDA) approach of Önhon and Çetin to alleviate the effects of phase errors due to motion errors in the context of IfSAR imaging. Our method solves the joint optimization problem with a Lagrangian optimization method iteratively. In our preliminary experimental analysis, we have obtained results of our method on synthetic SAR images and compared its performance to existing methods.

Toward a Unified Theory of Visual Area V4

PubMed Central

Roe, Anna W.; Chelazzi, Leonardo; Connor, Charles E.; Conway, Bevil R.; Fujita, Ichiro; Gallant, Jack L.; Lu, Haidong; Vanduffel, Wim

2016-01-01

Visual area V4 is a midtier cortical area in the ventral visual pathway. It is crucial for visual object recognition and has been a focus of many studies on visual attention. However, there is no unifying view of V4’s role in visual processing. Neither is there an understanding of how its role in feature processing interfaces with its role in visual attention. This review captures our current knowledge of V4, largely derived from electrophysiological and imaging studies in the macaque monkey. Based on recent discovery of functionally specific domains in V4, we propose that the unifying function of V4 circuitry is to enable selective extraction of specific functional domain-based networks, whether it be by bottom-up specification of object features or by top-down attentionally driven selection. PMID:22500626

Forty Years of Ebolavirus Molecular Biology: Understanding a Novel Disease Agent Through the Development and Application of New Technologies.

PubMed

Groseth, Allison; Hoenen, Thomas

2017-01-01

Molecular biology is a broad discipline that seeks to understand biological phenomena at a molecular level, and achieves this through the study of DNA, RNA, proteins, and/or other macromolecules (e.g., those involved in the modification of these substrates). Consequently, it relies on the availability of a wide variety of methods that deal with the collection, preservation, inactivation, separation, manipulation, imaging, and analysis of these molecules. As such the state of the art in the field of ebolavirus molecular biology research (and that of all other viruses) is largely intertwined with, if not driven by, advancements in the technical methodologies available for these kinds of studies. Here we review of the current state of our knowledge regarding ebolavirus biology and emphasize the associated methods that made these discoveries possible.

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

An IDL-based analysis package for COBE and other skycube-formatted astronomical data

NASA Technical Reports Server (NTRS)

Ewing, J. A.; Isaacman, Richard B.; Gales, J. M.

1992-01-01

UIMAGE is a data analysis package written in IDL for the Cosmic Background Explorer (COBE) project. COBE has extraordinarily stringent accuracy requirements: 1 percent mid-infrared absolute photometry, 0.01 percent submillimeter absolute spectrometry, and 0.0001 percent submillimeter relative photometry. Thus, many of the transformations and image enhancements common to analysis of large data sets must be done with special care. UIMAGE is unusual in this sense in that it performs as many of its operations as possible on the data in its native format and projection, which in the case of COBE is the quadrilateralized sphereical cube ('skycube'). That is, after reprojecting the data, e.g., onto an Aitoff map, the user who performs an operation such as taking a crosscut or extracting data from a pixel is transparently acting upon the skycube data from which the projection was made, thereby preserving the accuracy of the result. Current plans call for formatting external data bases such as CO maps into the skycube format with a high-accuracy transformation, thereby allowing Guest Investigators to use UIMAGE for direct comparison of the COBE maps with those at other wavelengths from other instruments. It is completely menu-driven so that its use requires no knowledge of IDL. Its functionality includes I/O from the COBE archives, FITS files, and IDL save sets as well as standard analysis operations such as smoothing, reprojection, zooming, statistics of areas, spectral analysis, etc. One of UIMAGE's more advanced and attractive features is its terminal independence. Most of the operations (e.g., menu-item selection or pixel selection) that are driven by the mouse on an X-windows terminal are also available using arrow keys and keyboard entry (e.g., pixel coordinates) on VT200 and Tektronix-class terminals. Even limited grey scales of images are available this way. Obviously, image processing is very limited on this type of terminal, but it is nonetheless surprising how much analysis can be done on that medium. Such flexibility has the virtue of expanding the user community to those who must work remotely on non-image terminals, e.g., via modem.

Smartphones as multimodal communication devices to facilitate clinical knowledge processes: randomized controlled trial.

PubMed

Pimmer, Christoph; Mateescu, Magdalena; Zahn, Carmen; Genewein, Urs

2013-11-27

Despite the widespread use and advancements of mobile technology that facilitate rich communication modes, there is little evidence demonstrating the value of smartphones for effective interclinician communication and knowledge processes. The objective of this study was to determine the effects of different synchronous smartphone-based modes of communication, such as (1) speech only, (2) speech and images, and (3) speech, images, and image annotation (guided noticing) on the recall and transfer of visually and verbally represented medical knowledge. The experiment was conducted from November 2011 to May 2012 at the University Hospital Basel (Switzerland) with 42 medical students in a master's program. All participants analyzed a standardized case (a patient with a subcapital fracture of the fifth metacarpal bone) based on a radiological image, photographs of the hand, and textual descriptions, and were asked to consult a remote surgical specialist via a smartphone. Participants were randomly assigned to 3 experimental conditions/groups. In group 1, the specialist provided verbal explanations (speech only). In group 2, the specialist provided verbal explanations and displayed the radiological image and the photographs to the participants (speech and images). In group 3, the specialist provided verbal explanations, displayed the radiological image and the photographs, and annotated the radiological image by drawing structures/angle elements (speech, images, and image annotation). To assess knowledge recall, participants were asked to write brief summaries of the case (verbally represented knowledge) after the consultation and to re-analyze the diagnostic images (visually represented knowledge). To assess knowledge transfer, participants analyzed a similar case without specialist support. Data analysis by ANOVA found that participants in groups 2 and 3 (images used) evaluated the support provided by the specialist as significantly more positive than group 1, the speech-only group (group 1: mean 4.08, SD 0.90; group 2: mean 4.73, SD 0.59; group 3: mean 4.93, SD 0.25; F2,39=6.76, P=.003; partial η(2)=0.26, 1-β=.90). However, significant positive effects on the recall and transfer of visually represented medical knowledge were only observed when the smartphone-based communication involved the combination of speech, images, and image annotation (group 3). There were no significant positive effects on the recall and transfer of visually represented knowledge between group 1 (speech only) and group 2 (speech and images). No significant differences were observed between the groups regarding verbally represented medical knowledge. The results show (1) the value of annotation functions for digital and mobile technology for interclinician communication and medical informatics, and (2) the use of guided noticing (the integration of speech, images, and image annotation) leads to significantly improved knowledge gains for visually represented knowledge. This is particularly valuable in situations involving complex visual subject matters, typical in clinical practice.

Smartphones as Multimodal Communication Devices to Facilitate Clinical Knowledge Processes: Randomized Controlled Trial

PubMed Central

Mateescu, Magdalena; Zahn, Carmen; Genewein, Urs

2013-01-01

Background Despite the widespread use and advancements of mobile technology that facilitate rich communication modes, there is little evidence demonstrating the value of smartphones for effective interclinician communication and knowledge processes. Objective The objective of this study was to determine the effects of different synchronous smartphone-based modes of communication, such as (1) speech only, (2) speech and images, and (3) speech, images, and image annotation (guided noticing) on the recall and transfer of visually and verbally represented medical knowledge. Methods The experiment was conducted from November 2011 to May 2012 at the University Hospital Basel (Switzerland) with 42 medical students in a master’s program. All participants analyzed a standardized case (a patient with a subcapital fracture of the fifth metacarpal bone) based on a radiological image, photographs of the hand, and textual descriptions, and were asked to consult a remote surgical specialist via a smartphone. Participants were randomly assigned to 3 experimental conditions/groups. In group 1, the specialist provided verbal explanations (speech only). In group 2, the specialist provided verbal explanations and displayed the radiological image and the photographs to the participants (speech and images). In group 3, the specialist provided verbal explanations, displayed the radiological image and the photographs, and annotated the radiological image by drawing structures/angle elements (speech, images, and image annotation). To assess knowledge recall, participants were asked to write brief summaries of the case (verbally represented knowledge) after the consultation and to re-analyze the diagnostic images (visually represented knowledge). To assess knowledge transfer, participants analyzed a similar case without specialist support. Results Data analysis by ANOVA found that participants in groups 2 and 3 (images used) evaluated the support provided by the specialist as significantly more positive than group 1, the speech-only group (group 1: mean 4.08, SD 0.90; group 2: mean 4.73, SD 0.59; group 3: mean 4.93, SD 0.25; F 2,39=6.76, P=.003; partial η2=0.26, 1–β=.90). However, significant positive effects on the recall and transfer of visually represented medical knowledge were only observed when the smartphone-based communication involved the combination of speech, images, and image annotation (group 3). There were no significant positive effects on the recall and transfer of visually represented knowledge between group 1 (speech only) and group 2 (speech and images). No significant differences were observed between the groups regarding verbally represented medical knowledge. Conclusions The results show (1) the value of annotation functions for digital and mobile technology for interclinician communication and medical informatics, and (2) the use of guided noticing (the integration of speech, images, and image annotation) leads to significantly improved knowledge gains for visually represented knowledge. This is particularly valuable in situations involving complex visual subject matters, typical in clinical practice. PMID:24284080

Nanoscale imaging of magnetization reversal driven by spin-orbit torque

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

Gilbert, Ian; Chen, P. J.; Gopman, Daniel B.

We use scanning electron microscopy with polarization analysis to image deterministic, spin-orbit torque-driven magnetization reversal of in-plane magnetized CoFeB rectangles in zero applied magnetic field. The spin-orbit torque is generated by running a current through heavy metal microstrips, either Pt or Ta, upon which the CoFeB rectangles are deposited. We image the CoFeB magnetization before and after a current pulse to see the effect of spin-orbit torque on the magnetic nanostructure. The observed changes in magnetic structure can be complex, deviating significantly from a simple macrospin approximation, especially in larger elements. Overall, however, the directions of the magnetization reversal inmore » the Pt and Ta devices are opposite, consistent with the opposite signs of the spin Hall angles of these materials. Lastly, our results elucidate the effects of current density, geometry, and magnetic domain structure on magnetization switching driven by spin-orbit torque.« less

Segmentation-driven compound document coding based on H.264/AVC-INTRA.

PubMed

Zaghetto, Alexandre; de Queiroz, Ricardo L

2007-07-01

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.

Nanoscale imaging of magnetization reversal driven by spin-orbit torque

DOE PAGES

Gilbert, Ian; Chen, P. J.; Gopman, Daniel B.; ...

2016-09-23

We use scanning electron microscopy with polarization analysis to image deterministic, spin-orbit torque-driven magnetization reversal of in-plane magnetized CoFeB rectangles in zero applied magnetic field. The spin-orbit torque is generated by running a current through heavy metal microstrips, either Pt or Ta, upon which the CoFeB rectangles are deposited. We image the CoFeB magnetization before and after a current pulse to see the effect of spin-orbit torque on the magnetic nanostructure. The observed changes in magnetic structure can be complex, deviating significantly from a simple macrospin approximation, especially in larger elements. Overall, however, the directions of the magnetization reversal inmore » the Pt and Ta devices are opposite, consistent with the opposite signs of the spin Hall angles of these materials. Lastly, our results elucidate the effects of current density, geometry, and magnetic domain structure on magnetization switching driven by spin-orbit torque.« less

Knowledge Management and the Academy

ERIC Educational Resources Information Center

Cain, Timothy J.; Branin, Joseph J.; Sherman, W. Michael

2008-01-01

Universities and colleges generate extraordinary quantities of knowledge and innovation, but in many ways the academy struggles to keep pace with the digital revolution. Growing pressures are reshaping how universities must do business--students expecting enhanced access and support, administrators eager to make data-driven strategic decisions,…

Recognition without Awareness: An Elusive Phenomenon

ERIC Educational Resources Information Center

Jeneson, Annette; Kirwan, C. Brock; Squire, Larry R.

2010-01-01

Two recent studies described conditions under which recognition memory performance appeared to be driven by nondeclarative memory. Specifically, participants successfully discriminated old images from highly similar new images even when no conscious memory for the images could be retrieved. Paradoxically, recognition performance was better when…

Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

DTIC Science & Technology

1989-08-01

Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17

Optical diagnostics of turbulent mixing in explosively-driven shock tube

NASA Astrophysics Data System (ADS)

Anderson, James; Hargather, Michael

2016-11-01

Explosively-driven shock tube experiments were performed to investigate the turbulent mixing of explosive product gases and ambient air. A small detonator initiated Al / I2O5 thermite, which produced a shock wave and expanding product gases. Schlieren and imaging spectroscopy were applied simultaneously along a common optical path to identify correlations between turbulent structures and spatially-resolved absorbance. The schlieren imaging identifies flow features including shock waves and turbulent structures while the imaging spectroscopy identifies regions of iodine gas presence in the product gases. Pressure transducers located before and after the optical diagnostic section measure time-resolved pressure. Shock speed is measured from tracking the leading edge of the shockwave in the schlieren images and from the pressure transducers. The turbulent mixing characteristics were determined using digital image processing. Results show changes in shock speed, product gas propagation, and species concentrations for varied explosive charge mass. Funded by DTRA Grant HDTRA1-14-1-0070.

A Hybrid Knowledge-Based and Data-Driven Approach to Identifying Semantically Similar Concepts

PubMed Central

Pivovarov, Rimma; Elhadad, Noémie

2012-01-01

An open research question when leveraging ontological knowledge is when to treat different concepts separately from each other and when to aggregate them. For instance, concepts for the terms "paroxysmal cough" and "nocturnal cough" might be aggregated in a kidney disease study, but should be left separate in a pneumonia study. Determining whether two concepts are similar enough to be aggregated can help build better datasets for data mining purposes and avoid signal dilution. Quantifying the similarity among concepts is a difficult task, however, in part because such similarity is context-dependent. We propose a comprehensive method, which computes a similarity score for a concept pair by combining data-driven and ontology-driven knowledge. We demonstrate our method on concepts from SNOMED-CT and on a corpus of clinical notes of patients with chronic kidney disease. By combining information from usage patterns in clinical notes and from ontological structure, the method can prune out concepts that are simply related from those which are semantically similar. When evaluated against a list of concept pairs annotated for similarity, our method reaches an AUC (area under the curve) of 92%. PMID:22289420

RADIOLOGY EDUCATION: A PILOT STUDY TO ASSESS KNOWLEDGE OF MEDICAL STUDENTS REGARDING IMAGING IN TRAUMA.

PubMed

Siddiqui, Saad; Saeed, Muhammad Anwar; Shah, Noreen; Nadeem, Naila

2015-01-01

Trauma remains one of the most frequent presentations in emergency departments. Imaging has established role in setting of acute trauma with ability to identify potentially fatal conditions. Adequate knowledge of health professionals regarding trauma imaging is vital for improved healthcare. In this work we try to assess knowledge of medical students regarding imaging in trauma as well as identify most effective way of imparting radiology education. This cross-sectional pilot study was conducted at Aga Khan University Medical College & Khyber Girls Medical College, to assess knowledge of medical students regarding imaging protocols practiced in initial management of trauma patients. Only 40 & 20% respectively were able to identify radiographs included in trauma series. Very few had knowledge of correct indication for Focused abdominal sonography in trauma. Clinical radiology rotation was reported as best way of learning radiology. Change in curricula & restructuring of clinical radiology rotation structure is needed to improve knowledge regarding Trauma imaging.

Schema-Driven Facilitation of New Hierarchy Learning in the Transitive Inference Paradigm

ERIC Educational Resources Information Center

Kumaran, Dharshan

2013-01-01

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in…

Submillisievert Radiation Dose Coronary CT Angiography: Clinical Impact of the Knowledge-Based Iterative Model Reconstruction.

PubMed

Iyama, Yuji; Nakaura, Takeshi; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Sakaino, Naritsugu; Tokuyasu, Shinichi; Osakabe, Hirokazu; Harada, Kazunori; Yamashita, Yasuyuki

2016-11-01

The purpose of this study was to evaluate the noise and image quality of images reconstructed with a knowledge-based iterative model reconstruction (knowledge-based IMR) in ultra-low dose cardiac computed tomography (CT). We performed submillisievert radiation dose coronary CT angiography on 43 patients. We also performed a phantom study to evaluate the influence of object size with the automatic exposure control phantom. We reconstructed clinical and phantom studies with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and knowledge-based IMR. We measured effective dose of patients and compared CT number, image noise, and contrast noise ratio in ascending aorta of each reconstruction technique. We compared the relationship between image noise and body mass index for the clinical study, and object size for phantom study. The mean effective dose was 0.98 ± 0.25 mSv. The image noise of knowledge-based IMR images was significantly lower than those of FBP and hybrid IR images (knowledge-based IMR: 19.4 ± 2.8; FBP: 126.7 ± 35.0; hybrid IR: 48.8 ± 12.8, respectively) (P < .01). The contrast noise ratio of knowledge-based IMR images was significantly higher than those of FBP and hybrid IR images (knowledge-based IMR: 29.1 ± 5.4; FBP: 4.6 ± 1.3; hybrid IR: 13.1 ± 3.5, respectively) (P < .01). There were moderate correlations between image noise and body mass index in FBP (r = 0.57, P < .01) and hybrid IR techniques (r = 0.42, P < .01); however, these correlations were weak in knowledge-based IMR (r = 0.27, P < .01). Compared to FBP and hybrid IR, the knowledge-based IMR offers significant noise reduction and improvement in image quality in submillisievert radiation dose cardiac CT. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

What can organisational theory offer knowledge translation in healthcare? A thematic and lexical analysis.

PubMed

Dadich, Ann; Doloswala, Navin

2018-05-10

Despite the relative abundance of frameworks and models to guide implementation science, the explicit use of theory is limited. Bringing together two seemingly disparate fields of research, this article asks, what can organisational theory offer implementation science? This is examined by applying a theoretical lens that incorporates agency, institutional, and situated change theories to understand the implementation of healthcare knowledge into practice. Interviews were conducted with 20 general practitioners (GPs) before and after using a resource to facilitate evidence-based sexual healthcare. Research material was analysed using two approaches - researcher-driven thematic coding and lexical analysis, which was relatively less researcher-driven. The theoretical lens elucidated the complex pathways of knowledge translation. More specifically, agency theory revealed tensions between the GP as agent and their organisations and patients as principals. Institutional theory highlighted the importance of GP-embeddedness within their chosen specialty of general practice; their medical profession; and the practice in which they worked. Situated change theory exposed the role of localised adaptations over time - a metamorphosis. This study has theoretical, methodological, and practical implications. Theoretically, it is the first to examine knowledge translation using a lens premised on agency, institutional, and situated change theories. Methodologically, the study highlights the complementary value of researcher-driven and researcher-guided analysis of qualitative research material. Practically, this study signposts opportunities to facilitate knowledge translation - more specifically, it suggests that efforts to shape clinician practices should accommodate the interrelated influence of the agent and the institution, and recognise that change can be ever so subtle.

On edge-aware path-based color spatial sampling for Retinex: from Termite Retinex to Light Energy-driven Termite Retinex

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Cordone, Roberto; Serapioni, Raul Paolo; Lecca, Michela

2017-05-01

Retinex theory estimates the human color sensation at any observed point by correcting its color based on the spatial arrangement of the colors in proximate regions. We revise two recent path-based, edge-aware Retinex implementations: Termite Retinex (TR) and Energy-driven Termite Retinex (ETR). As the original Retinex implementation, TR and ETR scan the neighborhood of any image pixel by paths and rescale their chromatic intensities by intensity levels computed by reworking the colors of the pixels on the paths. Our interest in TR and ETR is due to their unique, content-based scanning scheme, which uses the image edges to define the paths and exploits a swarm intelligence model for guiding the spatial exploration of the image. The exploration scheme of ETR has been showed to be particularly effective: its paths are local minima of an energy functional, designed to favor the sampling of image pixels highly relevant to color sensation. Nevertheless, since its computational complexity makes ETR poorly practicable, here we present a light version of it, named Light Energy-driven TR, and obtained from ETR by implementing a modified, optimized minimization procedure and by exploiting parallel computing.

Mystery #21 Answer

Atmospheric Science Data Center

2013-04-22

article title:  MISR Mystery Image Quiz #21: Actinoform Clouds ... This mystery concerns a particular type of cloud, one example of which was imaged by the Multi-angle Imaging SpectroRadiometer (MISR) ... ) These clouds are commonly tracked using propeller-driven research aircraft. Answer: C is True. The weather satellite, TIROS ...

In-vivo gingival sulcus imaging using full-range, complex-conjugate-free, endoscopic spectral domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Huang, Yong; Zhang, Kang; Yi, WonJin; Kang, Jin U.

2012-01-01

Frequent monitoring of gingival sulcus will provide valuable information for judging the presence and severity of periodontal disease. Optical coherence tomography, as a 3D high resolution high speed imaging modality is able to provide information for pocket depth, gum contour, gum texture, gum recession simultaneously. A handheld forward-viewing miniature resonant fiber-scanning probe was developed for in-vivo gingival sulcus imaging. The fiber cantilever driven by magnetic force vibrates at resonant frequency. A synchronized linear phase-modulation was applied in the reference arm by the galvanometer-driven reference mirror. Full-range, complex-conjugate-free, real-time endoscopic SD-OCT was achieved by accelerating the data process using graphics processing unit. Preliminary results showed a real-time in-vivo imaging at 33 fps with an imaging range of lateral 2 mm by depth 3 mm. Gap between the tooth and gum area was clearly visualized. Further quantification analysis of the gingival sulcus will be performed on the image acquired.

Entrepreneurial University: India's Response. Research & Occasional Paper Series: CSHE.2.08

ERIC Educational Resources Information Center

Gupta, Asha

2008-01-01

The object of this paper is to analyze the concepts of "entrepreneurship" and "entrepreneurial university" in the broader context of globalization, technological innovations and the emergence of knowledge-based and technology-driven economies. Instead of epistemological and organizational forms of knowledge production and…

Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI

NASA Astrophysics Data System (ADS)

Hwuang, Eileen; Rusu, Mirabela; Karthigeyan, Sudha; Agner, Shannon C.; Sparks, Rachel; Shih, Natalie; Tomaszewski, John E.; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

2014-03-01

Multi-modal image registration is needed to align medical images collected from different protocols or imaging sources, thereby allowing the mapping of complementary information between images. One challenge of multimodal image registration is that typical similarity measures rely on statistical correlations between image intensities to determine anatomical alignment. The use of alternate image representations could allow for mapping of intensities into a space or representation such that the multimodal images appear more similar, thus facilitating their co-registration. In this work, we present a spectral embedding based registration (SERg) method that uses non-linearly embedded representations obtained from independent components of statistical texture maps of the original images to facilitate multimodal image registration. Our methodology comprises the following main steps: 1) image-derived textural representation of the original images, 2) dimensionality reduction using independent component analysis (ICA), 3) spectral embedding to generate the alternate representations, and 4) image registration. The rationale behind our approach is that SERg yields embedded representations that can allow for very different looking images to appear more similar, thereby facilitating improved co-registration. Statistical texture features are derived from the image intensities and then reduced to a smaller set by using independent component analysis to remove redundant information. Spectral embedding generates a new representation by eigendecomposition from which only the most important eigenvectors are selected. This helps to accentuate areas of salience based on modality-invariant structural information and therefore better identifies corresponding regions in both the template and target images. The spirit behind SERg is that image registration driven by these areas of salience and correspondence should improve alignment accuracy. In this work, SERg is implemented using Demons to allow the algorithm to more effectively register multimodal images. SERg is also tested within the free-form deformation framework driven by mutual information. Nine pairs of synthetic T1-weighted to T2-weighted brain MRI were registered under the following conditions: five levels of noise (0%, 1%, 3%, 5%, and 7%) and two levels of bias field (20% and 40%) each with and without noise. We demonstrate that across all of these conditions, SERg yields a mean squared error that is 81.51% lower than that of Demons driven by MRI intensity alone. We also spatially align twenty-six ex vivo histology sections and in vivo prostate MRI in order to map the spatial extent of prostate cancer onto corresponding radiologic imaging. SERg performs better than intensity registration by decreasing the root mean squared distance of annotated landmarks in the prostate gland via both Demons algorithm and mutual information-driven free-form deformation. In both synthetic and clinical experiments, the observed improvement in alignment of the template and target images suggest the utility of parametric eigenvector representations and hence SERg for multimodal image registration.

SU-F-E-10: Student-Driven Exploration of Radiographic Material Properties, Phantom Construction, and Clinical Workflows Or: The Extraordinary Life of CANDY MAN

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

Mahon, RN; Riblett, MJ; Hugo, GD

Purpose: To develop a hands-on learning experience that explores the radiological and structural properties of everyday items and applies this knowledge to design a simple phantom for radiotherapy exercises. Methods: Students were asked to compile a list of readily available materials thought to have radiation attenuation properties similar to tissues within the human torso. Participants scanned samples of suggested materials and regions of interest (ROIs) were used to characterize bulk attenuation properties. Properties of each material were assessed via comparison to a Gammex Tissue characterization phantom and used to construct a list of inexpensive near-tissue-equivalent materials. Critical discussions focusing onmore » samples found to differ from student expectations were used to revise and narrow the comprehensive list. From their newly acquired knowledge, students designed and constructed a simple thoracic phantom for use in a simulated clinical workflow. Students were tasked with setting up the phantom and acquiring planning CT images for use in treatment planning and dose delivery. Results: Under engineer and physicist supervision, students were trained to use a CT simulator and acquired images for approximately 60 different foodstuffs, candies, and household items. Through peer discussion, students gained valuable insights and were made to review preconceptions about radiographic material properties. From a subset of imaged materials, a simple phantom was successfully designed and constructed to represent a human thorax. Students received hands-on experience with clinical treatment workflows by learning how to perform CT simulation, create a treatment plan for an embedded tumor, align the phantom for treatment, and deliver a treatment fraction. Conclusion: In this activity, students demonstrated their ability to reason through the radiographic material selection process, construct a simple phantom to specifications, and exercise their knowledge of clinical workflows. Furthermore, the enjoyable and inexpensive nature of this project proved to attract participant interest and drive creative exploration. Mahon and Riblett have nothing to disclose; Hugo has a research agreement with Phillips Medical systems, a license agreement with Varian Medical Systems, research grants from the National Institute of Health. Authors do not have any potential conflicts of interest to disclose.« less

Passively Driven Probe Based on Miniaturized Propeller for Intravascular Optical Coherence Tomography.

PubMed

Lu, Yu; Li, Zhongliang; Nan, Nan; Bu, Yang; Liu, Xuebo; Xu, Xiangdong; Wang, Xuan; Sasaki, Osami; Wang, Xiangzhao

2018-03-26

Optical coherent tomography (OCT) has enabled clinical applications ranging from ophthalmology to cardiology that revolutionized in vivo medical diagnostics in the last few decades, and a variety of endoscopic probes have been developed in order to meet the needs of various endoscopic OCT imaging. We propose a passive driven intravascular optical coherent tomography (IV-OCT) probe in this paper. Instead of using any electrically driven scanning device, the probe makes use of the kinetic energy of the fluid that flushes away the blood during the intravascular optical coherence tomography imaging. The probe converts it into the rotational kinetic energy of the propeller, and the rotation of the rectangular prism mounted on the propeller shaft enables the scanning of the beam. The probe is low cost, and enables unobstructed stable circumferential scanning over 360 deg. The experimental results show that the probe scanning speed can exceed 100 rotations per second (rps). Spectral-domain OCT imaging of a phantom and porcine cardiac artery are demonstrated with axial resolution of 13.6 μm, lateral resolution of 22 μm, and sensitivity of 101.7 dB. We present technically the passively driven IV-OCT probe in full detail and discuss how to optimize the probe in further.

The impact of subliminal effect images in voluntary vs. stimulus-driven actions.

PubMed

Le Bars, Solène; Hsu, Yi-Fang; Waszak, Florian

2016-11-01

According to the ideomotor theory, actions are represented in terms of their sensory effects. In the current study we tested whether subliminal effect images influence action control (1) at early and/or late preparatory stages of (2) voluntary actions or stimulus-driven actions (3) with or without Stimulus-Response (S-R) compatibility. In Experiment 1, participants were presented at random with 50% of S-R compatible stimulus-driven action trials and 50% of voluntary action trials. The actions' effects (i.e. up- or down-pointing arrows) were presented subliminally before each action (i.e. a keypress). In voluntary actions, participants selected more often the action congruent with the prime when it was presented at long intervals before the action. Moreover they responded faster in prime-congruent than in prime-incongruent trials when primes were presented at short intervals before the action. In Experiment 2, participants were only presented with stimulus-driven action trials, with or without S-R compatibility. In stimulus-driven action trials with S-R compatibility (e.g., left-pointing arrow signaling a left keypress), subliminal action-effects did not generate any significant effect on RTs or error rates. On the other hand, in stimulus-driven action trials without S-R compatibility (e.g., letter "H" signaling a left keypress), participants were significantly faster in prime-congruent trials when primes were presented at the shortest time interval before the action. These results suggest that subliminal effect images facilitate voluntary action preparation on an early and a late level. Stimulus-driven action preparation is influenced on a late level only, and only if there is no compatibility between the stimulus and the motor response, that is when the response is not automatically triggered by the common properties existing between the stimulus and the required action. Copyright © 2016 Elsevier B.V. All rights reserved.

Perceptions of early body image socialization in families: Exploring knowledge, beliefs, and strategies among mothers of preschoolers.

PubMed

Liechty, Janet M; Clarke, Samantha; Birky, Julie P; Harrison, Kristen

2016-12-01

This study sought to explore parental perceptions of body image in preschoolers. We conducted semi-structured interviews with 30 primary caregivers of preschoolers to examine knowledge, beliefs, and strategies regarding early body image socialization in families. Thematic Analysis yielded three themes highlighting knowledge gaps, belief discrepancies, and limited awareness of strategies. Findings regarding knowledge: Most participants defined body image as objective attractiveness rather than subjective self-assessment (53%) and focused on negative body image. Beliefs: Although 97% of participants believed weight and shape impact children's self-esteem, 63% believed preschoolers too young to have a body image. Strategies: Most participants (53%) said family was a primary influence on body image, but identified few effective strategies and 63% said they did not do anything to influence children's body image. Findings suggested family body image socialization in preschoolers is occurring outside the awareness of parents and the concept of positive body image is underdeveloped. Copyright © 2016 Elsevier Ltd. All rights reserved.

Knowledge Representation Of CT Scans Of The Head

NASA Astrophysics Data System (ADS)

Ackerman, Laurens V.; Burke, M. W.; Rada, Roy

1984-06-01

We have been investigating diagnostic knowledge models which assist in the automatic classification of medical images by combining information extracted from each image with knowledge specific to that class of images. In a more general sense we are trying to integrate verbal and pictorial descriptions of disease via representations of knowledge, study automatic hypothesis generation as related to clinical medicine, evolve new mathematical image measures while integrating them into the total diagnostic process, and investigate ways to augment the knowledge of the physician. Specifically, we have constructed an artificial intelligence knowledge model using the technique of a production system blending pictorial and verbal knowledge about the respective CT scan and patient history. It is an attempt to tie together different sources of knowledge representation, picture feature extraction and hypothesis generation. Our knowledge reasoning and representation system (KRRS) works with data at the conscious reasoning level of the practicing physician while at the visual perceptional level we are building another production system, the picture parameter extractor (PPE). This paper describes KRRS and its relationship to PPE.

The organized melee: Emergence of collective behavior in concentrated suspensions of swimming bacteria and associated phenomena

NASA Astrophysics Data System (ADS)

Cisneros Salerno, Luis

Suspensions of the aerobic bacteria Bacilus subtilis develop patterns and flows from the interplay of motility, chemotaxis and buoyancy. In sessile drops, such bioconvectively driven flows carry plumes down the slanted meniscus and concentrate cells at the drop edge, while in pendant drops such self-concentration occurs at the bottom. These dynamics are explained quantitatively by a mathematical model consisting of oxygen diffusion and consumption, chemotaxis, and viscous fluid dynamics. Concentrated regions in both geometries comprise nearly close-packed populations, forming the collective "Zooming BioNematic" (ZBN) phase. This state exhibits large-scale orientational coherence, analogous to the molecular alignment of nematic liquid crystals, coupled with remarkable spatial and temporal correlations of velocity and vorticity, as measured by both novel and standard applications of particle imaging velocimetry. To probe mechanisms leading to this phase, response of individual cells to steric stress was explored, finding that they can reverse swimming direction at spatial constrictions without turning the cell body. The consequences of this propensity to flip the flagella are quantified, showing that "forwards" and "backwards" motion are dynamically and morphologically indistinguishable. Finally, experiments and mathematical modeling show that complex flows driven by previously unknown bipolar flagellar arrangements are induced when B. subtilis are confined in a thin layer of fluid, between asymmetric boundaries. The resulting driven flow circulates around the cell body ranging over several cell diameters, in contrast to the more localized flows surrounding free swimmers. This discovery extends our knowledge of the dynamic geometry of bacteria and their flagella, and reveals new mechanisms for motility-associated molecular transport and intercellular communication.

Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge-Based Image Analysis.

DTIC Science & Technology

1988-01-19

approach for the analysis of aerial images. In this approach image analysis is performed ast three levels of abstraction, namely iconic or low-level... image analysis , symbolic or medium-level image analysis , and semantic or high-level image analysis . Domain dependent knowledge about prototypical urban

An Approach to Knowledge-Directed Image Analysis,

DTIC Science & Technology

1977-09-01

34AN APPROACH TO KNOWLEDGE -DIRECTED IMAGE ANALYSIS D.H. Ballard, C.M.’Brown, J.A. Feldman Computer Science Department iThe University of Rochester...Rochester, New York 14627 DTII EECTE UTIC FILE COPY o n I, n 83 - ’ f t 8 11 28 19 1f.. AN APPROACH TO KNOWLEDGE -DIRECTED IMAGE ANALYSIS 5*., D.H...semantic network model and a distributed control structure to accomplish the image analysis process. The process of " understanding an image" leads to

Hard x-ray (>100 keV) imager to measure hot electron preheat for indirectly driven capsule implosions on the NIF.

PubMed

Döppner, T; Dewald, E L; Divol, L; Thomas, C A; Burns, S; Celliers, P M; Izumi, N; Kline, J L; LaCaille, G; McNaney, J M; Prasad, R R; Robey, H F; Glenzer, S H; Landen, O L

2012-10-01

We have fielded a hard x-ray (>100 keV) imager with high aspect ratio pinholes to measure the spatially resolved bremsstrahlung emission from energetic electrons slowing in a plastic ablator shell during indirectly driven implosions at the National Ignition Facility. These electrons are generated in laser plasma interactions and are a source of preheat to the deuterium-tritium fuel. First measurements show that hot electron preheat does not limit obtaining the fuel areal densities required for ignition and burn.

Mystery #21

Atmospheric Science Data Center

2013-04-22

article title:  MISR Mystery Image Quiz #21   ... This mystery concerns a particular type of cloud, one example of which was imaged by the Multi-angle Imaging SpectroRadiometer (MISR) ... ) These clouds are commonly tracked using propeller-driven research aircraft. 3.   Two of these statements are false. Which one is ...

Multiplexed image storage by electromagnetically induced transparency in a solid

NASA Astrophysics Data System (ADS)

Heinze, G.; Rentzsch, N.; Halfmann, T.

2012-11-01

We report on frequency- and angle-multiplexed image storage by electromagnetically induced transparency (EIT) in a Pr3+:Y2SiO5 crystal. Frequency multiplexing by EIT relies on simultaneous storage of light pulses in atomic coherences, driven in different frequency ensembles of the inhomogeneously broadened solid medium. Angular multiplexing by EIT relies on phase matching of the driving laser beams, which permits simultaneous storage of light pulses propagating under different angles into the crystal. We apply the multiplexing techniques to increase the storage capacity of the EIT-driven optical memory, in particular to implement multiplexed storage of larger two-dimensional amounts of data (images). We demonstrate selective storage and readout of images by frequency-multiplexed EIT and angular-multiplexed EIT, as well as the potential to combine both multiplexing approaches towards further enhanced storage capacities.

Putting Priors in Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2004-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Restructuring Teachers' Work-Lives and Knowledge in England and Spain

ERIC Educational Resources Information Center

Muller, Jorg; Norrie, Caroline; Hernandez, Fernando; Goodson, Ivor

2010-01-01

This article explores the restructuring of education in England and Spain. Against a presumably homogeneous global streamlining of educational systems according to competition-driven goals, the comparison of teachers' work-lives and professional knowledge evidences a variety of experiences under-represented in discourses on global restructuring.…

Stealing Knowledge in a Landscape of Learning: Conceptualizations of Jazz Education

ERIC Educational Resources Information Center

Bjerstedt, Sven

2016-01-01

Theoretical approaches to learning in practice-based jazz improvisation contexts include situated learning and ecological perspectives. This article focuses on how interest-driven, self-sustaining jazz learning activities can be matched against the concepts of stolen knowledge (Brown & Duguid, 1996) and landscape of learning (Bjerstedt, 2014).…

Coordinating Scientific Argumentation and the Next Generation Science Standards through Argument Driven Inquiry

ERIC Educational Resources Information Center

Grooms, Jonathon; Enderle, Patrick; Sampson, Victor

2015-01-01

Scientific argumentation is an essential activity for the development and refinement of scientific knowledge. Additionally, fostering argumentation related to scientific concepts can help students engage in a variety of essential scientific practices and enhance their science content knowledge. With the increasing prevalence and emphasis on…

Agency as Inference: Toward a Critical Theory of Knowledge Objectification

ERIC Educational Resources Information Center

Gutiérrez, José Francisco

2013-01-01

This article evaluates the plausibility of synthesizing theory of knowledge objectification (Radford, 2003) with equity research on mathematics education. I suggest the cognitive phenomenon of mathematical inference as a promising locus for investigating the types of agency that equity-driven scholars often care for. In particular, I conceptualize…

The Problem of a Market-Oriented University

ERIC Educational Resources Information Center

Hayrinen-Alestalo, Marja; Peltola, Ulla

2006-01-01

Economy- and technology-driven theories dominate current explanations of social change. The political orientations of the European Union and many of its member states are increasingly based on the idea of knowledge economy where public organisations move towards market-orientation. Among the other producers of knowledge, universities are expected…

A biomechanical modeling-guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2018-02-01

Reconstructing four-dimensional cone-beam computed tomography (4D-CBCT) images directly from respiratory phase-sorted traditional 3D-CBCT projections can capture target motion trajectory, reduce motion artifacts, and reduce imaging dose and time. However, the limited numbers of projections in each phase after phase-sorting decreases CBCT image quality under traditional reconstruction techniques. To address this problem, we developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, an iterative method that can reconstruct higher quality 4D-CBCT images from limited projections using an inter-phase intensity-driven motion model. However, the accuracy of the intensity-driven motion model is limited in regions with fine details whose quality is degraded due to insufficient projection number, which consequently degrades the reconstructed image quality in corresponding regions. In this study, we developed a new 4D-CBCT reconstruction algorithm by introducing biomechanical modeling into SMEIR (SMEIR-Bio) to boost the accuracy of the motion model in regions with small fine structures. The biomechanical modeling uses tetrahedral meshes to model organs of interest and solves internal organ motion using tissue elasticity parameters and mesh boundary conditions. This physics-driven approach enhances the accuracy of solved motion in the organ’s fine structures regions. This study used 11 lung patient cases to evaluate the performance of SMEIR-Bio, making both qualitative and quantitative comparisons between SMEIR-Bio, SMEIR, and the algebraic reconstruction technique with total variation regularization (ART-TV). The reconstruction results suggest that SMEIR-Bio improves the motion model’s accuracy in regions containing small fine details, which consequently enhances the accuracy and quality of the reconstructed 4D-CBCT images.

The Skills Agenda: Issues for Post-16 Providers. FEDA Comments.

ERIC Educational Resources Information Center

Hughes, Maria; Mager, Caroline

Studies in Great Britain have focused on the rapidly changing economy of the 21st century and the skills that workers will need to contribute to it. The studies have found that the new century will be characterized by the knowledge-driven economy, changes driven by global markets, the rapid movement of finance, and developments in information and…

The NTeQ ISD Model: A Tech-Driven Model for Digital Natives (DNs)

ERIC Educational Resources Information Center

Williams, C.; Anekwe, J. U.

2017-01-01

Integrating Technology for enquiry (NTeQ) instructional development model (ISD), is believed to be a technology-driven model. The authors x-rayed the ten-step model to reaffirm the ICT knowledge demand of the learner and the educator; hence computer-based activities at various stages of the model are core elements. The model also is conscious of…

Recent advances in radiation oncology.

PubMed

Garibaldi, Cristina; Jereczek-Fossa, Barbara Alicja; Marvaso, Giulia; Dicuonzo, Samantha; Rojas, Damaris Patricia; Cattani, Federica; Starzyńska, Anna; Ciardo, Delia; Surgo, Alessia; Leonardi, Maria Cristina; Ricotti, Rosalinda

2017-01-01

Radiotherapy (RT) is very much a technology-driven treatment modality in the management of cancer. RT techniques have changed significantly over the past few decades, thanks to improvements in engineering and computing. We aim to highlight the recent developments in radiation oncology, focusing on the technological and biological advances. We will present state-of-the-art treatment techniques, employing photon beams, such as intensity-modulated RT, volumetric-modulated arc therapy, stereotactic body RT and adaptive RT, which make possible a highly tailored dose distribution with maximum normal tissue sparing. We will analyse all the steps involved in the treatment: imaging, delineation of the tumour and organs at risk, treatment planning and finally image-guidance for accurate tumour localisation before and during treatment delivery. Particular attention will be given to the crucial role that imaging plays throughout the entire process. In the case of adaptive RT, the precise identification of target volumes as well as the monitoring of tumour response/modification during the course of treatment is mainly based on multimodality imaging that integrates morphological, functional and metabolic information. Moreover, real-time imaging of the tumour is essential in breathing adaptive techniques to compensate for tumour motion due to respiration. Brief reference will be made to the recent spread of particle beam therapy, in particular to the use of protons, but also to the yet limited experience of using heavy particles such as carbon ions. Finally, we will analyse the latest biological advances in tumour targeting. Indeed, the effectiveness of RT has been improved not only by technological developments but also through the integration of radiobiological knowledge to produce more efficient and personalised treatment strategies.

Microemulsion-Based Soft Bacteria-Driven Microswimmers for Active Cargo Delivery.

PubMed

Singh, Ajay Vikram; Hosseinidoust, Zeinab; Park, Byung-Wook; Yasa, Oncay; Sitti, Metin

2017-10-24

Biohybrid cell-driven microsystems offer unparalleled possibilities for realization of soft microrobots at the micron scale. Here, we introduce a bacteria-driven microswimmer that combines the active locomotion and sensing capabilities of bacteria with the desirable encapsulation and viscoelastic properties of a soft double-micelle microemulsion for active transport and delivery of cargo (e.g., imaging agents, genes, and drugs) to living cells. Quasi-monodisperse double emulsions were synthesized with an aqueous core that encapsulated the fluorescence imaging agents, as a proof-of-concept cargo in this study, and an outer oil shell that was functionalized with streptavidin for specific and stable attachment of biotin-conjugated Escherichia coli. Motile bacteria effectively propelled the soft microswimmers across a Transwell membrane, actively delivering imaging agents (i.e., dyes) encapsulated inside of the micelles to a monolayer of cultured MCF7 breast cancer and J744A.1 macrophage cells, which enabled real-time, live-cell imaging of cell organelles, namely mitochondria, endoplasmic reticulum, and Golgi body. This in vitro model demonstrates the proof-of-concept feasibility of the proposed soft microswimmers and offers promise for potential biomedical applications in active and/or targeted transport and delivery of imaging agents, drugs, stem cells, siRNA, and therapeutic genes to live tissue in in vitro disease models (e.g., organ-on-a-chip devices) and stagnant or low-flow-velocity fluidic regions of the human body.

Government, industry, and university partnerships: A model for the knowledge age

NASA Astrophysics Data System (ADS)

Varner, Michael O.

1996-03-01

New technologies are transforming the industrial economy into a marketplace driven by information and knowledge. The depth, breadth, and rate of technology development, however, overwhelms our ability to absorb, process, and recall new information. Moreover, the bright future enabled by the knowledge age cannot be realized without the development of new organizational models and philosophies. This paper discusses the necessity for business, government, and universities to create inter-institutional partnerships in order to accommodate change and flourish in the knowledge age.

The Pearling Transition Provides Evidence of Force-Driven Endosomal Tubulation during Salmonella Infection.

PubMed

Gao, Yunfeng; Spahn, Christoph; Heilemann, Mike; Kenney, Linda J

2018-06-19

Bacterial pathogens exploit eukaryotic pathways for their own end. Upon ingestion, Salmonella enterica serovar Typhimurium passes through the stomach and then catalyzes its uptake across the intestinal epithelium. It survives and replicates in an acidic vacuole through the action of virulence factors secreted by a type three secretion system located on Salmonella pathogenicity island 2 (SPI-2). Two secreted effectors, SifA and SseJ, are sufficient for endosomal tubule formation, which modifies the vacuole and enables Salmonella to replicate within it. Two-color, superresolution imaging of the secreted virulence factor SseJ and tubulin revealed that SseJ formed clusters of conserved size at regular, periodic intervals in the host cytoplasm. Analysis of SseJ clustering indicated the presence of a pearling effect, which is a force-driven, osmotically sensitive process. The pearling transition is an instability driven by membranes under tension; it is induced by hypotonic or hypertonic buffer exchange and leads to the formation of beadlike structures of similar size and regular spacing. Reducing the osmolality of the fixation conditions using glutaraldehyde enabled visualization of continuous and intact tubules. Correlation analysis revealed that SseJ was colocalized with the motor protein kinesin. Tubulation of the endoplasmic reticulum is driven by microtubule motors, and in the present work, we describe how Salmonella has coopted the microtubule motor kinesin to drive the force-dependent process of endosomal tubulation. Thus, endosomal tubule formation is a force-driven process catalyzed by Salmonella virulence factors secreted into the host cytoplasm during infection. IMPORTANCE This study represents the first example of using two-color, superresolution imaging to analyze the secretion of Salmonella virulence factors as they are secreted from the SPI-2 type three secretion system. Previous studies imaged effectors that were overexpressed in the host cytoplasm. The present work reveals an unusual force-driven process, the pearling transition, which indicates that Salmonella -induced filaments are under force through the interactions of effector molecules with the motor protein kinesin. This work provides a caution by highlighting how fixation conditions can influence the images observed.

Development of direct multi-hazard susceptibility assessment method for post-earthquake reconstruction planning in Nepal

NASA Astrophysics Data System (ADS)

Mavrouli, Olga; Rana, Sohel; van Westen, Cees; Zhang, Jianqiang

2017-04-01

After the devastating 2015 Gorkha earthquake in Nepal, reconstruction activities have been delayed considerably, due to many reasons, of a political, organizational and technical nature. Due to the widespread occurrence of co-seismic landslides, and the expectation that these may be aggravated or re-activated in future years during the intense monsoon periods, there is a need to evaluate for thousands of sites whether these are suited for reconstruction. In this evaluation multi-hazards, such as rockfall, landslides, debris flow, and flashfloods should be taken into account. The application of indirect knowledge-based, data-driven or physically-based approaches is not suitable due to several reasons. Physically-based models generally require a large number of parameters, for which data is not available. Data-driven, statistical methods, depend on historical information, which is less useful after the occurrence of a major event, such as an earthquake. Besides, they would lead to unacceptable levels of generalization, as the analysis is done based on rather general causal factor maps. The same holds for indirect knowledge-driven methods. However, location-specific hazards analysis is required using a simple method that can be used by many people at the local level. In this research, a direct scientific method was developed where local level technical people can easily and quickly assess the post-earthquake multi hazards following a decision tree approach, using an app on a smartphone or tablet. The methods assumes that a central organization, such as the Department of Soil Conservation and Watershed Management, generates spatial information beforehand that is used in the direct assessment at a certain location. Pre-earthquake, co-seismic and post-seismic landslide inventories are generated through the interpretation of Google Earth multi-temporal images, using anaglyph methods. Spatial data, such as Digital Elevation Models, land cover maps, and geological maps are used in a GIS to generate Terrain Units in a semi-automated manner, which are further edited using stereo-image interpretation. Source areas for rockfall and debris flows are outlined from the factor maps, and historical inventory, and regional scale empirical runout models are used to define areas that might be affected. This data is then used in the field in an application that guides the user through the decision tree by asking a number of questions, which can be answered by using the existing data, and by direct field observations. The method was applied in a part of Rasuwa district, which was seriously affected by co-seismic and post-seismic mass movements, leading to the evacuation of a number of village, and temporary closure of a number of hydropower construction projects.

Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image

NASA Astrophysics Data System (ADS)

He, Xingwu; You, Junchen

2018-03-01

Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.

Predictors of Knowledge and Image Interpretation Skill Development in Radiology Residents.

PubMed

Ravesloot, Cécile J; van der Schaaf, Marieke F; Kruitwagen, Cas L J J; van der Gijp, Anouk; Rutgers, Dirk R; Haaring, Cees; Ten Cate, Olle; van Schaik, Jan P J

2017-09-01

Purpose To investigate knowledge and image interpretation skill development in residency by studying scores on knowledge and image questions on radiology tests, mediated by the training environment. Materials and Methods Ethical approval for the study was obtained from the ethical review board of the Netherlands Association for Medical Education. Longitudinal test data of 577 of 2884 radiology residents who took semiannual progress tests during 5 years were retrospectively analyzed by using a nonlinear mixed-effects model taking training length as input variable. Tests included nonimage and image questions that assessed knowledge and image interpretation skill. Hypothesized predictors were hospital type (academic or nonacademic), training hospital, enrollment age, sex, and test date. Results Scores showed a curvilinear growth during residency. Image scores increased faster during the first 3 years of residency and reached a higher maximum than knowledge scores (55.8% vs 45.1%). The slope of image score development versus knowledge question scores of 1st-year residents was 16.8% versus 12.4%, respectively. Training hospital environment appeared to be an important predictor in both knowledge and image interpretation skill development (maximum score difference between training hospitals was 23.2%; P < .001). Conclusion Expertise developed rapidly in the initial years of radiology residency and leveled off in the 3rd and 4th training year. The shape of the curve was mainly influenced by the specific training hospital. © RSNA, 2017 Online supplemental material is available for this article.

Impact of Data-driven Respiratory Gating in Clinical PET.

PubMed

Büther, Florian; Vehren, Thomas; Schäfers, Klaus P; Schäfers, Michael

2016-10-01

Purpose To study the feasibility and impact of respiratory gating in positron emission tomographic (PET) imaging in a clinical trial comparing conventional hardware-based gating with a data-driven approach and to describe the distribution of determined parameters. Materials and Methods This prospective study was approved by the ethics committee of the University Hospital of Münster (AZ 2014-217-f-N). Seventy-four patients suspected of having abdominal or thoracic fluorine 18 fluorodeoxyglucose (FDG)-positive lesions underwent clinical whole-body FDG PET/computed tomographic (CT) examinations. Respiratory gating was performed by using a pressure-sensitive belt system (belt gating [BG]) and an automatic data-driven approach (data-driven gating [DDG]). PET images were analyzed for lesion uptake, metabolic volumes, respiratory shifts of lesions, and diagnostic image quality. Results Forty-eight patients had at least one lesion in the field of view, resulting in a total of 164 lesions analyzed (range of number of lesions per patient, one to 13). Both gating methods revealed respiratory shifts of lesions (4.4 mm ± 3.1 for BG vs 4.8 mm ± 3.6 for DDG, P = .76). Increase in uptake of the lesions compared with nongated values did not differ significantly between both methods (maximum standardized uptake value [SUVmax], +7% ± 13 for BG vs +8% ± 16 for DDG, P = .76). Similarly, gating significantly decreased metabolic lesion volumes with both methods (-6% ± 26 for BG vs -7% ± 21 for DDG, P = .44) compared with nongated reconstructions. Blinded reading revealed significant improvements in diagnostic image quality when using gating, without significant differences between the methods (DDG was judged to be inferior to BG in 22 cases, equal in 12 cases, and superior in 15 cases; P = .32). Conclusion Respiratory gating increases diagnostic image quality and uptake values and decreases metabolic volumes compared with nongated acquisitions. Data-driven approaches are clinically applicable alternatives to belt-based methods and might help establishing routine respiratory gating in clinical PET/CT. (©) RSNA, 2016 Online supplemental material is available for this article.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Framing of scientific knowledge as a new category of health care research.

PubMed

Salvador-Carulla, Luis; Fernandez, Ana; Madden, Rosamond; Lukersmith, Sue; Colagiuri, Ruth; Torkfar, Ghazal; Sturmberg, Joachim

2014-12-01

The new area of health system research requires a revision of the taxonomy of scientific knowledge that may facilitate a better understanding and representation of complex health phenomena in research discovery, corroboration and implementation. A position paper by an expert group following and iterative approach. 'Scientific evidence' should be differentiated from 'elicited knowledge' of experts and users, and this latter typology should be described beyond the traditional qualitative framework. Within this context 'framing of scientific knowledge' (FSK) is defined as a group of studies of prior expert knowledge specifically aimed at generating formal scientific frames. To be distinguished from other unstructured frames, FSK must be explicit, standardized, based on the available evidence, agreed by a group of experts and subdued to the principles of commensurability, transparency for corroboration and transferability that characterize scientific research. A preliminary typology of scientific framing studies is presented. This typology includes, among others, health declarations, position papers, expert-based clinical guides, conceptual maps, classifications, expert-driven health atlases and expert-driven studies of costs and burden of illness. This grouping of expert-based studies constitutes a different kind of scientific knowledge and should be clearly differentiated from 'evidence' gathered from experimental and observational studies in health system research. © 2014 John Wiley & Sons, Ltd.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

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

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Promoting elementary students' epistemology of science through computer-supported knowledge-building discourse and epistemic reflection

NASA Astrophysics Data System (ADS)

Lin, Feng; Chan, Carol K. K.

2018-04-01

This study examined the role of computer-supported knowledge-building discourse and epistemic reflection in promoting elementary-school students' scientific epistemology and science learning. The participants were 39 Grade 5 students who were collectively pursuing ideas and inquiry for knowledge advance using Knowledge Forum (KF) while studying a unit on electricity; they also reflected on the epistemic nature of their discourse. A comparison class of 22 students, taught by the same teacher, studied the same unit using the school's established scientific investigation method. We hypothesised that engaging students in idea-driven and theory-building discourse, as well as scaffolding them to reflect on the epistemic nature of their discourse, would help them understand their own scientific collaborative discourse as a theory-building process, and therefore understand scientific inquiry as an idea-driven and theory-building process. As hypothesised, we found that students engaged in knowledge-building discourse and reflection outperformed comparison students in scientific epistemology and science learning, and that students' understanding of collaborative discourse predicted their post-test scientific epistemology and science learning. To further understand the epistemic change process among knowledge-building students, we analysed their KF discourse to understand whether and how their epistemic practice had changed after epistemic reflection. The implications on ways of promoting epistemic change are discussed.

Knowledge-Based Image Analysis.

DTIC Science & Technology

1981-04-01

UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

QA-driven Guidelines Generation for Bacteriotherapy

PubMed Central

Pasche, Emilie; Teodoro, Douglas; Gobeill, Julien; Ruch, Patrick; Lovis, Christian

2009-01-01

PURPOSE We propose a question-answering (QA) driven generation approach for automatic acquisition of structured rules that can be used in a knowledge authoring tool for antibiotic prescription guidelines management. METHODS: The rule generation is seen as a question-answering problem, where the parameters of the questions are known items of the rule (e.g. an infectious disease, caused by a given bacterium) and answers (e.g. some antibiotics) are obtained by a question-answering engine. RESULTS: When looking for a drug given a pathogen and a disease, top-precision of 0.55 is obtained by the combination of the Boolean engine (PubMed) and the relevance-driven engine (easyIR), which means that for more than half of our evaluation benchmark at least one of the recommended antibiotics was automatically acquired by the rule generation method. CONCLUSION: These results suggest that such an automatic text mining approach could provide a useful tool for guidelines management, by improving knowledge update and discovery. PMID:20351908

Image Understanding Architecture

DTIC Science & Technology

1991-09-01

architecture to support real-time, knowledge -based image understanding , and develop the software support environment that will be needed to utilize...NUMBER OF PAGES Image Understanding Architecture, Knowledge -Based Vision, AI Real-Time Computer Vision, Software Simulator, Parallel Processor IL PRICE... information . In addition to sensory and knowledge -based processing it is useful to introduce a level of symbolic processing. Thus, vision researchers

‘The kind of mildly curious sort of science interested person like me’: Science bloggers’ practices relating to audience recruitment

PubMed Central

Ranger, Mathieu; Bultitude, Karen

2014-01-01

With at least 150 million professional and amateur blogs on the Internet, blogging offers a potentially powerful tool for engaging large and diverse audiences with science. This article investigates science blogging practices to uncover key trends, including bloggers’ self-perceptions of their role. Interviews with seven of the most popular science bloggers revealed them to be driven by intrinsic personal motivations. Wishing to pursue their love of writing and share their passion for science, they produce content suitable for niche audiences of science enthusiasts, although they do not assume background scientific knowledge. A content analysis of 1000 blog posts and comparison with the most popular blogs on the Internet further confirmed this result and additionally identified key factors that affect science blog popularity, including update frequency, topic diversity and the inclusion of non-text elements (especially images and video). PMID:25361791

'The kind of mildly curious sort of science interested person like me': Science bloggers' practices relating to audience recruitment.

PubMed

Ranger, Mathieu; Bultitude, Karen

2016-04-01

With at least 150 million professional and amateur blogs on the Internet, blogging offers a potentially powerful tool for engaging large and diverse audiences with science. This article investigates science blogging practices to uncover key trends, including bloggers' self-perceptions of their role. Interviews with seven of the most popular science bloggers revealed them to be driven by intrinsic personal motivations. Wishing to pursue their love of writing and share their passion for science, they produce content suitable for niche audiences of science enthusiasts, although they do not assume background scientific knowledge. A content analysis of 1000 blog posts and comparison with the most popular blogs on the Internet further confirmed this result and additionally identified key factors that affect science blog popularity, including update frequency, topic diversity and the inclusion of non-text elements (especially images and video). © The Author(s) 2014.

Dual wavelength imaging of a scrape-off layer in an advanced beam-driven field-reversed configuration

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

Osin, D.; Schindler, T., E-mail: dosin@trialphaenergy.com

2016-11-15

A dual wavelength imaging system has been developed and installed on C-2U to capture 2D images of a He jet in the Scrape-Off Layer (SOL) of an advanced beam-driven Field-Reversed Configuration (FRC) plasma. The system was designed to optically split two identical images and pass them through 1 nm FWHM filters. Dual wavelength images are focused adjacent on a large format CCD chip and recorded simultaneously with a time resolution down to 10 μs using a gated micro-channel plate. The relatively compact optical system images a 10 cm plasma region with a spatial resolution of 0.2 cm and can bemore » used in a harsh environment with high electro-magnetic noise and high magnetic field. The dual wavelength imaging system provides 2D images of either electron density or temperature by observing spectral line pairs emitted by He jet atoms in the SOL. A large field of view, combined with good space and time resolution of the imaging system, allows visualization of macro-flows in the SOL. First 2D images of the electron density and temperature observed in the SOL of the C-2U FRC are presented.« less

Dynamic x-ray imaging of laser-driven nanoplasmas

NASA Astrophysics Data System (ADS)

Fennel, Thomas

2016-05-01

A major promise of current x-ray science at free electron lasers is the realization of unprecedented imaging capabilities for resolving the structure and ultrafast dynamics of matter with nanometer spatial and femtosecond temporal resolution or even below via single-shot x-ray diffraction. Laser-driven atomic clusters and nanoparticles provide an ideal platform for developing and demonstrating the required technology to extract the ultrafast transient spatiotemporal dynamics from the diffraction images. In this talk, the perspectives and challenges of dynamic x-ray imaging will be discussed using complete self-consistent microscopic electromagnetic simulations of IR pump x-ray probe imaging for the example of clusters. The results of the microscopic particle-in-cell simulations (MicPIC) enable the simulation-assisted reconstruction of corresponding experimental data. This capability is demonstrated by converting recently measured LCLS data into a ultrahigh resolution movie of laser-induced plasma expansion. Finally, routes towards reaching attosecond time resolution in the visualization of complex dynamical processes in matter by x-ray diffraction will be discussed.

Detector for imaging and dosimetry of laser-driven epithermal neutrons by alpha conversion

NASA Astrophysics Data System (ADS)

Mirfayzi, S. R.; Alejo, A.; Ahmed, H.; Wilson, L. A.; Ansell, S.; Armstrong, C.; Butler, N. M. H.; Clarke, R. J.; Higginson, A.; Notley, M.; Raspino, D.; Rusby, D. R.; Borghesi, M.; Rhodes, N. J.; McKenna, P.; Neely, D.; Brenner, C. M.; Kar, S.

2016-10-01

An epithermal neutron imager based on detecting alpha particles created via boron neutron capture mechanism is discussed. The diagnostic mainly consists of a mm thick Boron Nitride (BN) sheet (as an alpha converter) in contact with a non-borated cellulose nitride film (LR115 type-II) detector. While the BN absorbs the neutrons in the thermal and epithermal ranges, the fast neutrons register insignificantly on the detector due to their low neutron capture and recoil cross-sections. The use of solid-state nuclear track detectors (SSNTD), unlike image plates, micro-channel plates and scintillators, provide safeguard from the x-rays, gamma-rays and electrons. The diagnostic was tested on a proof-of-principle basis, in front of a laser driven source of moderated neutrons, which suggests the potential of using this diagnostic (BN+SSNTD) for dosimetry and imaging applications.

High-speed multi-frame dynamic transmission electron microscope image acquisition system with arbitrary timing

DOEpatents

Reed, Bryan W.; DeHope, William J.; Huete, Glenn; LaGrange, Thomas B.; Shuttlesworth, Richard M.

2016-02-23

An electron microscope is disclosed which has a laser-driven photocathode and an arbitrary waveform generator (AWG) laser system ("laser"). The laser produces a train of temporally-shaped laser pulses each being of a programmable pulse duration, and directs the laser pulses to the laser-driven photocathode to produce a train of electron pulses. An image sensor is used along with a deflector subsystem. The deflector subsystem is arranged downstream of the target but upstream of the image sensor, and has a plurality of plates. A control system having a digital sequencer controls the laser and a plurality of switching components, synchronized with the laser, to independently control excitation of each one of the deflector plates. This allows each electron pulse to be directed to a different portion of the image sensor, as well as to enable programmable pulse durations and programmable inter-pulse spacings.

High-speed multiframe dynamic transmission electron microscope image acquisition system with arbitrary timing

DOEpatents

Reed, Bryan W.; DeHope, William J.; Huete, Glenn; LaGrange, Thomas B.; Shuttlesworth, Richard M.

2015-10-20

An electron microscope is disclosed which has a laser-driven photocathode and an arbitrary waveform generator (AWG) laser system ("laser"). The laser produces a train of temporally-shaped laser pulses of a predefined pulse duration and waveform, and directs the laser pulses to the laser-driven photocathode to produce a train of electron pulses. An image sensor is used along with a deflector subsystem. The deflector subsystem is arranged downstream of the target but upstream of the image sensor, and has two pairs of plates arranged perpendicular to one another. A control system controls the laser and a plurality of switching components synchronized with the laser, to independently control excitation of each one of the deflector plates. This allows each electron pulse to be directed to a different portion of the image sensor, as well as to be provided with an independently set duration and independently set inter-pulse spacings.

High-speed multiframe dynamic transmission electron microscope image acquisition system with arbitrary timing

DOEpatents

Reed, Bryan W.; Dehope, William J; Huete, Glenn; LaGrange, Thomas B.; Shuttlesworth, Richard M

2016-06-21

An electron microscope is disclosed which has a laser-driven photocathode and an arbitrary waveform generator (AWG) laser system ("laser"). The laser produces a train of temporally-shaped laser pulses of a predefined pulse duration and waveform, and directs the laser pulses to the laser-driven photocathode to produce a train of electron pulses. An image sensor is used along with a deflector subsystem. The deflector subsystem is arranged downstream of the target but upstream of the image sensor, and has two pairs of plates arranged perpendicular to one another. A control system controls the laser and a plurality of switching components synchronized with the laser, to independently control excitation of each one of the deflector plates. This allows each electron pulse to be directed to a different portion of the image sensor, as well as to be provided with an independently set duration and independently set inter-pulse spacings.

Using Content Acquisition Podcasts to Increase Student Knowledge and to Reduce Perceived Cognitive Load

ERIC Educational Resources Information Center

Kennedy, Michael J.; Hirsch, Shanna Eisner; Dillon, Sarah E.; Rabideaux, Lindsey; Alves, Kathryn D.; Driver, Melissa K.

2016-01-01

The use of multimedia-driven instruction in college courses is an emerging practice designed to increase students' knowledge. However, limited research has validated the effectiveness of using multimedia to teach students about functional behavioral assessments (FBAs). To test the effectiveness of a multimedia tool called Content Acquisition…

Where Computer Science and Cultural Studies Collide

ERIC Educational Resources Information Center

Kirschenbaum, Matthew

2009-01-01

Most users have no more knowledge of what their computer or code is actually doing than most automobile owners have of their carburetor or catalytic converter. Nor is any such knowledge necessarily needed. But for academics, driven by an increasing emphasis on the materiality of new media--that is, the social, cultural, and economic factors…

Research Knowledge Transfer through Business-Driven Student Assignment

ERIC Educational Resources Information Center

Sas, Corina

2009-01-01

Purpose: The purpose of this paper is to present a knowledge transfer method that capitalizes on both research and teaching dimensions of academic work. It also aims to propose a framework for evaluating the impact of such a method on the involved stakeholders. Design/methodology/approach: The case study outlines and evaluates the six-stage…

Universities and Innovation in a Factor-Driven Economy: The Performance of Universities in Egypt

ERIC Educational Resources Information Center

El Hadidi, Hala; Kirby, David A.

2016-01-01

In the contemporary knowledge-based global economy, universities are required to operate more entrepreneurially, commercializing the results of their research and spinning out new knowledge-based enterprises. In this article, the third in a series by the authors, case studies are presented of activities in three Egyptian universities to…

Evaluating laser-driven Bremsstrahlung radiation sources for imaging and analysis of nuclear waste packages.

PubMed

Jones, Christopher P; Brenner, Ceri M; Stitt, Camilla A; Armstrong, Chris; Rusby, Dean R; Mirfayzi, Seyed R; Wilson, Lucy A; Alejo, Aarón; Ahmed, Hamad; Allott, Ric; Butler, Nicholas M H; Clarke, Robert J; Haddock, David; Hernandez-Gomez, Cristina; Higginson, Adam; Murphy, Christopher; Notley, Margaret; Paraskevoulakos, Charilaos; Jowsey, John; McKenna, Paul; Neely, David; Kar, Satya; Scott, Thomas B

2016-11-15

A small scale sample nuclear waste package, consisting of a 28mm diameter uranium penny encased in grout, was imaged by absorption contrast radiography using a single pulse exposure from an X-ray source driven by a high-power laser. The Vulcan laser was used to deliver a focused pulse of photons to a tantalum foil, in order to generate a bright burst of highly penetrating X-rays (with energy >500keV), with a source size of <0.5mm. BAS-TR and BAS-SR image plates were used for image capture, alongside a newly developed Thalium doped Caesium Iodide scintillator-based detector coupled to CCD chips. The uranium penny was clearly resolved to sub-mm accuracy over a 30cm(2) scan area from a single shot acquisition. In addition, neutron generation was demonstrated in situ with the X-ray beam, with a single shot, thus demonstrating the potential for multi-modal criticality testing of waste materials. This feasibility study successfully demonstrated non-destructive radiography of encapsulated, high density, nuclear material. With recent developments of high-power laser systems, to 10Hz operation, a laser-driven multi-modal beamline for waste monitoring applications is envisioned. Copyright © 2016. Published by Elsevier B.V.

Complexity in Design-Driven Innovation: A Case Study of Knowledge Transfer Flow in Subsea Seismic Sensor Technology and Design Education

ERIC Educational Resources Information Center

Pavel, Nenad; Berg, Arild

2015-01-01

To the extent previously claimed, concept exploration is not the key to product innovation. However, companies that are design-focused are twice as innovative as those that are not. To study design-driven innovation and its occurrence in design education, two case studies are conducted. The first is an example of design practice which includes…

Mission Driven Science at Argonne

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

Thackery, Michael; Wang, Michael; Young, Linda

2012-07-05

Mission driven science at Argonne means applying science and scientific knowledge to a physical and "real world" environment. Examples include testing a theoretical model through the use of formal science or solving a practical problem through the use of natural science. At the laboratory, our materials scientists are leading the way in producing energy solutions today that could help reduce and remove the energy crisis of tomorrow.

Potential role of hypoxia imaging using (18)F-FAZA PET to guide hypoxia-driven interventions (carbogen breathing or dose escalation) in radiation therapy.

PubMed

Tran, Ly-Binh-An; Bol, Anne; Labar, Daniel; Karroum, Oussama; Bol, Vanesa; Jordan, Bénédicte; Grégoire, Vincent; Gallez, Bernard

2014-11-01

Hypoxia-driven intervention (oxygen manipulation or dose escalation) could overcome radiation resistance linked to tumor hypoxia. Here, we evaluated the value of hypoxia imaging using (18)F-FAZA PET to predict the outcome and guide hypoxia-driven interventions. Two hypoxic rat tumor models were used: rhabdomyosarcoma and 9L-glioma. For the irradiated groups, the animals were divided into two subgroups: breathing either room air or carbogen. (18)F-FAZA PET images were obtained just before the irradiation to monitor the hypoxic level of each tumor. Absolute pO2 were also measured using EPR oximetry. Dose escalation was used in Rhabdomyosarcomas. For 9L-gliomas, a significant correlation between (18)F-FAZA T/B ratio and tumor growth delay was found; additionally, carbogen breathing dramatically improved the tumor response to irradiation. On the contrary, Rhabdomyosarcomas were less responsive to hyperoxic challenge. For that model, an increase in growth delay was observed using dose escalation, but not when combining irradiation with carbogen. (18)F-FAZA uptake may be prognostic of outcome following radiotherapy and could assess the response of tumor to carbogen breathing. (18)F-FAZA PET may help to guide the hypoxia-driven intervention with irradiation: carbogen breathing in responsive tumors or dose escalation in tumors non-responsive to carbogen. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Retrospective data-driven respiratory gating for PET/CT

NASA Astrophysics Data System (ADS)

Schleyer, Paul J.; O'Doherty, Michael J.; Barrington, Sally F.; Marsden, Paul K.

2009-04-01

Respiratory motion can adversely affect both PET and CT acquisitions. Respiratory gating allows an acquisition to be divided into a series of motion-reduced bins according to the respiratory signal, which is typically hardware acquired. In order that the effects of motion can potentially be corrected for, we have developed a novel, automatic, data-driven gating method which retrospectively derives the respiratory signal from the acquired PET and CT data. PET data are acquired in listmode and analysed in sinogram space, and CT data are acquired in cine mode and analysed in image space. Spectral analysis is used to identify regions within the CT and PET data which are subject to respiratory motion, and the variation of counts within these regions is used to estimate the respiratory signal. Amplitude binning is then used to create motion-reduced PET and CT frames. The method was demonstrated with four patient datasets acquired on a 4-slice PET/CT system. To assess the accuracy of the data-derived respiratory signal, a hardware-based signal was acquired for comparison. Data-driven gating was successfully performed on PET and CT datasets for all four patients. Gated images demonstrated respiratory motion throughout the bin sequences for all PET and CT series, and image analysis and direct comparison of the traces derived from the data-driven method with the hardware-acquired traces indicated accurate recovery of the respiratory signal.

An accuracy improvement method for the topology measurement of an atomic force microscope using a 2D wavelet transform.

PubMed

Yoon, Yeomin; Noh, Suwoo; Jeong, Jiseong; Park, Kyihwan

2018-05-01

The topology image is constructed from the 2D matrix (XY directions) of heights Z captured from the force-feedback loop controller. For small height variations, nonlinear effects such as hysteresis or creep of the PZT-driven Z nano scanner can be neglected and its calibration is quite straightforward. For large height variations, the linear approximation of the PZT-driven Z nano scanner fail and nonlinear behaviors must be considered because this would cause inaccuracies in the measurement image. In order to avoid such inaccuracies, an additional strain gauge sensor is used to directly measure displacement of the PZT-driven Z nano scanner. However, this approach also has a disadvantage in its relatively low precision. In order to obtain high precision data with good linearity, we propose a method of overcoming the low precision problem of the strain gauge while its feature of good linearity is maintained. We expect that the topology image obtained from the strain gauge sensor showing significant noise at high frequencies. On the other hand, the topology image obtained from the controller output showing low noise at high frequencies. If the low and high frequency signals are separable from both topology images, the image can be constructed so that it is represented with high accuracy and low noise. In order to separate the low frequencies from high frequencies, a 2D Haar wavelet transform is used. Our proposed method use the 2D wavelet transform for obtaining good linearity from strain gauge sensor and good precision from controller output. The advantages of the proposed method are experimentally validated by using topology images. Copyright © 2018 Elsevier B.V. All rights reserved.

Flight path-driven mitigation of wavefront curvature effects in SAR images

DOEpatents

Doerry, Armin W [Albuquerque, NM

2009-06-23

A wavefront curvature effect associated with a complex image produced by a synthetic aperture radar (SAR) can be mitigated based on which of a plurality of possible flight paths is taken by the SAR when capturing the image. The mitigation can be performed differently for different ones of the flight paths.

User-Driven Planning for Digital-Image Delivery

ERIC Educational Resources Information Center

Pisciotta, Henry; Halm, Michael J.; Dooris, Michael J.

2006-01-01

This article draws on two projects funded by the Andrew W. Mellon Foundation concerning the ways colleges and universities can support the legitimate sharing of digital learning resources for scholarly use. The 2001-03 Visual Image User Study (VIUS) assessed the scholarly needs of digital image users-faculty, staff, and students. That study led to…

Characteristics of spondylotic myelopathy on 3D driven-equilibrium fast spin echo and 2D fast spin echo magnetic resonance imaging: a retrospective cross-sectional study.

PubMed

Abdulhadi, Mike A; Perno, Joseph R; Melhem, Elias R; Nucifora, Paolo G P

2014-01-01

In patients with spinal stenosis, magnetic resonance imaging of the cervical spine can be improved by using 3D driven-equilibrium fast spin echo sequences to provide a high-resolution assessment of osseous and ligamentous structures. However, it is not yet clear whether 3D driven-equilibrium fast spin echo sequences adequately evaluate the spinal cord itself. As a result, they are generally supplemented by additional 2D fast spin echo sequences, adding time to the examination and potential discomfort to the patient. Here we investigate the hypothesis that in patients with spinal stenosis and spondylotic myelopathy, 3D driven-equilibrium fast spin echo sequences can characterize cord lesions equally well as 2D fast spin echo sequences. We performed a retrospective analysis of 30 adult patients with spondylotic myelopathy who had been examined with both 3D driven-equilibrium fast spin echo sequences and 2D fast spin echo sequences at the same scanning session. The two sequences were inspected separately for each patient, and visible cord lesions were manually traced. We found no significant differences between 3D driven-equilibrium fast spin echo and 2D fast spin echo sequences in the mean number, mean area, or mean transverse dimensions of spondylotic cord lesions. Nevertheless, the mean contrast-to-noise ratio of cord lesions was decreased on 3D driven-equilibrium fast spin echo sequences compared to 2D fast spin echo sequences. These findings suggest that 3D driven-equilibrium fast spin echo sequences do not need supplemental 2D fast spin echo sequences for the diagnosis of spondylotic myelopathy, but they may be less well suited for quantitative signal measurements in the spinal cord.

Data-Intensive Science Meets Inquiry-Driven Pedagogy: Interactive Big Data Exploration, Threshold Concepts, and Liminality

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Nair, U. S.; Word, A.

2014-12-01

Threshold concepts in any discipline are the core concepts an individual must understand in order to master a discipline. By their very nature, these concepts are troublesome, irreversible, integrative, bounded, discursive, and reconstitutive. Although grasping threshold concepts can be extremely challenging for each learner as s/he moves through stages of cognitive development relative to a given discipline, the learner's grasp of these concepts determines the extent to which s/he is prepared to work competently and creatively within the field itself. The movement of individuals from a state of ignorance of these core concepts to one of mastery occurs not along a linear path but in iterative cycles of knowledge creation and adjustment in liminal spaces - conceptual spaces through which learners move from the vaguest awareness of concepts to mastery, accompanied by understanding of their relevance, connectivity, and usefulness relative to questions and constructs in a given discipline. With the explosive growth of data available in atmospheric science, driven largely by satellite Earth observations and high-resolution numerical simulations, paradigms such as that of data-intensive science have emerged. These paradigm shifts are based on the growing realization that current infrastructure, tools and processes will not allow us to analyze and fully utilize the complex and voluminous data that is being gathered. In this emerging paradigm, the scientific discovery process is driven by knowledge extracted from large volumes of data. In this presentation, we contend that this paradigm naturally lends to inquiry-driven pedagogy where knowledge is discovered through inductive engagement with large volumes of data rather than reached through traditional, deductive, hypothesis-driven analyses. In particular, data-intensive techniques married with an inductive methodology allow for exploration on a scale that is not possible in the traditional classroom with its typical problem sets and static, limited data samples. In addition, we identify existing gaps and possible solutions for addressing the infrastructure and tools as well as a pedagogical framework through which to implement this inductive approach.

Stakeholder-Driven Quality Improvement: A Compelling Force for Clinical Practice Guidelines.

PubMed

Rosenfeld, Richard M; Wyer, Peter C

2018-01-01

Clinical practice guideline development should be driven by rigorous methodology, but what is less clear is where quality improvement enters the process: should it be a priority-guiding force, or should it enter only after recommendations are formulated? We argue for a stakeholder-driven approach to guideline development, with an overriding goal of quality improvement based on stakeholder perceptions of needs, uncertainties, and knowledge gaps. In contrast, the widely used topic-driven approach, which often makes recommendations based only on randomized controlled trials, is driven by epidemiologic purity and evidence rigor, with quality improvement a downstream consideration. The advantages of a stakeholder-driven versus a topic-driven approach are highlighted by comparisons of guidelines for otitis media with effusion, thyroid nodules, sepsis, and acute bacterial rhinosinusitis. These comparisons show that stakeholder-driven guidelines are more likely to address the quality improvement needs and pressing concerns of clinicians and patients, including understudied populations and patients with multiple chronic conditions. Conversely, a topic-driven approach often addresses "typical" patients, based on research that may not reflect the needs of high-risk groups excluded from studies because of ethical issues or a desire for purity of research design.

Sequence-of-events-driven automation of the deep space network

NASA Technical Reports Server (NTRS)

Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

1996-01-01

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Sequence-of-Events-Driven Automation of the Deep Space Network

NASA Technical Reports Server (NTRS)

Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

1996-01-01

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Perceptions of Public Breastfeeding Images and Their Association With Breastfeeding Knowledge and Attitudes Among an Internet Panel of Men Ages 21-44 in the United States.

PubMed

Magnusson, Brianna M; Thackeray, Callie R; Van Wagenen, Sarah A; Davis, Siena F; Richards, Rickelle; Merrill, Ray M

2017-02-01

Men's attitudes toward public breastfeeding may influence a woman's decisions about breastfeeding and her perceived comfort with public breastfeeding. Research aim: This study aimed to evaluate factors associated with men's visual perception of images of public breastfeeding. A 95-item online survey was administered to 502 U.S. men ages 21 to 44. Respondents were presented with four images of women breastfeeding and asked to evaluate agreement with 15 adjectives describing each image. Based on factor analysis, 13 of these adjectives were combined to create the Breastfeeding Images Scale for each image. An 8-item Situational Statements Scale and the 17-item Iowa Infant Feeding Attitude Scale (IIFAS) were used to assess breastfeeding knowledge and attitudes. Multiple regression was used to evaluate the association between breastfeeding attitudes and knowledge and the Breastfeeding Images Scale. The image depicting a woman breastfeeding privately at home had the highest mean score of 71.95, 95% confidence interval (CI) [70.69, 73.22], on the Breastfeeding Images Scale, compared with 61.93, 95% CI [60.51, 63.36], for the image of a woman breastfeeding in a public setting. The overall mean scale score for the IIFAS was 56.99, 95% CI [56.27, 57.70], and for the Situational Statements Scale was 28.80, 95% CI [27.92, 29.69]. For all images, increasing breastfeeding knowledge and attitudes measured by the IIFAS and the Situational Statements Scale were associated with a more positive perception of the image. Images of public breastfeeding are viewed less favorably by men in the sample than are images of private breastfeeding. Knowledge and attitudes toward breastfeeding are positively associated with perception of breastfeeding images.

A knowledge-based framework for image enhancement in aviation security.

PubMed

Singh, Maneesha; Singh, Sameer; Partridge, Derek

2004-12-01

The main aim of this paper is to present a knowledge-based framework for automatically selecting the best image enhancement algorithm from several available on a per image basis in the context of X-ray images of airport luggage. The approach detailed involves a system that learns to map image features that represent its viewability to one or more chosen enhancement algorithms. Viewability measures have been developed to provide an automatic check on the quality of the enhanced image, i.e., is it really enhanced? The choice is based on ground-truth information generated by human X-ray screening experts. Such a system, for a new image, predicts the best-suited enhancement algorithm. Our research details the various characteristics of the knowledge-based system and shows extensive results on real images.

Content-based image retrieval with ontological ranking

NASA Astrophysics Data System (ADS)

Tsai, Shen-Fu; Tsai, Min-Hsuan; Huang, Thomas S.

2010-02-01

Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text; the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well; second, the grouping is different from pure visual similarity clustering. More specifically, the inferred concepts of each image in the group are examined in the context of a huge concept ontology to determine their true relations with what people have in mind when doing image search.

The Just-in-Time Imperative.

ERIC Educational Resources Information Center

Weintraub, Robert S.; Martineau, Jennifer W.

2002-01-01

Increasinginly in demand, just-in-time learning is associated with informal, learner-driven knowledge acquisition. Technologies being used include databases, intranets, portals, and content management systems. (JOW)

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

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

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Laser speckle imaging based on photothermally driven convection.

PubMed

Regan, Caitlin; Choi, Bernard

2016-02-01

Laser speckle imaging (LSI) is an interferometric technique that provides information about the relative speed of moving scatterers in a sample. Photothermal LSI overcomes limitations in depth resolution faced by conventional LSI by incorporating an excitation pulse to target absorption by hemoglobin within the vascular network. Here we present results from experiments designed to determine the mechanism by which photothermal LSI decreases speckle contrast. We measured the impact of mechanical properties on speckle contrast, as well as the spatiotemporal temperature dynamics and bulk convective motion occurring during photothermal LSI. Our collective data strongly support the hypothesis that photothermal LSI achieves a transient reduction in speckle contrast due to bulk motion associated with thermally driven convection. The ability of photothermal LSI to image structures below a scattering medium may have important preclinical and clinical applications.

Imaging the Dynamics of the Ferroelectric Stripe Phase Near a Field-Driven Phase Transition in Bismuth Ferrite

NASA Astrophysics Data System (ADS)

Laanait, Nouamane; Li, Qian; Zhang, Zhan; Kalinin, Sergei

Electric field-driven phase transitions in multiferroic systems such as Bismuth Ferrite could potentially host interesting domain dynamics due to the coexistence of multiple order parameters. Structural imaging of these dynamics under a host of elastic and electric boundary conditions is therefore of interest. Here, we present X-ray diffraction microscopy (XDM) studies of the domain wall dynamics in a bismuth ferrite thin-film near the field-driven transition from rhombohedral to monoclinic (R to M). XDM is a novel full-field imaging technique that uses Bragg diffraction contrast to image structural configurations with sub-100nm lateral resolutions and fast acquisition times (milliseconds to seconds per image). We find that under electric fields 100 kV/cm, a bismuth ferrite thin-film (100 nm BiFeO3/DyScO3 (110)) undergoes a structural phase transition but that this new phase (M) is pinned by the preexisting ferroelectric/ferroelastic stripe phase (R). At higher fields ( 300 kV/cm), we observe unusually slow domain wall dynamics in the stripe phase, consisting of periodicity doubling, domain wall roughening and crowding. These observed ferroelastic domain wall spatial dynamics are weakly constrained by the crystal symmetry of the orthorhombic substrate but exhibit nonlinear dynamics more commonly associated with disordered nematic systems. This work was supported by the Eugene P. Wigner Fellowship program at Oak Ridge National Laboratory, a U.S. Department of Energy facility.

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

PubMed

Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

2017-08-01

Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

User-driven sampling strategies in image exploitation

NASA Astrophysics Data System (ADS)

Harvey, Neal; Porter, Reid

2013-12-01

Visual analytics and interactive machine learning both try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human-computer interaction. This paper focuses on one aspect of the human-computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteration, we investigate situations where the user selects which data is to be labeled at each iteration. User-driven sampling strategies can emerge in many visual analytics applications but they have not been fully developed in machine learning. User-driven sampling strategies suggest new theoretical and practical research questions for both visualization science and machine learning. In this paper we identify and quantify the potential benefits of these strategies in a practical image analysis application. We find user-driven sampling strategies can sometimes provide significant performance gains by steering tools towards local minima that have lower error than tools trained with all of the data. In preliminary experiments we find these performance gains are particularly pronounced when the user is experienced with the tool and application domain.

Objected-oriented remote sensing image classification method based on geographic ontology model

NASA Astrophysics Data System (ADS)

Chu, Z.; Liu, Z. J.; Gu, H. Y.

2016-11-01

Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.

Feature maps driven no-reference image quality prediction of authentically distorted images

NASA Astrophysics Data System (ADS)

Ghadiyaram, Deepti; Bovik, Alan C.

2015-03-01

Current blind image quality prediction models rely on benchmark databases comprised of singly and synthetically distorted images, thereby learning image features that are only adequate to predict human perceived visual quality on such inauthentic distortions. However, real world images often contain complex mixtures of multiple distortions. Rather than a) discounting the effect of these mixtures of distortions on an image's perceptual quality and considering only the dominant distortion or b) using features that are only proven to be efficient for singly distorted images, we deeply study the natural scene statistics of authentically distorted images, in different color spaces and transform domains. We propose a feature-maps-driven statistical approach which avoids any latent assumptions about the type of distortion(s) contained in an image, and focuses instead on modeling the remarkable consistencies in the scene statistics of real world images in the absence of distortions. We design a deep belief network that takes model-based statistical image features derived from a very large database of authentically distorted images as input and discovers good feature representations by generalizing over different distortion types, mixtures, and severities, which are later used to learn a regressor for quality prediction. We demonstrate the remarkable competence of our features for improving automatic perceptual quality prediction on a benchmark database and on the newly designed LIVE Authentic Image Quality Challenge Database and show that our approach of combining robust statistical features and the deep belief network dramatically outperforms the state-of-the-art.

Art for reward's sake: visual art recruits the ventral striatum.

PubMed

Lacey, Simon; Hagtvedt, Henrik; Patrick, Vanessa M; Anderson, Amy; Stilla, Randall; Deshpande, Gopikrishna; Hu, Xiaoping; Sato, João R; Reddy, Srinivas; Sathian, K

2011-03-01

A recent study showed that people evaluate products more positively when they are physically associated with art images than similar non-art images. Neuroimaging studies of visual art have investigated artistic style and esthetic preference but not brain responses attributable specifically to the artistic status of images. Here we tested the hypothesis that the artistic status of images engages reward circuitry, using event-related functional magnetic resonance imaging (fMRI) during viewing of art and non-art images matched for content. Subjects made animacy judgments in response to each image. Relative to non-art images, art images activated, on both subject- and item-wise analyses, reward-related regions: the ventral striatum, hypothalamus and orbitofrontal cortex. Neither response times nor ratings of familiarity or esthetic preference for art images correlated significantly with activity that was selective for art images, suggesting that these variables were not responsible for the art-selective activations. Investigation of effective connectivity, using time-varying, wavelet-based, correlation-purged Granger causality analyses, further showed that the ventral striatum was driven by visual cortical regions when viewing art images but not non-art images, and was not driven by regions that correlated with esthetic preference for either art or non-art images. These findings are consistent with our hypothesis, leading us to propose that the appeal of visual art involves activation of reward circuitry based on artistic status alone and independently of its hedonic value. Copyright © 2010 Elsevier Inc. All rights reserved.

ART FOR REWARD’S SAKE: VISUAL ART RECRUITS THE VENTRAL STRIATUM

PubMed Central

Lacey, Simon; Hagtvedt, Henrik; Patrick, Vanessa M.; Anderson, Amy; Stilla, Randall; Deshpande, Gopikrishna; Hu, Xiaoping; Sato, João R.; Reddy, Srinivas; Sathian, K.

2010-01-01

A recent study showed that people evaluate products more positively when they are physically associated with art images than similar non-art images. Neuroimaging studies of visual art have investigated artistic style and esthetic preference but not brain responses attributable specifically to the artistic status of images. Here we tested the hypothesis that the artistic status of images engages reward circuitry, using event-related functional magnetic resonance imaging (fMRI) during viewing of art and non-art images matched for content. Subjects made animacy judgments in response to each image. Relative to non-art images, art images activated, on both subject- and item-wise analyses, reward-related regions: the ventral striatum, hypothalamus and orbitofrontal cortex. Neither response times nor ratings of familiarity or esthetic preference for art images correlated significantly with activity that was selective for art images, suggesting that these variables were not responsible for the art-selective activations. Investigation of effective connectivity, using time-varying, wavelet-based, correlation-purged Granger causality analyses, further showed that the ventral striatum was driven by visual cortical regions when viewing art images but not non-art images, and was not driven by regions that correlated with esthetic preference for either art or non -art images. These findings are consistent with our hypothesis, leading us to propose that the appeal of visual art involves activation of reward circuitry based on artistic status alone and independently of its hedonic value. PMID:21111833

Development and testing of a novel survey to assess Stakeholder-driven Community Diffusion of childhood obesity prevention efforts.

PubMed

Korn, Ariella R; Hennessy, Erin; Hammond, Ross A; Allender, Steven; Gillman, Matthew W; Kasman, Matt; McGlashan, Jaimie; Millar, Lynne; Owen, Brynle; Pachucki, Mark C; Swinburn, Boyd; Tovar, Alison; Economos, Christina D

2018-05-31

Involving groups of community stakeholders (e.g., steering committees) to lead community-wide health interventions appears to support multiple outcomes ranging from policy and systems change to individual biology. While numerous tools are available to measure stakeholder characteristics, many lack detail on reliability and validity, are not context specific, and may not be sensitive enough to capture change over time. This study describes the development and reliability of a novel survey to measure Stakeholder-driven Community Diffusion via assessment of stakeholders' social networks, knowledge, and engagement about childhood obesity prevention. This study was completed in three phases. Phase 1 included conceptualization and online survey development through literature reviews and expert input. Phase 2 included a retrospective study with stakeholders from two completed whole-of-community interventions. Between May-October 2015, 21 stakeholders from the Shape Up Somerville and Romp & Chomp interventions recalled their social networks, knowledge, and engagement pre-post intervention. We also assessed one-week test-retest reliability of knowledge and engagement survey modules among Shape Up Somerville respondents. Phase 3 included survey modifications and a second prospective reliability assessment. Test-retest reliability was assessed in May 2016 among 13 stakeholders involved in ongoing interventions in Victoria, Australia. In Phase 1, we developed a survey with 7, 20 and 50 items for the social networks, knowledge, and engagement survey modules, respectively. In the Phase 2 retrospective study, Shape Up Somerville and Romp & Chomp networks included 99 and 54 individuals. Pre-post Shape Up Somerville and Romp & Chomp mean knowledge scores increased by 3.5 points (95% CI: 0.35-6.72) and (- 0.42-7.42). Engagement scores did not change significantly (Shape Up Somerville: 1.1 points (- 0.55-2.73); Romp & Chomp: 0.7 points (- 0.43-1.73)). Intraclass correlation coefficients (ICCs) for knowledge and engagement were 0.88 (0.67-0.97) and 0.97 (0.89-0.99). In Phase 3, the modified knowledge and engagement survey modules included 18 and 25 items, respectively. Knowledge and engagement ICCs were 0.84 (0.62-0.95) and 0.58 (0.23-0.86). The survey measures upstream stakeholder properties-social networks, knowledge, and engagement-with good test-retest reliability. Future research related to Stakeholder-driven Community Diffusion should focus on prospective change and survey validation for intervention effectiveness.

A synchronized particle image velocimetry and infrared thermography technique applied to convective mass transfer in champagne glasses

NASA Astrophysics Data System (ADS)

Beaumont, Fabien; Liger-Belair, Gérard; Bailly, Yannick; Polidori, Guillaume

2016-05-01

In champagne glasses, it was recently suggested that ascending bubble-driven flow patterns should be involved in the release of gaseous carbon dioxide (CO2) and volatile organic compounds. A key assumption was that the higher the velocity of the upward bubble-driven flow patterns in the liquid phase, the higher the volume fluxes of gaseous CO2 desorbing from the supersaturated liquid phase. In the present work, simultaneous monitoring of bubble-driven flow patterns within champagne glasses and gaseous CO2 escaping above the champagne surface was performed, through particle image velocimetry and infrared thermography techniques. Two quite emblematic types of champagne drinking vessels were investigated, namely a long-stemmed flute and a wide coupe. The synchronized use of both techniques proved that the cloud of gaseous CO2 escaping above champagne glasses strongly depends on the mixing flow patterns found in the liquid phase below.

Imaging Plasmon Hybridization of Fano Resonances via Hot-Electron-Mediated Absorption Mapping.

PubMed

Simoncelli, Sabrina; Li, Yi; Cortés, Emiliano; Maier, Stefan A

2018-06-13

The inhibition of radiative losses in dark plasmon modes allows storing electromagnetic energy more efficiently than in far-field excitable bright-plasmon modes. As such, processes benefiting from the enhanced absorption of light in plasmonic materials could also take profit of dark plasmon modes to boost and control nanoscale energy collection, storage, and transfer. We experimentally probe this process by imaging with nanoscale precision the hot-electron driven desorption of thiolated molecules from the surface of gold Fano nanostructures, investigating the effect of wavelength and polarization of the incident light. Spatially resolved absorption maps allow us to show the contribution of each element of the nanoantenna in the hot-electron driven process and their interplay in exciting a dark plasmon mode. Plasmon-mode engineering allows control of nanoscale reactivity and offers a route to further enhance and manipulate hot-electron driven chemical reactions and energy-conversion and transfer at the nanoscale.

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing

NASA Astrophysics Data System (ADS)

Kerekes, John P.; Presnar, Michael D.; Fourspring, Kenneth D.; Ninkov, Zoran; Pogorzala, David R.; Raisanen, Alan D.; Rice, Andrew C.; Vasquez, Juan R.; Patel, Jeffrey P.; MacIntyre, Robert T.; Brown, Scott D.

2009-05-01

A novel multi-object spectrometer (MOS) is being explored for use as an adaptive performance-driven sensor that tracks moving targets. Developed originally for astronomical applications, the instrument utilizes an array of micromirrors to reflect light to a panchromatic imaging array. When an object of interest is detected the individual micromirrors imaging the object are tilted to reflect the light to a spectrometer to collect a full spectrum. This paper will present example sensor performance from empirical data collected in laboratory experiments, as well as our approach in designing optical and radiometric models of the MOS channels and the micromirror array. Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor. Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.

Heterogeneous postsurgical data analytics for predictive modeling of mortality risks in intensive care units.

PubMed

Yun Chen; Hui Yang

2014-01-01

The rapid advancements of biomedical instrumentation and healthcare technology have resulted in data-rich environments in hospitals. However, the meaningful information extracted from rich datasets is limited. There is a dire need to go beyond current medical practices, and develop data-driven methods and tools that will enable and help (i) the handling of big data, (ii) the extraction of data-driven knowledge, (iii) the exploitation of acquired knowledge for optimizing clinical decisions. This present study focuses on the prediction of mortality rates in Intensive Care Units (ICU) using patient-specific healthcare recordings. It is worth mentioning that postsurgical monitoring in ICU leads to massive datasets with unique properties, e.g., variable heterogeneity, patient heterogeneity, and time asyncronization. To cope with the challenges in ICU datasets, we developed the postsurgical decision support system with a series of analytical tools, including data categorization, data pre-processing, feature extraction, feature selection, and predictive modeling. Experimental results show that the proposed data-driven methodology outperforms traditional approaches and yields better results based on the evaluation of real-world ICU data from 4000 subjects in the database. This research shows great potentials for the use of data-driven analytics to improve the quality of healthcare services.

Each-One-Teach-One Mobile Networks: An Innovative Strategy for Knowledge Access in Asian Countries

ERIC Educational Resources Information Center

Misra, P. K.

2012-01-01

The changing landscape of learning is helping Asian countries to emerge as technology-driven knowledge-based societies. The success of these societies depends on promoting the acquisition of key competences and broadening opportunities for innovative and more flexible forms of learning for every citizen. Considering that in Asia almost everyone…

Education, Globalisation and the Future of the Knowledge Economy

ERIC Educational Resources Information Center

Brown, Phillip; Lauder, Hugh; Ashton, David

2008-01-01

The dominant view today is of a global knowledge-based economy, driven by the application of new technologies, accelerating the shift to high-skilled, high-waged European economies. This view is reflected in the expansion of higher education and the key role of higher education in national and European economic policy. The Lisbon agenda seeks to…

Early Childhood General and Special Educators: An Examination of Similarities and Differences in Beliefs, Knowledge, and Practice

ERIC Educational Resources Information Center

Spear, Caitlin F.; Piasta, Shayne B.; Yeomans-Maldonado, Gloria; Ottley, Jennifer R.; Justice, Laura M.; O'Connell, Ann A.

2018-01-01

In this study, we provide a contemporary examination of the similarities and differences between early childhood general educators (ECEs) and early childhood special educators (ECSEs) within a theoretically driven model that accounted for the associations of beliefs and knowledge with practice. We used structural equation modeling to examine the…

Public Understanding of Plant Biology: Voices from the Bottom of the Garden

ERIC Educational Resources Information Center

Watts, Mike

2015-01-01

Many household gardeners accumulate considerable knowledge of plant biology through a range of informal learning sources. This knowledge seldom relates to school biology and is driven by interest, keen motivation and what is termed here "vital relevance." A small opportunity sample of 12 gardeners (6 M, 6 F) is interviewed in terms of…

Theory-Driven Intervention Improves Calcium Intake, Osteoporosis Knowledge, and Self-Efficacy in Community-Dwelling Older Black Adults

ERIC Educational Resources Information Center

Babatunde, Oyinlola T.; Himburg, Susan P.; Newman, Frederick L.; Campa, Adriana; Dixon, Zisca

2011-01-01

Objective: To assess the effectiveness of an osteoporosis education program to improve calcium intake, knowledge, and self-efficacy in community-dwelling older Black adults. Design: Randomized repeated measures experimental design. Setting: Churches and community-based organizations. Participants: Men and women (n = 110) 50 years old and older…

TV nurses: promoting a positive image of nursing?

PubMed

Spear, Hila J

2010-01-01

It's understood that medical dramas are meant to entertain, not serve as documentaries. Nevertheless, media-driven messages are powerful, influencing the culture and collective mindset. This article evaluates current images of nurses in the media and challenges nurses to engage in professional and public service designed to promote a positive media and public image of nursing.

Integrating ergonomics knowledge into business-driven design projects: The shaping of resource constraints in engineering consultancy.

PubMed

Hall-Andersen, Lene Bjerg; Neumann, Patrick; Broberg, Ole

2016-10-17

The integration of ergonomics knowledge into engineering projects leads to both healthier and more efficient workplaces. There is a lack of knowledge about integrating ergonomic knowledge into the design practice in engineering consultancies. This study explores how organizational resources can pose constraints for the integration of ergonomics knowledge into engineering design projects in a business-driven setting, and how ergonomists cope with these resource constraints. An exploratory case study in an engineering consultancy was conducted. A total of 27 participants were interviewed. Data were collected applying semi-structured interviews, observations, and documentary studies. Interviews were transcribed, coded, and categorized into themes. From the analysis five overall themes emerged as major constituents of resource constraints: 1) maximizing project revenue, 2) payment for ergonomics services, 3) value of ergonomic services, 4) role of the client, and 5) coping strategies to overcome resource constraints. We hypothesize that resource constraints were shaped due to sub-optimization of costs in design projects. The economical contribution of ergonomics measures was not evaluated in the entire life cycle of a designed workplace. Coping strategies included teaming up with engineering designers in the sales process or creating an alliance with ergonomists in the client organization.

Big data to smart data in Alzheimer's disease: The brain health modeling initiative to foster actionable knowledge.

PubMed

Geerts, Hugo; Dacks, Penny A; Devanarayan, Viswanath; Haas, Magali; Khachaturian, Zaven S; Gordon, Mark Forrest; Maudsley, Stuart; Romero, Klaus; Stephenson, Diane

2016-09-01

Massive investment and technological advances in the collection of extensive and longitudinal information on thousands of Alzheimer patients results in large amounts of data. These "big-data" databases can potentially advance CNS research and drug development. However, although necessary, they are not sufficient, and we posit that they must be matched with analytical methods that go beyond retrospective data-driven associations with various clinical phenotypes. Although these empirically derived associations can generate novel and useful hypotheses, they need to be organically integrated in a quantitative understanding of the pathology that can be actionable for drug discovery and development. We argue that mechanism-based modeling and simulation approaches, where existing domain knowledge is formally integrated using complexity science and quantitative systems pharmacology can be combined with data-driven analytics to generate predictive actionable knowledge for drug discovery programs, target validation, and optimization of clinical development. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Recent advances in radiation oncology

PubMed Central

Garibaldi, Cristina; Jereczek-Fossa, Barbara Alicja; Marvaso, Giulia; Dicuonzo, Samantha; Rojas, Damaris Patricia; Cattani, Federica; Starzyńska, Anna; Ciardo, Delia; Surgo, Alessia; Leonardi, Maria Cristina; Ricotti, Rosalinda

2017-01-01

Radiotherapy (RT) is very much a technology-driven treatment modality in the management of cancer. RT techniques have changed significantly over the past few decades, thanks to improvements in engineering and computing. We aim to highlight the recent developments in radiation oncology, focusing on the technological and biological advances. We will present state-of-the-art treatment techniques, employing photon beams, such as intensity-modulated RT, volumetric-modulated arc therapy, stereotactic body RT and adaptive RT, which make possible a highly tailored dose distribution with maximum normal tissue sparing. We will analyse all the steps involved in the treatment: imaging, delineation of the tumour and organs at risk, treatment planning and finally image-guidance for accurate tumour localisation before and during treatment delivery. Particular attention will be given to the crucial role that imaging plays throughout the entire process. In the case of adaptive RT, the precise identification of target volumes as well as the monitoring of tumour response/modification during the course of treatment is mainly based on multimodality imaging that integrates morphological, functional and metabolic information. Moreover, real-time imaging of the tumour is essential in breathing adaptive techniques to compensate for tumour motion due to respiration. Brief reference will be made to the recent spread of particle beam therapy, in particular to the use of protons, but also to the yet limited experience of using heavy particles such as carbon ions. Finally, we will analyse the latest biological advances in tumour targeting. Indeed, the effectiveness of RT has been improved not only by technological developments but also through the integration of radiobiological knowledge to produce more efficient and personalised treatment strategies. PMID:29225692

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Geodesic active fields--a geometric framework for image registration.

PubMed

Zosso, Dominique; Bresson, Xavier; Thiran, Jean-Philippe

2011-05-01

In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inverse problem, which is usually solved by adding a regularization term. Here, we propose a multiplicative coupling between the registration term and the regularization term, which turns out to be equivalent to embed the deformation field in a weighted minimal surface problem. Then, the deformation field is driven by a minimization flow toward a harmonic map corresponding to the solution of the registration problem. This proposed approach for registration shares close similarities with the well-known geodesic active contours model in image segmentation, where the segmentation term (the edge detector function) is coupled with the regularization term (the length functional) via multiplication as well. As a matter of fact, our proposed geometric model is actually the exact mathematical generalization to vector fields of the weighted length problem for curves and surfaces introduced by Caselles-Kimmel-Sapiro. The energy of the deformation field is measured with the Polyakov energy weighted by a suitable image distance, borrowed from standard registration models. We investigate three different weighting functions, the squared error and the approximated absolute error for monomodal images, and the local joint entropy for multimodal images. As compared to specialized state-of-the-art methods tailored for specific applications, our geometric framework involves important contributions. Firstly, our general formulation for registration works on any parametrizable, smooth and differentiable surface, including nonflat and multiscale images. In the latter case, multiscale images are registered at all scales simultaneously, and the relations between space and scale are intrinsically being accounted for. Second, this method is, to the best of our knowledge, the first reparametrization invariant registration method introduced in the literature. Thirdly, the multiplicative coupling between the registration term, i.e. local image discrepancy, and the regularization term naturally results in a data-dependent tuning of the regularization strength. Finally, by choosing the metric on the deformation field one can freely interpolate between classic Gaussian and more interesting anisotropic, TV-like regularization.

Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades

USGS Publications Warehouse

Zhu, Qiuan; Peng, Changhui; Liu, Jinxun; Jiang, Hong; Fang, Xiuqin; Chen, Huai; Niu, Zhichun; Gong, Peng; Lin, Guanghui; Wang, Meng; Yang, Yanzheng; Chang, Jie; Ge, Ying; Xiang, Wenhua; Deng, Xiangwen; He, Jin-Sheng

2016-01-01

Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH4) emissions in China is important for improving our knowledge on CH4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH4 model to quantify the human and climate change induced contributions to natural wetland CH4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH4 emissions reduction (0.92 TgCH4), and climate change contributed 20.4% to the CH4 emissions increase (0.31 TgCH4), suggesting that decreasing CH4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH4 emissions estimation.

Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades

PubMed Central

Zhu, Qiuan; Peng, Changhui; Liu, Jinxun; Jiang, Hong; Fang, Xiuqin; Chen, Huai; Niu, Zhenguo; Gong, Peng; Lin, Guanghui; Wang, Meng; Wang, Han; Yang, Yanzheng; Chang, Jie; Ge, Ying; Xiang, Wenhua; Deng, Xiangwen; He, Jin-Sheng

2016-01-01

Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH4) emissions in China is important for improving our knowledge on CH4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH4 model to quantify the human and climate change induced contributions to natural wetland CH4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH4 emissions reduction (0.92 TgCH4), and climate change contributed 20.4% to the CH4 emissions increase (0.31 TgCH4), suggesting that decreasing CH4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH4 emissions estimation. PMID:27892535

Are We Correctly Measuring Star-Formation Rates?

NASA Astrophysics Data System (ADS)

McQuinn, Kristen B.; Skillman, Evan D.; Dolphin, Andrew E.; Mitchell, Noah P.

2017-01-01

Integrating our knowledge of star formation (SF) traced by observations at different wavelengths is essential for correctly interpreting and comparing SF activity in a variety of systems and environments. This study compares extinction-corrected, integrated ultraviolet (UV) emission from resolved galaxies with color-magnitude diagram (CMD) based star-formation rates (SFRs) derived from resolved stellar populations and CMD fitting techniques in 19 nearby starburst and post-starburst dwarf galaxies. The data sets are from the panchromatic Starburst Irregular Dwarf Survey (STARBIRDS) and include deep legacy GALEX UV imaging, Hubble Space Telescope optical imaging, and Spitzer MIPS imaging. For the majority of the sample, the integrated near-UV fluxes predicted from the CMD-based SFRs—using four different models—agree with the measured, extinction corrected, integrated near-UV fluxes from GALEX images, but the far-UV (FUV) predicted fluxes do not. Furthermore, we find a systematic deviation between the SFRs based on integrated FUV luminosities and existing scaling relations, and the SFRs based on the resolved stellar populations. This offset is not driven by different SF timescales, variations in SFRs, UV attenuation, nor stochastic effects. This first comparison between CMD-based SFRs and an integrated FUV emission SFR indicator suggests that the most likely cause of the discrepancy is the theoretical FUV-SFR calibration from stellar evolutionary libraries and/or stellar atmospheric models. We present an empirical calibration of the FUV-based SFR relation for dwarf galaxies, with uncertainties, which is ˜53% larger than previous relations. These results have signficant implications for measuring FUV-based SFRs of high-redshift galaxies.

Knowledge on Irradiation, Medical Imaging Prescriptions, and Clinical Imaging Referral Guidelines among Physicians in a Sub-Saharan African Country (Cameroon)

PubMed Central

Tene, Ulrich; Samba Ngano, Odette; Tchemtchoua Youta, Justine; Simo, Augustin; Gonsu Fotsin, Joseph

2017-01-01

Background Clinical imaging guidelines (CIGs) are suitable tools to enhance justification of imaging procedures. Objective To assess physicians' knowledge on irradiation, their self-perception of imaging prescriptions, and the use of CIGs. Materials and Methods A questionnaire of 21 items was self-administered between July and August 2016 to 155 referring physicians working in seven university-affiliated hospitals in Yaoundé and Douala (Cameroon). This pretested questionnaire based on imaging referral practices, the use and the need of CIGs, knowledge on radiation doses of 11 specific radiologic procedures, and knowledge of injurious effects of radiation was completed in the presence of the investigator. Scores were allocated for each question. Results 155 questionnaires were completed out of 180 administered (86.1%). Participants were 90 (58%) females, 63 (40.64%) specialists, 53 (34.20%) residents/interns, and 39 (25.16%) general practitioners. The average professional experience was 7.4 years (1–25 years). The mean knowledge score was 11.5/59 with no influence of sex, years of experience, and professional category. CIGs users' score was better than nonusers (means 14.2 versus 10.6; p < 0.01). 80% of physicians (124/155) underrated radiation doses of routine imaging exams. Seventy-eight (50.3%) participants have knowledge on CIGs and half of them made use of them. “Impact on diagnosis” was the highest justification criteria follow by “impact on treatment decision.” Unjustified requests were mainly for “patient expectation or will” or for “research motivations.” 96% of interviewees believed that making available national CIGs will improve justification. Conclusion Most physicians did not have appropriate awareness about radiation doses for routine imaging procedures. A small number of physicians have knowledge on CIGs but they believe that making available CIGs will improve justification of imaging procedures. Continuous trainings on radiation protection and implementation of national CIGs are therefore recommended. PMID:28630770

Building an Ontology-driven Database for Clinical Immune Research

PubMed Central

Ma, Jingming

2006-01-01

The clinical researches of immune response usually generate a huge amount of biomedical testing data over a certain period of time. The user-friendly data management systems based on the relational database will help immunologists/clinicians to fully manage the data. On the other hand, the same biological assays such as ELISPOT and flow cytometric assays are involved in immunological experiments no matter of different study purposes. The reuse of biological knowledge is one of driving forces behind this ontology-driven data management. Therefore, an ontology-driven database will help to handle different clinical immune researches and help immunologists/clinicians easily understand the immunological data from each other. We will discuss some outlines for building an ontology-driven data management for clinical immune researches (ODMim). PMID:17238637

Ontology-driven data integration and visualization for exploring regional geologic time and paleontological information

NASA Astrophysics Data System (ADS)

Wang, Chengbin; Ma, Xiaogang; Chen, Jianguo

2018-06-01

Initiatives of open data promote the online publication and sharing of large amounts of geologic data. How to retrieve information and discover knowledge from the big data is an ongoing challenge. In this paper, we developed an ontology-driven data integration and visualization pilot system for exploring information of regional geologic time, paleontology, and fundamental geology. The pilot system (http://www2.cs.uidaho.edu/%7Emax/gts/)

Multimodal image analysis of clinical influences on preterm brain development

PubMed Central

Ball, Gareth; Aljabar, Paul; Nongena, Phumza; Kennea, Nigel; Gonzalez‐Cinca, Nuria; Falconer, Shona; Chew, Andrew T.M.; Harper, Nicholas; Wurie, Julia; Rutherford, Mary A.; Edwards, A. David

2017-01-01

Objective Premature birth is associated with numerous complex abnormalities of white and gray matter and a high incidence of long‐term neurocognitive impairment. An integrated understanding of these abnormalities and their association with clinical events is lacking. The aim of this study was to identify specific patterns of abnormal cerebral development and their antenatal and postnatal antecedents. Methods In a prospective cohort of 449 infants (226 male), we performed a multivariate and data‐driven analysis combining multiple imaging modalities. Using canonical correlation analysis, we sought separable multimodal imaging markers associated with specific clinical and environmental factors and correlated to neurodevelopmental outcome at 2 years. Results We found five independent patterns of neuroanatomical variation that related to clinical factors including age, prematurity, sex, intrauterine complications, and postnatal adversity. We also confirmed the association between imaging markers of neuroanatomical abnormality and poor cognitive and motor outcomes at 2 years. Interpretation This data‐driven approach defined novel and clinically relevant imaging markers of cerebral maldevelopment, which offer new insights into the nature of preterm brain injury. Ann Neurol 2017;82:233–246 PMID:28719076

Laser speckle imaging based on photothermally driven convection

PubMed Central

Regan, Caitlin; Choi, Bernard

2016-01-01

Abstract. Laser speckle imaging (LSI) is an interferometric technique that provides information about the relative speed of moving scatterers in a sample. Photothermal LSI overcomes limitations in depth resolution faced by conventional LSI by incorporating an excitation pulse to target absorption by hemoglobin within the vascular network. Here we present results from experiments designed to determine the mechanism by which photothermal LSI decreases speckle contrast. We measured the impact of mechanical properties on speckle contrast, as well as the spatiotemporal temperature dynamics and bulk convective motion occurring during photothermal LSI. Our collective data strongly support the hypothesis that photothermal LSI achieves a transient reduction in speckle contrast due to bulk motion associated with thermally driven convection. The ability of photothermal LSI to image structures below a scattering medium may have important preclinical and clinical applications. PMID:26927221

Defocused Imaging of UV-Driven Surface-Bound Molecular Motors.

PubMed

Krajnik, Bartosz; Chen, Jiawen; Watson, Matthew A; Cockroft, Scott L; Feringa, Ben L; Hofkens, Johan

2017-05-31

Synthetic molecular motors continue to attract great interest due to their ability to transduce energy into nanomechanical motion, the potential to do work and drive systems out-of-equilibrium. Of particular interest are unidirectional rotary molecular motors driven by chemical fuel or light. Probing the mechanistic details of their operation at the single-molecule level is hampered by the diffraction limit, which prevents the collection of dynamic positional information by traditional optical methods. Here, we use defocused wide-field imaging to examine the unidirectional rotation of individual molecular rotary motors on a quartz surface in unprecedented detail. The sequential occupation of nanomechanical states during the UV and heat-induced cycle of rotation are directly imaged in real-time. The approach will undoubtedly prove important in elucidating the mechanistic details and assessing the utility of novel synthetic molecular motors in the future.

Energy-resolved coherent diffraction from laser-driven electronic motion in atoms

NASA Astrophysics Data System (ADS)

Shao, Hua-Chieh; Starace, Anthony F.

2017-10-01

We investigate theoretically the use of energy-resolved ultrafast electron diffraction to image laser-driven electronic motion in atoms. A chirped laser pulse is used to transfer the valence electron of the lithium atom from the ground state to the first excited state. During this process, the electronic motion is imaged by 100-fs and 1-fs electron pulses in energy-resolved diffraction measurements. Simulations show that the angle-resolved spectra reveal the time evolution of the energy content and symmetry of the electronic state. The time-dependent diffraction patterns are further interpreted in terms of the momentum transfer. For the case of incident 1-fs electron pulses, the rapid 2 s -2 p quantum beat motion of the target electron is imaged as a time-dependent asymmetric oscillation of the diffraction pattern.

A knowledge-based machine vision system for space station automation

NASA Technical Reports Server (NTRS)

Chipman, Laure J.; Ranganath, H. S.

1989-01-01

A simple knowledge-based approach to the recognition of objects in man-made scenes is being developed. Specifically, the system under development is a proposed enhancement to a robot arm for use in the space station laboratory module. The system will take a request from a user to find a specific object, and locate that object by using its camera input and information from a knowledge base describing the scene layout and attributes of the object types included in the scene. In order to use realistic test images in developing the system, researchers are using photographs of actual NASA simulator panels, which provide similar types of scenes to those expected in the space station environment. Figure 1 shows one of these photographs. In traditional approaches to image analysis, the image is transformed step by step into a symbolic representation of the scene. Often the first steps of the transformation are done without any reference to knowledge of the scene or objects. Segmentation of an image into regions generally produces a counterintuitive result in which regions do not correspond to objects in the image. After segmentation, a merging procedure attempts to group regions into meaningful units that will more nearly correspond to objects. Here, researchers avoid segmenting the image as a whole, and instead use a knowledge-directed approach to locate objects in the scene. The knowledge-based approach to scene analysis is described and the categories of knowledge used in the system are discussed.

Ultrasound for internal medicine physicians: the future of the physical examination.

PubMed

Dulohery, Megan M; Stoven, Samantha; Kurklinsky, Andrew K; Kurklinksy, Andrew; Halvorsen, Andrew; McDonald, Furman S; Bhagra, Anjali

2014-06-01

With the advent of compact ultrasound (US) devices, it is easier for physicians to enhance their physical examinations through the use of US. However, although this new tool is widely available, few internal medicine physicians have US training. This study sought to understand physicians' baseline knowledge and skill, provide education in US principles, and demonstrate that proper use of compact US devices is a skill that can be quickly learned. Training was performed at the Mayo Clinic in June 2010 and June 2011. The participants consisted of internal medicine residents. The workshop included didactics and hands-on US experiences with human and cadaver models in a simulation center. Pretests and posttests of residents' knowledge, attitudes, and skills with US were completed. We reassessed the 2010 group in the spring of 2012 with a long-term retention survey for knowledge and confidence in viewing images. A total of 136 interns completed the workshop. Thirty-nine residents completed the long-term retention survey. Posttest assessments showed a statistically significant improvement in the knowledge of US imaging, confidence in identifying structures, image identification, and image acquisition (P < .0001). In the long-term retention study, knowledge of US imaging and confidence in identifying structures did decline. This educational intervention resulted in improvement in US knowledge and image acquisition. However, the knowledge diminished over time, suggesting that further education is needed if US is to become an important component of internal medicine training and practice. © 2014 by the American Institute of Ultrasound in Medicine.

Body image and its relation to obesity for Pacific minority ethnic groups in New Zealand: a critical analysis.

PubMed

Teevale, Tasileta

2011-03-01

The stimulus behind most of the early investigations into Pacific or Polynesian peoples' body image, particularly those that looked to compare with Western or Westernised groups, is the assumption that Pacific peoples valued and therefore desired very large bodies, and in relation to obesity-risk, this is a problematic cultural feature to have. This may be driven by popular anecdotes which are captured in the title of one such study "Do Polynesians still believe that big is beautiful?" To the author's knowledge, no research in Pacific peoples' body image has been conducted in the New Zealand (NZ) context by Pacific researchers. This study makes a contribution to the literature gap and more importantly through an emic viewpoint. A critique of the current literature is provided below which calls into question the initial catalyst behind earlier investigations which have led to the perpetuation of particular types of body image research for Pacific groups. Using mixed-methods, the specific objective of this study was to describe the behaviours, beliefs and values of Pacific adolescents and their parents, that are related to body image. A self-completion questionnaire was administered to 2495 Pacific students who participated in the New Zealand arm of the Obesity Prevention In Communities (OPIC) project. Sixty-eight people (33 adolescents and 35 parents) from 30 Pacific households were interviewed in the qualitative phase of the study. This study found Pacific adolescents and their parents did not desire obesity-sized bodies but desired a range of average-sized bodies that met their Pacific-defined view of health. It is not clear whether body image research makes any meaningful contribution to obesity prevention for Pacific people, given the cultural-bounded nature of the concept "body image" which sits communication and understanding between obesity interventionists and all healthcare workers generally and Pacific communities. For obesity interventions to be acceptable and useful for Pacific people, they must be responsive to the beliefs and desires of these communities.

Curricula and Pedagogic Potentials When Educating Diverse Students in Higher Education: Students' "Funds of Knowledge" as a Bridge to Disciplinary Learning

ERIC Educational Resources Information Center

Daddow, Angela

2016-01-01

With the massification of higher education in a knowledge-driven economy, Western universities have struggled to keep pace with the cultural, linguistic, educational and economic diversity of university students and the complex realities of their lifeworlds. This has generated systemic inequities for diverse or "non-traditional"…

Theory in Practice: Why "Good Medicine" and "Scientific Medicine" Are Not Necessarily the Same Thing

ERIC Educational Resources Information Center

De Camargo, Kenneth, Jr.; Coeli, Claudia Medina

2006-01-01

The term "scientific medicine", ubiquitous in medical literature although poorly defined, can be traced to a number of assumptions, three of which are examined in this paper: that medicine is a form of knowledge-driven practice, where the established body of proven medical knowledge determines what doctors do; if what doctors do is either…

Exploring Teachers' Perceived Self Efficacy and Technological Pedagogical Content Knowledge with Respect to Educational Use of the World Wide Web

ERIC Educational Resources Information Center

Lee, Min-Hsien; Tsai, Chin-Chung

2010-01-01

Research in the area of educational technology has claimed that Web technology has driven online pedagogy such that teachers need to know how to use Web technology to assist their teaching. This study provides a framework for understanding teachers' Technological Pedagogical Content Knowledge-Web (TPCK-W), while integrating Web technology into…

Putting More "Modern" in Modern Physics Education: A Knowledge Building Approach Using Student Questions and Ideas about the Universe

ERIC Educational Resources Information Center

Wagner, Glenn

2017-01-01

Student-generated questions and ideas about our universe are the start of a rich and highly motivating learning environment. Using their curiosity-driven questions and ideas, students form Knowledge Building groups or "communities" where they plan, set goals, design questions for research, and assess the progress of their work, tasks…

Mission Operations of EO-1 with Onboard Autonomy

NASA Technical Reports Server (NTRS)

Tran, Daniel Q.

2006-01-01

Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the prior, labor and knowledge intensive mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the new autonomous operations as part of the Autonomous Sciencecraft Experiment.

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Impaired semantic knowledge underlies the reduced verbal short-term storage capacity in Alzheimer's disease.

PubMed

Peters, Frédéric; Majerus, Steve; De Baerdemaeker, Julie; Salmon, Eric; Collette, Fabienne

2009-12-01

A decrease in verbal short-term memory (STM) capacity is consistently observed in patients with Alzheimer's disease (AD). Although this impairment has been mainly attributed to attentional deficits during encoding and maintenance, the progressive deterioration of semantic knowledge in early stages of AD may also be an important determinant of poor STM performance. The aim of this study was to examine the influence of semantic knowledge on verbal short-term memory storage capacity in normal aging and in AD by exploring the impact of word imageability on STM performance. Sixteen patients suffering from mild AD, 16 healthy elderly subjects and 16 young subjects performed an immediate serial recall task using word lists containing high or low imageability words. All participant groups recalled more high imageability words than low imageability words, but the effect of word imageability on verbal STM was greater in AD patients than in both the young and the elderly control groups. More precisely, AD patients showed a marked decrease in STM performance when presented with lists of low imageability words, whereas recall of high imageability words was relatively well preserved. Furthermore, AD patients displayed an abnormal proportion of phonological errors in the low imageability condition. Overall, these results indicate that the support of semantic knowledge on STM performance was impaired for lists of low imageability words in AD patients. More generally, these findings suggest that the deterioration of semantic knowledge is partly responsible for the poor verbal short-term storage capacity observed in AD.

More than the Verbal Stimulus Matters: Visual Attention in Language Assessment for People with Aphasia Using Multiple-Choice Image Displays

ERIC Educational Resources Information Center

Heuer, Sabine; Ivanova, Maria V.; Hallowell, Brooke

2017-01-01

Purpose: Language comprehension in people with aphasia (PWA) is frequently evaluated using multiple-choice displays: PWA are asked to choose the image that best corresponds to the verbal stimulus in a display. When a nontarget image is selected, comprehension failure is assumed. However, stimulus-driven factors unrelated to linguistic…

Feature-based Morphometry

PubMed Central

Toews, Matthew; Wells, William M.; Collins, Louis; Arbel, Tal

2013-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between all subjects, FBM models images as a collage of distinct, localized image features which may not be present in all subjects. FBM thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. A probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. Features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. Scale-invariant image features are used, which reflect generic, salient patterns in the image. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer’s (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and obtains an equal error classification rate of 0.78 on new subjects. PMID:20426102

A capillary-driven micromixer: idea and fabrication

NASA Astrophysics Data System (ADS)

Lee, Chun-Te; Lee, Chun-Che

2012-10-01

Microfluidic systems have been drawing attention upon the various branches of engineering science and the allied areas within biology and biomedicine. In this paper, a fabrication of a capillary-driven micromixer using photoresist JSR and glasses is proposed. We design three types of planar capillary-driven micormixers with different sizes of baffles in the channel. Flow tests have shown that the micromixer with a baffle gap of 100 μm and space of 100 μm reaches a best mixing performance of 93% in gray-level image analysis.

Multirate and event-driven Kalman filters for helicopter flight

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Smith, Phillip; Suorsa, Raymond E.; Hussien, Bassam

1993-01-01

A vision-based obstacle detection system that provides information about objects as a function of azimuth and elevation is discussed. The range map is computed using a sequence of images from a passive sensor, and an extended Kalman filter is used to estimate range to obstacles. The magnitude of the optical flow that provides measurements for each Kalman filter varies significantly over the image depending on the helicopter motion and object location. In a standard Kalman filter, the measurement update takes place at fixed intervals. It may be necessary to use a different measurement update rate in different parts of the image in order to maintain the same signal to noise ratio in the optical flow calculations. A range estimation scheme that accepts the measurement only under certain conditions is presented. The estimation results from the standard Kalman filter are compared with results from a multirate Kalman filter and an event-driven Kalman filter for a sequence of helicopter flight images.

Modeling of Multi-Kilovolt X-ray Driven Ablation and Closure of Pinholes during Point-Projection Backlit Imaging

NASA Astrophysics Data System (ADS)

Bullock, A. B.; Landen, O. L.; Bradley, D. K.

2000-10-01

Pinhole-assisted point-projection backlighting of large samples with few µm pinholes can result in pinhole closure due to x-ray driven ablation of the high Z pinhole substrate, thereby potentially limiting the usefulness of this imaging method. The results of a previous study[1] using streaked 1-D backlit imaging of 25 mm W wires at the OMEGA laser are compared to simulations produced by HYADES, a 1-D Lagrangian hydrodynamics code. Interestingly, the observed image resolution stays fixed while the pinhole transmission drops within 1-2 ns, suggesting rapid filling by a long scale-length of low density substrate material. These results will be compared to time-dependent HYADES predictions of pinhole closure timescales and resolution. 1 A.B. bullock, D.K. Bradley, and O.L. Landen, to be published in RSI (2001). *This work was performed under the auspices of the U.S. Department of Energy by University of California/Lawrence Livermore National Laboratory under Contract No. W-7405-Eng-48.

Reversible watermarking for knowledge digest embedding and reliability control in medical images.

PubMed

Coatrieux, Gouenou; Le Guillou, Clara; Cauvin, Jean-Michel; Roux, Christian

2009-03-01

To improve medical image sharing in applications such as e-learning or remote diagnosis aid, we propose to make the image more usable by watermarking it with a digest of its associated knowledge. The aim of such a knowledge digest (KD) is for it to be used for retrieving similar images with either the same findings or differential diagnoses. It summarizes the symbolic descriptions of the image, the symbolic descriptions of the findings semiology, and the similarity rules that contribute to balancing the importance of previous descriptors when comparing images. Instead of modifying the image file format by adding some extra header information, watermarking is used to embed the KD in the pixel gray-level values of the corresponding images. When shared through open networks, watermarking also helps to convey reliability proofs (integrity and authenticity) of an image and its KD. The interest of these new image functionalities is illustrated in the updating of the distributed users' databases within the framework of an e-learning application demonstrator of endoscopic semiology.

Basic-level categorization of intermediate complexity fragments reveals top-down effects of expertise in visual perception.

PubMed

Harel, Assaf; Ullman, Shimon; Harari, Danny; Bentin, Shlomo

2011-07-28

Visual expertise is usually defined as the superior ability to distinguish between exemplars of a homogeneous category. Here, we ask how real-world expertise manifests at basic-level categorization and assess the contribution of stimulus-driven and top-down knowledge-based factors to this manifestation. Car experts and novices categorized computer-selected image fragments of cars, airplanes, and faces. Within each category, the fragments varied in their mutual information (MI), an objective quantifiable measure of feature diagnosticity. Categorization of face and airplane fragments was similar within and between groups, showing better performance with increasing MI levels. Novices categorized car fragments more slowly than face and airplane fragments, while experts categorized car fragments as fast as face and airplane fragments. The experts' advantage with car fragments was similar across MI levels, with similar functions relating RT with MI level for both groups. Accuracy was equal between groups for cars as well as faces and airplanes, but experts' response criteria were biased toward cars. These findings suggest that expertise does not entail only specific perceptual strategies. Rather, at the basic level, expertise manifests as a general processing advantage arguably involving application of top-down mechanisms, such as knowledge and attention, which helps experts to distinguish between object categories. © ARVO

Reverberation Mapping of the Broad Line Region: Application to a Hydrodynamical Line-driven Disk Wind Solution

NASA Astrophysics Data System (ADS)

Waters, Tim; Kashi, Amit; Proga, Daniel; Eracleous, Michael; Barth, Aaron J.; Greene, Jenny

2016-08-01

The latest analysis efforts in reverberation mapping are beginning to allow reconstruction of echo images (or velocity-delay maps) that encode information about the structure and kinematics of the broad line region (BLR) in active galactic nuclei (AGNs). Such maps can constrain sophisticated physical models for the BLR. The physical picture of the BLR is often theorized to be a photoionized wind launched from the AGN accretion disk. Previously we showed that the line-driven disk wind solution found in an earlier simulation by Proga and Kallman is virialized over a large distance from the disk. This finding implies that, according to this model, black hole masses can be reliably estimated through reverberation mapping techniques. However, predictions of echo images expected from line-driven disk winds are not available. Here, after presenting the necessary radiative transfer methodology, we carry out the first calculations of such predictions. We find that the echo images are quite similar to other virialized BLR models such as randomly orbiting clouds and thin Keplerian disks. We conduct a parameter survey exploring how echo images, line profiles, and transfer functions depend on both the inclination angle and the line opacity. We find that the line profiles are almost always single peaked, while transfer functions tend to have tails extending to large time delays. The outflow, despite being primarily equatorially directed, causes an appreciable blueshifted excess on both the echo image and line profile when seen from lower inclinations (I≲ 45^\\circ ). This effect may be observable in low ionization lines such as {{H}}β .

MO-DE-BRA-05: Developing Effective Medical Physics Knowledge Structures: Models and Methods

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

Sprawls, P

Purpose: Develop a method and supporting online resources to be used by medical physics educators for teaching medical imaging professionals and trainees so they develop highly-effective physics knowledge structures that can contribute to improved diagnostic image quality on a global basis. Methods: The different types of mental knowledge structures were analyzed and modeled with respect to both the learning and teaching process for their development and the functions or tasks that can be performed with the knowledge. While symbolic verbal and mathematical knowledge structures are very important in medical physics for many purposes, the tasks of applying physics in clinicalmore » imaging--especially to optimize image quality and diagnostic accuracy--requires a sensory conceptual knowledge structure, specifically, an interconnected network of visually based concepts. This type of knowledge supports tasks such as analysis, evaluation, problem solving, interacting, and creating solutions. Traditional educational methods including lectures, online modules, and many texts are serial procedures and limited with respect to developing interconnected conceptual networks. A method consisting of the synergistic combination of on-site medical physics teachers and the online resource, CONET (Concept network developer), has been developed and made available for the topic Radiographic Image Quality. This was selected as the inaugural topic, others to follow, because it can be used by medical physicists teaching the large population of medical imaging professionals, such as radiology residents, who can apply the knowledge. Results: Tutorials for medical physics educators on developing effective knowledge structures are being presented and published and CONET is available with open access for all to use. Conclusion: An adjunct to traditional medical physics educational methods with the added focus on sensory concept development provides opportunities for medical physics teachers to share their knowledge and experience at a higher cognitive level and produce medical professionals with the enhanced ability to apply physics to clinical procedures.« less

Developing a knowledge base to support the annotation of ultrasound images of ectopic pregnancy.

PubMed

Dhombres, Ferdinand; Maurice, Paul; Friszer, Stéphanie; Guilbaud, Lucie; Lelong, Nathalie; Khoshnood, Babak; Charlet, Jean; Perrot, Nicolas; Jauniaux, Eric; Jurkovic, Davor; Jouannic, Jean-Marie

2017-01-31

Ectopic pregnancy is a frequent early complication of pregnancy associated with significant rates of morbidly and mortality. The positive diagnosis of this condition is established through transvaginal ultrasound scanning. The timing of diagnosis depends on the operator expertise in identifying the signs of ectopic pregnancy, which varies dramatically among medical staff with heterogeneous training. Developing decision support systems in this context is expected to improve the identification of these signs and subsequently improve the quality of care. In this article, we present a new knowledge base for ectopic pregnancy, and we demonstrate its use on the annotation of clinical images. The knowledge base is supported by an application ontology, which provides the taxonomy, the vocabulary and definitions for 24 types and 81 signs of ectopic pregnancy, 484 anatomical structures and 32 technical elements for image acquisition. The knowledge base provides a sign-centric model of the domain, with the relations of signs to ectopic pregnancy types, anatomical structures and the technical elements. The evaluation of the ontology and knowledge base demonstrated a positive feedback from a panel of 17 medical users. Leveraging these semantic resources, we developed an application for the annotation of ultrasound images. Using this application, 6 operators achieved a precision of 0.83 for the identification of signs in 208 ultrasound images corresponding to 35 clinical cases of ectopic pregnancy. We developed a new ectopic pregnancy knowledge base for the annotation of ultrasound images. The use of this knowledge base for the annotation of ultrasound images of ectopic pregnancy showed promising results from the perspective of clinical decision support system development. Other gynecological disorders and fetal anomalies may benefit from our approach.

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study

PubMed Central

Choi, Se Y; Ahn, Seung H; Choi, Jae D; Kim, Jung H; Lee, Byoung-Il; Kim, Jeong-In

2016-01-01

Objective: The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses. Methods: A 5 × 5 × 5 mm3 uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current–time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5–7) and knowledge-based IMR (soft-tissue Levels 1–3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed. Results: The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs. Conclusion: At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment. Advances in knowledge: Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients. PMID:26577542

The Effects of Prior Knowledge and Instruction on Understanding Image Formation.

ERIC Educational Resources Information Center

Galili, Igal; And Others

1993-01-01

Reports a study (n=27) concerning the knowledge about image formation exhibited by students following instruction in geometrical optics in an activity-based college physics course for prospective elementary teachers. Student diagrams and verbal comments indicate their knowledge can be described as an intermediate state: a hybridization of…

Event management for large scale event-driven digital hardware spiking neural networks.

PubMed

Caron, Louis-Charles; D'Haene, Michiel; Mailhot, Frédéric; Schrauwen, Benjamin; Rouat, Jean

2013-09-01

The interest in brain-like computation has led to the design of a plethora of innovative neuromorphic systems. Individually, spiking neural networks (SNNs), event-driven simulation and digital hardware neuromorphic systems get a lot of attention. Despite the popularity of event-driven SNNs in software, very few digital hardware architectures are found. This is because existing hardware solutions for event management scale badly with the number of events. This paper introduces the structured heap queue, a pipelined digital hardware data structure, and demonstrates its suitability for event management. The structured heap queue scales gracefully with the number of events, allowing the efficient implementation of large scale digital hardware event-driven SNNs. The scaling is linear for memory, logarithmic for logic resources and constant for processing time. The use of the structured heap queue is demonstrated on a field-programmable gate array (FPGA) with an image segmentation experiment and a SNN of 65,536 neurons and 513,184 synapses. Events can be processed at the rate of 1 every 7 clock cycles and a 406×158 pixel image is segmented in 200 ms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantifying the dynamic density driven convection in high permeability packed beds.

PubMed

Teng, Ying; Jiang, Lanlan; Fan, Yingting; Liu, Yu; Wang, Dayong; Abudula, Abuliti; Song, Yongchen

2017-06-01

The density driven convection phenomenon is expected to have a significant and positive role in CO 2 geological storage capacity and safety. The onset and development of density-driven convective on the core scale is critical to understand the mass transfer mechanism. In this paper, laboratory experiments were conducted to investigate the density-driven convective in a vertical tube. The deuterium oxide (D 2 O)/manganese chloride (MnCl 2 ) water solution in water or brine were as an analog for CO 2 -rich brine in original brine. Experiments are repeated with variations in permeability to vary the characteristic Rayleigh number. Based on the MRI technology, the intensity images showed the interface clearly, reflecting the transition from diffusion to convective. With the echo-multi-slice pulse sequence method, the intensity images can be obtained as 2min 8s. For the denser fluid pairs, fingers appeared, propagated, coalesced and multi-fingers formed. The finger growth rate of the convective was visualized as three distinct periods: rising, stable and declining. Detailed information regarding the wave number, wave length, onset time and mixing time as functions of Rayleigh number are developed. Copyright © 2017 Elsevier Inc. All rights reserved.

How do Medical Radiation Science educators keep up with the [clinical] Joneses?

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

Giles, Eileen

Medical radiation science (MRS) disciplines include medical imaging, radiation therapy and nuclear medicine. These allied health fields are technology driven and evolving rapidly with regard to imaging and treatment techniques within the clinical environment. This research aims to identify the activities academics are currently participating in to maintain clinical currency and offer strategies to support academics to connect with an ever-changing clinical environment. A cross-sectional designed survey was sampled across the nine Australian universities where MRS programmes are offered. The survey targeted academic teaching staff that were working in MRS programmes at the time of distribution (n ≈ 90). Enablersmore » and barriers to maintaining clinical currency as well as support to participate in continuing professional development were rated by the respondents. Descriptive statistics were used to analyse quantitative data, and free-text comment responses were collated and themed. There were 38 responses to the survey (42%) and all three disciplines were represented. Responses highlighted activities valued by academics as contributing to their knowledge of current practice and as resources to inform their teaching. Positive elements included participating in clinical work and research, attending clinical sites and training days and attending scientific meetings. Common barriers identified by academics in this area were time constraints, workload allocation and employer/financial support. This research has identified that Australian MRS academics participate in a broad range of activities to inform their teaching and maintain knowledge of contemporary clinical practice. A connection with the clinical world is valued highly by academics, however, access and support to maintain that link is often a difficulty and as a result for MRS teaching staff keeping up with the clinical [MRS] Joneses is often a challenge.« less

A Curriculum Experiment in Climate Change Education Using and Integrated Approach of Content Knowledge Instruction and Student-Driven Research to Promote Civic Engagement

NASA Astrophysics Data System (ADS)

Adams, P. E.; Heinrichs, J. F.

2009-12-01

One of the greatest challenges facing the world is climate change. Coupled with this challenge is an under-informed population that has not received a rigorous education about climate change other than what is available through the media. Fort Hays State University is piloting a course on climate change targeted to students early in their academic careers. The course is modeled after our past work (NSF DUE-0088818) of integrating content knowledge instruction and student-driven research where there was a positive correlation between student research engagement and student knowledge gains. The current course, based on prior findings, utilizes a mix of inquiry-based instruction, problem-based learning, and student-driven research to educate and engage the students in understanding climate change. The course was collaboratively developed by a geoscientist and science educator both of whom are active in citizen science programs. The emphasis on civic engagement by students is reflected in the course structure. The course model is unique in that 50% of the course is dedicated to developing core knowledge and technical skills (e.g. critical analysis, writing, data acquisition, data representation, and research design), and 50% to conducting a research project using available data sets from federal agencies and research groups. A key element of the course is a focus on local and regional data sets to make climate change relevant to the students. The research serves as a means of civic engagement by the students as they are tasked to understand their role in communicating their research findings to the community and coping with the local and regional changes they find through their research.

A Curriculum Experiment in Climate Change Education Using an Integrated Approach of Content Knowledge Instruction and Student-Driven Research, Year 2

NASA Astrophysics Data System (ADS)

Adams, P. E.; Heinrichs, J. F.

2010-12-01

One of the greatest challenges facing the world is climate change. Coupled with this challenge is an under-informed population that has not received a rigorous education about climate change other than what is available through the media. Fort Hays State University is in a second year of piloting a course on climate change targeted to students early in their academic careers. The course is modeled after our past work (NSF DUE-0088818) of integrating content knowledge instruction and student-driven research where there was a positive correlation between student research engagement and student knowledge gains. The second pilot offering utilizes a mix of inquiry-based instruction, problem-based learning, and student-driven research to educate and engage the students in understanding climate change. The course was collaboratively developed by a geoscientist and science educator both of whom are active in citizen science programs. The course model is unique in that 50% of the course is dedicated to developing core knowledge and technical skills (e.g. global climate change, critical analysis, writing, data acquisition, data representation, and research design), and 50% to conducting a research project using available data sets from federal agencies and research groups. A key element of the course is a focus on data sets to make climate change relevant to the students. The research serves as a means of civic engagement by the students as they are tasked to understand their role in communicating their research findings to the community and coping with the local and regional changes they find through their research. The impacts of course changes from the first offering to the second offering of the course will be reported, as well as the structure of the course.

Towards an Intelligent Planning Knowledge Base Development Environment

NASA Technical Reports Server (NTRS)

Chien, S.

1994-01-01

ract describes work in developing knowledge base editing and debugging tools for the Multimission VICAR Planner (MVP) system. MVP uses artificial intelligence planning techniques to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing requests made to the JPL Multimission Image Processing Laboratory.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Mission Driven Scene Understanding: Candidate Model Training and Validation

DTIC Science & Technology

2016-09-01

driven scene understanding. One of the candidate engines that we are evaluating is a convolutional neural network (CNN) program installed on a Windows 10...Theano-AlexNet6,7) installed on a Windows 10 notebook computer. To the best of our knowledge, an implementation of the open-source, Python-based...AlexNet CNN on a Windows notebook computer has not been previously reported. In this report, we present progress toward the proof-of-principle testing

Reduction of Metal Artifact in Single Photon-Counting Computed Tomography by Spectral-Driven Iterative Reconstruction Technique

PubMed Central

Nasirudin, Radin A.; Mei, Kai; Panchev, Petar; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Fiebich, Martin; Noël, Peter B.

2015-01-01

Purpose The exciting prospect of Spectral CT (SCT) using photon-counting detectors (PCD) will lead to new techniques in computed tomography (CT) that take advantage of the additional spectral information provided. We introduce a method to reduce metal artifact in X-ray tomography by incorporating knowledge obtained from SCT into a statistical iterative reconstruction scheme. We call our method Spectral-driven Iterative Reconstruction (SPIR). Method The proposed algorithm consists of two main components: material decomposition and penalized maximum likelihood iterative reconstruction. In this study, the spectral data acquisitions with an energy-resolving PCD were simulated using a Monte-Carlo simulator based on EGSnrc C++ class library. A jaw phantom with a dental implant made of gold was used as an object in this study. A total of three dental implant shapes were simulated separately to test the influence of prior knowledge on the overall performance of the algorithm. The generated projection data was first decomposed into three basis functions: photoelectric absorption, Compton scattering and attenuation of gold. A pseudo-monochromatic sinogram was calculated and used as input in the reconstruction, while the spatial information of the gold implant was used as a prior. The results from the algorithm were assessed and benchmarked with state-of-the-art reconstruction methods. Results Decomposition results illustrate that gold implant of any shape can be distinguished from other components of the phantom. Additionally, the result from the penalized maximum likelihood iterative reconstruction shows that artifacts are significantly reduced in SPIR reconstructed slices in comparison to other known techniques, while at the same time details around the implant are preserved. Quantitatively, the SPIR algorithm best reflects the true attenuation value in comparison to other algorithms. Conclusion It is demonstrated that the combination of the additional information from Spectral CT and statistical reconstruction can significantly improve image quality, especially streaking artifacts caused by the presence of materials with high atomic numbers. PMID:25955019

Enhancing navigation in biomedical databases by community voting and database-driven text classification

PubMed Central

Duchrow, Timo; Shtatland, Timur; Guettler, Daniel; Pivovarov, Misha; Kramer, Stefan; Weissleder, Ralph

2009-01-01

Background The breadth of biological databases and their information content continues to increase exponentially. Unfortunately, our ability to query such sources is still often suboptimal. Here, we introduce and apply community voting, database-driven text classification, and visual aids as a means to incorporate distributed expert knowledge, to automatically classify database entries and to efficiently retrieve them. Results Using a previously developed peptide database as an example, we compared several machine learning algorithms in their ability to classify abstracts of published literature results into categories relevant to peptide research, such as related or not related to cancer, angiogenesis, molecular imaging, etc. Ensembles of bagged decision trees met the requirements of our application best. No other algorithm consistently performed better in comparative testing. Moreover, we show that the algorithm produces meaningful class probability estimates, which can be used to visualize the confidence of automatic classification during the retrieval process. To allow viewing long lists of search results enriched by automatic classifications, we added a dynamic heat map to the web interface. We take advantage of community knowledge by enabling users to cast votes in Web 2.0 style in order to correct automated classification errors, which triggers reclassification of all entries. We used a novel framework in which the database "drives" the entire vote aggregation and reclassification process to increase speed while conserving computational resources and keeping the method scalable. In our experiments, we simulate community voting by adding various levels of noise to nearly perfectly labelled instances, and show that, under such conditions, classification can be improved significantly. Conclusion Using PepBank as a model database, we show how to build a classification-aided retrieval system that gathers training data from the community, is completely controlled by the database, scales well with concurrent change events, and can be adapted to add text classification capability to other biomedical databases. The system can be accessed at . PMID:19799796

Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

PubMed

Buonaccorsi, Giovanni A; Roberts, Caleb; Cheung, Sue; Watson, Yvonne; O'Connor, James P B; Davies, Karen; Jackson, Alan; Jayson, Gordon C; Parker, Geoff J M

2006-09-01

The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

Combination of visual and symbolic knowledge: A survey in anatomy.

PubMed

Banerjee, Imon; Patané, Giuseppe; Spagnuolo, Michela

2017-01-01

In medicine, anatomy is considered as the most discussed field and results in a huge amount of knowledge, which is heterogeneous and covers aspects that are mostly independent in nature. Visual and symbolic modalities are mainly adopted for exemplifying knowledge about human anatomy and are crucial for the evolution of computational anatomy. In particular, a tight integration of visual and symbolic modalities is beneficial to support knowledge-driven methods for biomedical investigation. In this paper, we review previous work on the presentation and sharing of anatomical knowledge, and the development of advanced methods for computational anatomy, also focusing on the key research challenges for harmonizing symbolic knowledge and spatial 3D data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation

NASA Astrophysics Data System (ADS)

Kneser, Reinhard; Lehmann, Helko; Geller, Dieter; Qian, Yue-Chen; Weese, Jürgen

2009-02-01

To make accurate decisions based on imaging data, radiologists must associate the viewed imaging data with the corresponding anatomical structures. Furthermore, given a disease hypothesis possible image findings which verify the hypothesis must be considered and where and how they are expressed in the viewed images. If rare anatomical variants, rare pathologies, unfamiliar protocols, or ambiguous findings are present, external knowledge sources such as medical encyclopedias are consulted. These sources are accessed using keywords typically describing anatomical structures, image findings, pathologies. In this paper we present our vision of how a patient's imaging data can be automatically enhanced with anatomical knowledge as well as knowledge about image findings. On one hand, we propose the automatic annotation of the images with labels from a standard anatomical ontology. These labels are used as keywords for a medical encyclopedia such as STATdx to access anatomical descriptions, information about pathologies and image findings. On the other hand we envision encyclopedias to contain links to region- and finding-specific image processing algorithms. Then a finding is evaluated on an image by applying the respective algorithm in the associated anatomical region. Towards realization of our vision, we present our method and results of automatic annotation of anatomical structures in 3D MRI brain images. Thereby we develop a complex surface mesh model incorporating major structures of the brain and a model-based segmentation method. We demonstrate the validity by analyzing the results of several training and segmentation experiments with clinical data focusing particularly on the visual pathway.

Industrial knowledge design: an approach for designing information artifacts

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

Schatz, Sae; Berking, Peter; Raybourn, Elaine M.

In this study, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. Themore » paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike.« less

Industrial knowledge design: an approach for designing information artifacts

DOE PAGES

Schatz, Sae; Berking, Peter; Raybourn, Elaine M.

2017-01-19

In this study, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. Themore » paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike.« less

Education and Technology in the 21st Century Experiences of Adult Online Learners Using Web 2.0

ERIC Educational Resources Information Center

Bryant, Wanda L.

2014-01-01

The emergence of a knowledge-based and technology-driven economy has prompted adults to seek additional knowledge and skills that will enable them to participate effectively in society. The rapid growth and popularity of the internet tools such as Web 2.0 tools have revolutionized adult learning. Through the rich support of Web 2.0 tools, adult…

Integrating shape into an interactive segmentation framework

NASA Astrophysics Data System (ADS)

Kamalakannan, S.; Bryant, B.; Sari-Sarraf, H.; Long, R.; Antani, S.; Thoma, G.

2013-02-01

This paper presents a novel interactive annotation toolbox which extends a well-known user-steered segmentation framework, namely Intelligent Scissors (IS). IS, posed as a shortest path problem, is essentially driven by lower level image based features. All the higher level knowledge about the problem domain is obtained from the user through mouse clicks. The proposed work integrates one higher level feature, namely shape up to a rigid transform, into the IS framework, thus reducing the burden on the user and the subjectivity involved in the annotation procedure, especially during instances of occlusions, broken edges, noise and spurious boundaries. The above mentioned scenarios are commonplace in medical image annotation applications and, hence, such a tool will be of immense help to the medical community. As a first step, an offline training procedure is performed in which a mean shape and the corresponding shape variance is computed by registering training shapes up to a rigid transform in a level-set framework. The user starts the interactive segmentation procedure by providing a training segment, which is a part of the target boundary. A partial shape matching scheme based on a scale-invariant curvature signature is employed in order to extract shape correspondences and subsequently predict the shape of the unsegmented target boundary. A `zone of confidence' is generated for the predicted boundary to accommodate shape variations. The method is evaluated on segmentation of digital chest x-ray images for lung annotation which is a crucial step in developing algorithms for screening Tuberculosis.

Numerical study of core formation of asymmetrically driven cone-guided targets

DOE PAGES

Sawada, Hiroshi; Sakagami, Hitoshi

2017-09-22

Compression of a directly driven fast ignition cone-sphere target with a finite number of laser beams is numerically studied using a three-dimensional hydrodynamics code IMPACT-3D. The formation of a dense plasma core is simulated for 12-, 9-, 6-, and 4-beam configurations of the GEKKO XII laser. The complex 3D shapes of the cores are analyzed by elucidating synthetic 2D x-ray radiographic images in two orthogonal directions. Finally, the simulated x-ray images show significant differences in the core shape between the two viewing directions and rotation of the stagnating core axis in the top view for the axisymmetric 9- and 6-beammore » configurations.« less

Numerical study of core formation of asymmetrically driven cone-guided targets

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

Sawada, Hiroshi; Sakagami, Hitoshi

Compression of a directly driven fast ignition cone-sphere target with a finite number of laser beams is numerically studied using a three-dimensional hydrodynamics code IMPACT-3D. The formation of a dense plasma core is simulated for 12-, 9-, 6-, and 4-beam configurations of the GEKKO XII laser. The complex 3D shapes of the cores are analyzed by elucidating synthetic 2D x-ray radiographic images in two orthogonal directions. Finally, the simulated x-ray images show significant differences in the core shape between the two viewing directions and rotation of the stagnating core axis in the top view for the axisymmetric 9- and 6-beammore » configurations.« less

Emphysema diagnosis using X-ray dark-field imaging at a laser-driven compact synchrotron light source

PubMed Central

Schleede, Simone; Meinel, Felix G.; Bech, Martin; Herzen, Julia; Achterhold, Klaus; Potdevin, Guillaume; Malecki, Andreas; Adam-Neumair, Silvia; Thieme, Sven F.; Bamberg, Fabian; Nikolaou, Konstantin; Bohla, Alexander; Yildirim, Ali Ö.; Loewen, Roderick; Gifford, Martin; Ruth, Ronald; Eickelberg, Oliver; Reiser, Maximilian; Pfeiffer, Franz

2012-01-01

In early stages of various pulmonary diseases, such as emphysema and fibrosis, the change in X-ray attenuation is not detectable with absorption-based radiography. To monitor the morphological changes that the alveoli network undergoes in the progression of these diseases, we propose using the dark-field signal, which is related to small-angle scattering in the sample. Combined with the absorption-based image, the dark-field signal enables better discrimination between healthy and emphysematous lung tissue in a mouse model. All measurements have been performed at 36 keV using a monochromatic laser-driven miniature synchrotron X-ray source (Compact Light Source). In this paper we present grating-based dark-field images of emphysematous vs. healthy lung tissue, where the strong dependence of the dark-field signal on mean alveolar size leads to improved diagnosis of emphysema in lung radiographs. PMID:23074250

Image-Processing Program

NASA Technical Reports Server (NTRS)

Roth, D. J.; Hull, D. R.

1994-01-01

IMAGEP manipulates digital image data to effect various processing, analysis, and enhancement functions. It is keyboard-driven program organized into nine subroutines. Within subroutines are sub-subroutines also selected via keyboard. Algorithm has possible scientific, industrial, and biomedical applications in study of flows in materials, analysis of steels and ores, and pathology, respectively.

An evaluation of data-driven motion estimation in comparison to the usage of external-surrogates in cardiac SPECT imaging

PubMed Central

Mukherjee, Joyeeta Mitra; Hutton, Brian F; Johnson, Karen L; Pretorius, P Hendrik; King, Michael A

2014-01-01

Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference (MSD), mutual information (MI), normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation (NCC) and entropy of the difference (EDI). Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the visual appearance of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in patient studies. Pattern intensity and normalized mutual information cost functions were observed to have the best performance in terms of lowest average position error and stability with degradation of image quality of the partial reconstruction in simulations. In all patients, the visual quality of PI-based estimation was either significantly better or comparable to NMI-based estimation. Best visual quality was obtained with PI-based estimation in 1 of the 5 patient studies, and with external-surrogate based correction in 3 out of 5 patients. In the remaining patient study there was little motion and all methods yielded similar visual image quality. PMID:24107647

A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.

PubMed

Yu, Jun; Wang, Zeng-Fu

2015-05-01

A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.

Measuring implosion velocities in experiments and simulations of laser-driven cylindrical implosions on the OMEGA laser

NASA Astrophysics Data System (ADS)

Hansen, E. C.; Barnak, D. H.; Betti, R.; Campbell, E. M.; Chang, P.-Y.; Davies, J. R.; Glebov, V. Yu; Knauer, J. P.; Peebles, J.; Regan, S. P.; Sefkow, A. B.

2018-05-01

Laser-driven magnetized liner inertial fusion (MagLIF) on OMEGA involves cylindrical implosions, a preheat beam, and an applied magnetic field. Initial experiments excluded the preheat beam and magnetic field to better characterize the implosion. X-ray self-emission as measured by framing cameras was used to determine the shell trajectory. The 1D code LILAC was used to model the central region of the implosion, and results were compared to 2D simulations from the HYDRA code. Post-processing of simulation output with SPECT3D and Yorick produced synthetic x-ray images that were used to compare the simulation results with the x-ray framing camera data. Quantitative analysis shows that higher measured neutron yields correlate with higher implosion velocities. The future goal is to further analyze the x-ray images to characterize the uniformity of the implosions and apply these analysis techniques to integrated laser-driven MagLIF shots to better understand the effects of preheat and the magnetic field.

Large Spin-Wave Bullet in a Ferrimagnetic Insulator Driven by the Spin Hall Effect

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

Jungfleisch, M. B.; Zhang, W.; Sklenar, J.

2016-02-01

Due to its transverse nature, spin Hall effects (SHE) provide the possibility to excite and detect spin currents and magnetization dynamics even in magnetic insulators. Magnetic insulators are outstanding materials for the investigation of nonlinear phenomena and for novel low power spintronics applications because of their extremely low Gilbert damping. Here, we report on the direct imaging of electrically driven spin-torque ferromagnetic resonance (ST-FMR) in the ferrimagnetic insulator Y 3Fe 5O 12 based on the excitation and detection by SHEs. The driven spin dynamics in Y 3Fe 5O 12 is directly imaged by spatially-resolved microfocused Brillouin light scattering (BLS) spectroscopy.more » Previously, ST-FMR experiments assumed a uniform precession across the sample, which is not valid in our measurements. A strong spin-wave localization in the center of the sample is observed indicating the formation of a nonlinear, self-localized spin-wave `bullet'.« less

Direct observation of oxygen vacancy-driven structural and resistive phase transitions in La2/3Sr1/3MnO3

NASA Astrophysics Data System (ADS)

Yao, Lide; Inkinen, Sampo; van Dijken, Sebastiaan

2017-02-01

Resistive switching in transition metal oxides involves intricate physical and chemical behaviours with potential for non-volatile memory and memristive devices. Although oxygen vacancy migration is known to play a crucial role in resistive switching of oxides, an in-depth understanding of oxygen vacancy-driven effects requires direct imaging of atomic-scale dynamic processes and their real-time impact on resistance changes. Here we use in situ transmission electron microscopy to demonstrate reversible switching between three resistance states in epitaxial La2/3Sr1/3MnO3 films. Simultaneous high-resolution imaging and resistance probing indicate that the switching events are caused by the formation of uniform structural phases. Reversible horizontal migration of oxygen vacancies within the manganite film, driven by combined effects of Joule heating and bias voltage, predominantly triggers the structural and resistive transitions. Our findings open prospects for ionotronic devices based on dynamic control of physical properties in complex oxide nanostructures.

Semantics driven approach for knowledge acquisition from EMRs.

PubMed

Perera, Sujan; Henson, Cory; Thirunarayan, Krishnaprasad; Sheth, Amit; Nair, Suhas

2014-03-01

Semantic computing technologies have matured to be applicable to many critical domains such as national security, life sciences, and health care. However, the key to their success is the availability of a rich domain knowledge base. The creation and refinement of domain knowledge bases pose difficult challenges. The existing knowledge bases in the health care domain are rich in taxonomic relationships, but they lack nontaxonomic (domain) relationships. In this paper, we describe a semiautomatic technique for enriching existing domain knowledge bases with causal relationships gleaned from Electronic Medical Records (EMR) data. We determine missing causal relationships between domain concepts by validating domain knowledge against EMR data sources and leveraging semantic-based techniques to derive plausible relationships that can rectify knowledge gaps. Our evaluation demonstrates that semantic techniques can be employed to improve the efficiency of knowledge acquisition.

Label-free imaging of intracellular motility by low-coherent quantitative phase microscope in reflection geometry

NASA Astrophysics Data System (ADS)

Yamauchi, Toyohiko; Iwai, Hidenao; Yamashita, Yutaka

2011-11-01

We demonstrate tomographic imaging of intracellular activity of living cells by a low-coherent quantitative phase microscope. The intracellular organelles, such as the nucleus, nucleolus, and mitochondria, are moving around inside living cells, driven by the cellular physiological activity. In order to visualize the intracellular motility in a label-free manner we have developed a reflection-type quantitative phase microscope which employs the phase shifting interferometric technique with a low-coherent light source. The phase shifting interferometry enables us to quantitatively measure the intensity and phase of the optical field, and the low-coherence interferometry makes it possible to selectively probe a specific sectioning plane in the cell volume. The results quantitatively revealed the depth-resolved fluctuations of intracellular surfaces so that the plasma membrane and the membranes of intracellular organelles were independently measured. The transversal and the vertical spatial resolutions were 0.56 μm and 0.93 μm, respectively, and the mechanical sensitivity of the phase measurement was 1.2 nanometers. The mean-squared displacement was applied as a statistical tool to analyze the temporal fluctuation of the intracellular organelles. To the best of our knowledge, our system visualized depth-resolved intracellular organelles motion for the first time in sub-micrometer resolution without contrast agents.

Images as Orienting Activity: Using Theory to Inform Classroom Practices

ERIC Educational Resources Information Center

Feryok, Anne; Pryde, Michael

2012-01-01

Conceptualizations of teacher knowledge have shifted to focusing on the role of experiential rather than theoretical knowledge. There are different approaches to this, but the idea of an image that guides practice is widespread. One approach to images that has not been frequently investigated in studies of second language teachers is through…

Ethanol catalytic optical driven deposition for 1D and 2D materials with ultra-low power threshold of 0 dBm

NASA Astrophysics Data System (ADS)

Wang, Hao; Chen, Bohua; Xiao, Xu; Guo, Chaoshi; Zhang, Xiaoyan; Wang, Jun; Jiang, Meng; Wu, Kan; Chen, Jianping

2018-01-01

We have demonstrated a generalized optical driven deposition method, ethanol catalytic deposition (ECD) method, which is widely applicable to the deposition of a broad range of one-dimensional (1D) and two-dimensional (2D) materials with common deposition parameters. Using ECD method, deposition of 1D material carbon nanotubes and 2D materials MoS2, MoSe2, WS2 and WSe2 on tapered fiber has been demonstrated with the threshold power as low as 0 dBm. To our knowledge, this is the lowest threshold power ever reported in optical driven deposition, noting that the conventional optical driven deposition has a threshold typically near 15 dBm. It means ECD method can significantly reduce the power requirement and simplify the setup of the optical driven deposition as well as its wide applicability to different materials, which benefits the research on optical nonlinearity and ultrafast photonics of 1D and 2D materials.

Basket Studies: Redefining Clinical Trials in the Era of Genome-Driven Oncology.

PubMed

Tao, Jessica J; Schram, Alison M; Hyman, David M

2018-01-29

Understanding a tumor's detailed molecular profile has become increasingly necessary to deliver the standard of care for patients with advanced cancer. Innovations in both tumor genomic sequencing technology and the development of drugs that target molecular alterations have fueled recent gains in genome-driven oncology care. "Basket studies," or histology-agnostic clinical trials in genomically selected patients, represent one important research tool to continue making progress in this field. We review key aspects of genome-driven oncology care, including the purpose and utility of basket studies, biostatistical considerations in trial design, genomic knowledgebase development, and patient matching and enrollment models, which are critical for translating our genomic knowledge into clinically meaningful outcomes.

Rhetoric vs. reality: employer views on consumer-driven health care.

PubMed

Trude, Sally; Conwell, Leslie

2004-07-01

Because of rising premiums, employers are investigating new health insurance approaches that maintain workers' broad choice of providers while raising awareness of health care costs through increased patient financial responsibility. Employers' knowledge of new health plan products, including consumer-driven health plans and tiered-provider networks, has grown considerably in recent years, according to findings from the Center for Studying Health System Change's (HSC) 2002-03 site visit to 12 nationally representative communities. But employers are concerned that consumer-driven health plans would take considerable effort to implement without much cost savings. They also are skeptical that tiered-provider networks can adequately capture both cost and quality information in a way that is understandable to patients.

A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

PubMed

Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D

2011-07-01

Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

R&D in Poland: Is the Country Close to a Knowledge-Driven Economy?

NASA Astrophysics Data System (ADS)

Chybowska, Dorota; Chybowski, Leszek; Souchkov, Valeri

2018-06-01

Poland has a strong ambition to evolve rapidly into a knowledge-driven economy. Since 2004, it has been the largest beneficiary of European Union cohesion policy funds among all member states. Between 2007 and 2013, Poland was allocated approximately EUR 67 billion, whereas for 2014-2020 the EU budget earmarked EUR 82.5 billion for Polish cohesion policy. This means that in the coming years, Poland's R&D intensity will grow. But the question remains: is 27 years of free market economy enough to enable a country's economy to become knowledge-based ? This paper offers an analysis of Polish R&D expenditures and investments in terms of their sources (business, government or higher education sectors), types (European Union or state aid) and areas of support (infrastructure, education or innovation). It also characterises the Polish R&D market with its strengths and weaknesses. Then, it examines the process of technology transfer in Poland, comparing it to best practice. Finally, the paper lays out the barriers to effective commercialisation that need to be overcome, and attempts to answer the question raised in its title.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

PubMed

Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; De Keersmaecker, Sigrid C J; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L; Shin, Sook-il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M; Zengler, Karsten; Palsson, Bernhard O; Adkins, Joshua N; Bumann, Dirk

2011-01-18

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

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

Thiele, Ines; Hyduke, Daniel R.; Steeb, Benjamin

2011-01-01

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of thismore » reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Finally, taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.« less

Customer-driven outcomes: a patient and family perspective.

PubMed

Weston, Marla J; Weston, Richard R

2006-01-01

Experiencing the healthcare system during an acute surgical event highlighted factors that contributed to customer-driven outcomes. Communicating intentions of and rationale for interventions increased the patient and family's confidence, and engaged the whole mind-body connection into the healing process. Utilizing the family as a repository of patient information incorporated their perspective, knowledge, and wisdom into the delivery and evaluation of patient care. Lastly, fostering the relationship between the nurse and the patient and family strengthened the therapeutic process, thus providing a foundation for customizing care.

Critical Analysis of Textbooks: Knowledge-Generating Logics and the Emerging Image of "Global Economic Contexts"

ERIC Educational Resources Information Center

Thoma, Michael

2017-01-01

This paper presents an approach to the critical analysis of textbook knowledge, which, working from a discourse theory perspective (based on the work of Foucault), refers to the performative nature of language. The critical potential of the approach derives from an analysis of knowledge-generating logics, which produce particular images of reality…

The rise of developmental genetics - a historical account of the fusion of embryology and cell biology with human genetics and the emergence of the Stem Cell Initiative.

PubMed

Kidson, S H; Ballo, R; Greenberg, L J

2016-05-25

Genetics and cell biology are very prominent areas of biological research with rapid advances being driven by a flood of theoretical, technological and informational knowledge. Big biology and small biology continue to feed off each other. In this paper, we provide a brief overview of the productive interactions that have taken place between human geneticists and cell biologists at UCT, and credit is given to the enabling environment created led by Prof. Peter Beighton. The growth of new disciplines and disciplinary mergers that have swept away division of the past to make new exciting syntheses are discussed. We show how our joint research has benefitted from worldwide advances in developmental genetics, cloning and stem cell technologies, genomics, bioinformatics and imaging. We conclude by describing the role of the UCT Stem Cell Initiative and show how we are using induced pluripotent cells to carry out disease-in-the- dish studies on retinal degeneration and fibrosis.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

Measuring the shock impedance mismatch between high-density carbon and deuterium at the National Ignition Facility

DOE PAGES

Millot, M.; Celliers, P. M.; Sterne, P. A.; ...

2018-04-18

Fine-grained diamond, or high-density carbon (HDC), is being used as an ablator for inertial confinement fusion (ICF) research at the National Ignition Facility (NIF). Accurate equation of state (EOS) knowledge over a wide range of phase space is critical in the design and analysis of integrated ICF experiments. Here in this paper, we report shock and release measurements of the shock impedance mismatch between HDC and liquid deuterium conducted during shock-timing experiments having a first shock in the ablator ranging between 8 and 14 Mbar. Using ultrafast Doppler imaging velocimetry to track the leading shock front, we characterize the shockmore » velocity discontinuity upon the arrival of the shock at the HDC/liquid deuterium interface. Comparing the experimental data with tabular EOS models used to simulate integrated ICF experiments indicates the need for an improved multiphase EOS model for HDC in order to achieve a significant increase in neutron yield in indirect-driven ICF implosions with HDC ablators.« less

Measuring the shock impedance mismatch between high-density carbon and deuterium at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Millot, M.; Celliers, P. M.; Sterne, P. A.; Benedict, L. X.; Correa, A. A.; Hamel, S.; Ali, S. J.; Baker, K. L.; Berzak Hopkins, L. F.; Biener, J.; Collins, G. W.; Coppari, F.; Divol, L.; Fernandez-Panella, A.; Fratanduono, D. E.; Haan, S. W.; Le Pape, S.; Meezan, N. B.; Moore, A. S.; Moody, J. D.; Ralph, J. E.; Ross, J. S.; Rygg, J. R.; Thomas, C.; Turnbull, D. P.; Wild, C.; Eggert, J. H.

2018-04-01

Fine-grained diamond, or high-density carbon (HDC), is being used as an ablator for inertial confinement fusion (ICF) research at the National Ignition Facility (NIF). Accurate equation of state (EOS) knowledge over a wide range of phase space is critical in the design and analysis of integrated ICF experiments. Here, we report shock and release measurements of the shock impedance mismatch between HDC and liquid deuterium conducted during shock-timing experiments having a first shock in the ablator ranging between 8 and 14 Mbar. Using ultrafast Doppler imaging velocimetry to track the leading shock front, we characterize the shock velocity discontinuity upon the arrival of the shock at the HDC/liquid deuterium interface. Comparing the experimental data with tabular EOS models used to simulate integrated ICF experiments indicates the need for an improved multiphase EOS model for HDC in order to achieve a significant increase in neutron yield in indirect-driven ICF implosions with HDC ablators.

Enhancing Human Responses to Climate Change Risks through Simulated Flooding Experiences

NASA Astrophysics Data System (ADS)

Zaalberg, Ruud; Midden, Cees

Delta areas are threatened by global climate change. The general aims of our research were (1) to increase our understanding of climate and flood risk perceptions and the factors that influence these judgments, and (2) to seek for interventions that can contribute to a realistic assessment by laypersons of long-term flooding risks. We argue that awareness of one's own vulnerability to future flooding and insights into the effectiveness of coping strategies is driven by direct flooding experiences. In the current research multimodal sensory stimulation by means of interactive 3D technology is used to simulate direct flooding experiences at the experiential or sensory level, thereby going beyond traditional persuasion attempts using fear-evoking images. Our results suggest that future communication efforts should not only use these new technologies to transfer knowledge about effective coping strategies and flooding risks, but should especially be directed towards residents living in flood prone areas, but who lack direct flooding experiences as their guiding principle.

Measuring the shock impedance mismatch between high-density carbon and deuterium at the National Ignition Facility

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

Millot, M.; Celliers, P. M.; Sterne, P. A.

Fine-grained diamond, or high-density carbon (HDC), is being used as an ablator for inertial confinement fusion (ICF) research at the National Ignition Facility (NIF). Accurate equation of state (EOS) knowledge over a wide range of phase space is critical in the design and analysis of integrated ICF experiments. Here in this paper, we report shock and release measurements of the shock impedance mismatch between HDC and liquid deuterium conducted during shock-timing experiments having a first shock in the ablator ranging between 8 and 14 Mbar. Using ultrafast Doppler imaging velocimetry to track the leading shock front, we characterize the shockmore » velocity discontinuity upon the arrival of the shock at the HDC/liquid deuterium interface. Comparing the experimental data with tabular EOS models used to simulate integrated ICF experiments indicates the need for an improved multiphase EOS model for HDC in order to achieve a significant increase in neutron yield in indirect-driven ICF implosions with HDC ablators.« less

Neurofibroma involving obturator nerve mimicking an adnexal mass: a rare case report and PRISMA-driven systematic review.

PubMed

Chao, Wei-Ting; Liu, Chia-Hao; Chen, Yi-Jen; Wu, Hua-Hsi; Chuang, Chi-Mu; Wang, Peng-Hui

2018-02-09

Pelvic masses are a common gynecologic problem, and majority of them are diagnosed as ovarian tumors finally. Sometimes, it is hard to distinguish the origin of these pelvic masses. The following case is a solitary neurofibroma arising from the right-side obturator nerve, which was impressed as a right-side ovarian tumor initially. We reported this case, and also performed a PRISMA-driven systematic review to summary the similar cases in the literature. This review includes image, molecular and pathological findings and outcome of neurofibroma. A 33-year-old woman with a regular menstrual period denied any symptoms or signs. During her physical check-up, image examination revealed a right-side heterogeneous pelvic mass; it was suggestive of a complex of right-side ovarian tumor. A provisional diagnosis of retroperitoneal pelvic mass, probably a benign ovarian tumor, was made. Excision of the right-side pelvic mass was performed. We sent the specimens for frozen pathology, which indicated neurofibroma and lipomatous tumor and that the possibility of liposarcoma cannot be excluded. A segment of the obturator nerve was attached to the tumor and was severed. A right-side obturator nerve tear during tumor excision was observed, and a neurosurgeon was consulted for obturator nerve grafting and repair. The patient complained of mild weakness and paresthesia affecting the right leg, and we consulted a rehabilitation doctor for neuron injury. The patient's recovery was uneventful, and she was discharged eight days after the drain was removed. Further rehabilitation treatment was arranged. A neurofibroma is an uncommon pelvic retroperitoneal tumor, and it can be misdiagnosed as an adnexal mass. To our knowledge, this is a rare case of a solitary neurofibroma arising from the obturator nerve. It usually does not have any neurological deficit. We present this case to demonstrate that pelvic neurofibroma can be mistaken for an adnexal mass. This fact should be borne in mind during the diagnosis process.

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

PubMed Central

Nielson, Jessica L.; Cooper, Shelly R.; Sorani, Marco D.; Inoue, Tomoo; Yuh, Esther L.; Mukherjee, Pratik; Petrossian, Tanya C.; Lum, Pek Y.; Lingsma, Hester F.; Gordon, Wayne A.; Okonkwo, David O.; Manley, Geoffrey T.

2017-01-01

Background Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients. Trial Registration ClinicalTrials.gov Identifier NCT01565551 PMID:28257413

Dynamic integral imaging technology for 3D applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Huang, Yi-Pai; Javidi, Bahram; Martínez-Corral, Manuel; Shieh, Han-Ping D.; Jen, Tai-Hsiang; Hsieh, Po-Yuan; Hassanfiroozi, Amir

2017-05-01

Depth and resolution are always the trade-off in integral imaging technology. With the dynamic adjustable devices, the two factors of integral imaging can be fully compensated with time-multiplexed addressing. Those dynamic devices can be mechanical or electrical driven. In this presentation, we will mainly focused on discussing various Liquid Crystal devices which can change the focal length, scan and shift the image position, or switched in between 2D/3D mode. By using the Liquid Crystal devices, dynamic integral imaging have been successfully applied on 3D Display, capturing, and bio-imaging applications.

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

Gang, G; Siewerdsen, J; Stayman, J

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFMmore » objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task-based optimization framework provides a promising approach that maximizes imaging performance under the same total dose constraint.« less

Investigating Non-Equilibrium Fluctuations of Nanocolloids in a Magnetic Field Using Direct Imaging Methods

NASA Astrophysics Data System (ADS)

Rice, Ashley; Oprisan, Ana; Oprisan, Sorinel; Rice-Oprisan College of Charleston Team

Nanoparticles of iron oxide have a high surface area and can be controlled by an external magnetic field. Since they have a fast response to the applied magnetic field, these systems have been used for numerous in vivo applications, such as MRI contrast enhancement, tissue repair, immunoassay, detoxification of biological fluids, hyperthermia, drug delivery, and cell separation. We performed three direct imaging experiments in order to investigate the concentration-driven fluctuations using magnetic nanoparticles in the absence and in the presence of magnetic field. Our direct imaging experimental setup involved a glass cell filled with magnetic nanocolloidal suspension and water with the concentration gradient oriented against the gravitational field and a superluminescent diode (SLD) as the light source. Nonequilibrium concentration-driven fluctuations were recorded using a direct imaging technique. We used a dynamic structure factor algorithm for image processing in order to compute the structure factor and to find the power law exponents. We saw evidence of large concentration fluctuations and permanent magnetism. Further research will use the correlation time to approximate the diffusion coefficient for the free diffusion experiment. Funded by College of Charleston Department of Undergraduate Research and Creative Activities SURF grant.

Real-time and sub-wavelength ultrafast coherent diffraction imaging in the extreme ultraviolet.

PubMed

Zürch, M; Rothhardt, J; Hädrich, S; Demmler, S; Krebs, M; Limpert, J; Tünnermann, A; Guggenmos, A; Kleineberg, U; Spielmann, C

2014-12-08

Coherent Diffraction Imaging is a technique to study matter with nanometer-scale spatial resolution based on coherent illumination of the sample with hard X-ray, soft X-ray or extreme ultraviolet light delivered from synchrotrons or more recently X-ray Free-Electron Lasers. This robust technique simultaneously allows quantitative amplitude and phase contrast imaging. Laser-driven high harmonic generation XUV-sources allow table-top realizations. However, the low conversion efficiency of lab-based sources imposes either a large scale laser system or long exposure times, preventing many applications. Here we present a lensless imaging experiment combining a high numerical aperture (NA = 0.8) setup with a high average power fibre laser driven high harmonic source. The high flux and narrow-band harmonic line at 33.2 nm enables either sub-wavelength spatial resolution close to the Abbe limit (Δr = 0.8λ) for long exposure time, or sub-70 nm imaging in less than one second. The unprecedented high spatial resolution, compactness of the setup together with the real-time capability paves the way for a plethora of applications in fundamental and life sciences.

Temporal dynamics of the knowledge-mediated visual disambiguation process in humans: a magnetoencephalography study.

PubMed

Urakawa, Tomokazu; Ogata, Katsuya; Kimura, Takahiro; Kume, Yuko; Tobimatsu, Shozo

2015-01-01

Disambiguation of a noisy visual scene with prior knowledge is an indispensable task of the visual system. To adequately adapt to a dynamically changing visual environment full of noisy visual scenes, the implementation of knowledge-mediated disambiguation in the brain is imperative and essential for proceeding as fast as possible under the limited capacity of visual image processing. However, the temporal profile of the disambiguation process has not yet been fully elucidated in the brain. The present study attempted to determine how quickly knowledge-mediated disambiguation began to proceed along visual areas after the onset of a two-tone ambiguous image using magnetoencephalography with high temporal resolution. Using the predictive coding framework, we focused on activity reduction for the two-tone ambiguous image as an index of the implementation of disambiguation. Source analysis revealed that a significant activity reduction was observed in the lateral occipital area at approximately 120 ms after the onset of the ambiguous image, but not in preceding activity (about 115 ms) in the cuneus when participants perceptually disambiguated the ambiguous image with prior knowledge. These results suggested that knowledge-mediated disambiguation may be implemented as early as approximately 120 ms following an ambiguous visual scene, at least in the lateral occipital area, and provided an insight into the temporal profile of the disambiguation process of a noisy visual scene with prior knowledge. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Mission Driven Scene Understanding: Dynamic Environments

DTIC Science & Technology

2016-06-01

the Army mission. Then, for example, helpful image cues that relate to mission activities may include time of day, current and future weather...mission.10 In other words, visual saliency also can be used to highlight key image cues that relate to Army mission activities.10 For example, an...to the Army mission. Then, for example, helpful image cues that relate to mission activities may include time of day, current and future weather

An adaptive optics imaging system designed for clinical use.

PubMed

Zhang, Jie; Yang, Qiang; Saito, Kenichi; Nozato, Koji; Williams, David R; Rossi, Ethan A

2015-06-01

Here we demonstrate a new imaging system that addresses several major problems limiting the clinical utility of conventional adaptive optics scanning light ophthalmoscopy (AOSLO), including its small field of view (FOV), reliance on patient fixation for targeting imaging, and substantial post-processing time. We previously showed an efficient image based eye tracking method for real-time optical stabilization and image registration in AOSLO. However, in patients with poor fixation, eye motion causes the FOV to drift substantially, causing this approach to fail. We solve that problem here by tracking eye motion at multiple spatial scales simultaneously by optically and electronically integrating a wide FOV SLO (WFSLO) with an AOSLO. This multi-scale approach, implemented with fast tip/tilt mirrors, has a large stabilization range of ± 5.6°. Our method consists of three stages implemented in parallel: 1) coarse optical stabilization driven by a WFSLO image, 2) fine optical stabilization driven by an AOSLO image, and 3) sub-pixel digital registration of the AOSLO image. We evaluated system performance in normal eyes and diseased eyes with poor fixation. Residual image motion with incremental compensation after each stage was: 1) ~2-3 arc minutes, (arcmin) 2) ~0.5-0.8 arcmin and, 3) ~0.05-0.07 arcmin, for normal eyes. Performance in eyes with poor fixation was: 1) ~3-5 arcmin, 2) ~0.7-1.1 arcmin and 3) ~0.07-0.14 arcmin. We demonstrate that this system is capable of reducing image motion by a factor of ~400, on average. This new optical design provides additional benefits for clinical imaging, including a steering subsystem for AOSLO that can be guided by the WFSLO to target specific regions of interest such as retinal pathology and real-time averaging of registered images to eliminate image post-processing.

About probabilistic integration of ill-posed geophysical tomography and logging data: A knowledge discovery approach versus petrophysical transfer function concepts illustrated using cross-borehole radar-, P- and S-wave traveltime tomography in combination with cone penetration and dielectric logging data

NASA Astrophysics Data System (ADS)

Paasche, Hendrik

2018-01-01

Site characterization requires detailed and ideally spatially continuous information about the subsurface. Geophysical tomographic experiments allow for spatially continuous imaging of physical parameter variations, e.g., seismic wave propagation velocities. Such physical parameters are often related to typical geotechnical or hydrological target parameters, e.g. as achieved from 1D direct push or borehole logging. Here, the probabilistic inference of 2D tip resistance, sleeve friction, and relative dielectric permittivity distributions in near-surface sediments is constrained by ill-posed cross-borehole seismic P- and S-wave and radar wave traveltime tomography. In doing so, we follow a discovery science strategy employing a fully data-driven approach capable of accounting for tomographic ambiguity and differences in spatial resolution between the geophysical tomograms and the geotechnical logging data used for calibration. We compare the outcome to results achieved employing classical hypothesis-driven approaches, i.e., deterministic transfer functions derived empirically for the inference of 2D sleeve friction from S-wave velocity tomograms and theoretically for the inference of 2D dielectric permittivity from radar wave velocity tomograms. The data-driven approach offers maximal flexibility in combination with very relaxed considerations about the character of the expected links. This makes it a versatile tool applicable to almost any combination of data sets. However, error propagation may be critical and justify thinking about a hypothesis-driven pre-selection of an optimal database going along with the risk of excluding relevant information from the analyses. Results achieved by transfer function rely on information about the nature of the link and optimal calibration settings drawn as retrospective hypothesis by other authors. Applying such transfer functions at other sites turns them into a priori valid hypothesis, which can, particularly for empirically derived transfer functions, result in poor predictions. However, a mindful utilization and critical evaluation of the consequences of turning a retrospectively drawn hypothesis into an a priori valid hypothesis can also result in good results for inference and prediction problems when using classical transfer function concepts.

KITAE II: Knowledge Development in Battlespace Helmand

DTIC Science & Technology

2011-06-01

Sergeant Andrew James Jones 18-09-2010 Private Simon Mundt Jørgensen 22-09-2010 Corporal Matthew Thomas 25-09-2010 Rifleman Suraj Gurung 02-10-2010...targeting driven. See Mattis (2008); For philosophical foundation see Smith (2005, 2006); Nicholson (2006);Mitchell (2004); and a doctrinal...BATTLESPACE IS THE KNOWLEDGE BASE HUMINT 1 SIGINT1 OSINT BIO IMINT 1 SIGINT 2 PATROLS HUMINT 2 REACHBACK IMINT 2 Sources OTHER… Actionable Assets Organic

"Bad for the Penguins ... because They Need Ice and that to Live On": An Exploratory Study into the Environmental Views, Concerns and Knowledge of Socially Disadvantaged Young People

ERIC Educational Resources Information Center

Wilson, Sarah Jane; Snell, Carolyn

2010-01-01

Environmental policies and practices have maintained a high status internationally, nationally and locally, but limited literature relates to the perspective of social disadvantage in England, with a particular under-representation of young people. The research presented in this paper has been driven by the supposition that a lack of knowledge and…

Adaptation of reference volumes for correlation-based digital holographic particle tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Peinke, Joachim; Gülker, Gerd

2018-04-01

Numerically reconstructed reference volumes tailored to particle images are used for particle position detection by means of three-dimensional correlation. After a first tracking of these positions, the experimentally recorded particle images are retrieved as a posteriori knowledge about the particle images in the system. This knowledge is used for a further refinement of the detected positions. A transparent description of the individual algorithm steps including the results retrieved with experimental data complete the paper. The work employs extraordinarily small particles, smaller than the pixel pitch of the camera sensor. It is the first approach known to the authors that combines numerical knowledge about particle images and particle images retrieved from the experimental system to an iterative particle tracking approach for digital holographic particle tracking velocimetry.

An integrated measure of display clutter based on feature content, user knowledge and attention allocation factors.

PubMed

Pankok, Carl; Kaber, David B

2018-05-01

Existing measures of display clutter in the literature generally exhibit weak correlations with task performance, which limits their utility in safety-critical domains. A literature review led to formulation of an integrated display data- and user knowledge-driven measure of display clutter. A driving simulation experiment was conducted in which participants were asked to search 'high' and 'low' clutter displays for navigation information. Data-driven measures and subjective perceptions of clutter were collected along with patterns of visual attention allocation and driving performance responses during time periods in which participants searched the navigation display for information. The new integrated measure was more strongly correlated with driving performance than other, previously developed measures of clutter, particularly in the case of low-clutter displays. Integrating display data and user knowledge factors with patterns of visual attention allocation shows promise for measuring display clutter and correlation with task performance, particularly for low-clutter displays. Practitioner Summary: A novel measure of display clutter was formulated, accounting for display data content, user knowledge states and patterns of visual attention allocation. The measure was evaluated in terms of correlations with driver performance in a safety-critical driving simulation study. The measure exhibited stronger correlations with task performance than previously defined measures.

Does the transition to an active-learning environment for the introductory course reduce students' overall knowledge of the various disciplines in biology?

PubMed

Simurda, Maryanne C

2012-01-01

As biology education is being redesigned toward an interdisciplinary focus and as pedagogical trends move toward active-learning strategies and investigative experiences, a restructuring of the course content for the Introductory Biology course is necessary. The introductory course in biology has typically been a survey of all the biosciences. If the total number of topics covered is reduced, is the students' overall knowledge of biology also reduced? Our introductory course has been substantially modified away from surveying the biological sciences and toward providing a deep understanding of a particular biological topic, as well as focusing on developing students' analytical and communication skills. Because of this shift to a topic-driven approach for the introductory course, we were interested in assessing our graduating students' overall knowledge of the various biological disciplines. Using the Major Field Test - Biology (Educational Testing Service (ETS), Princeton, NJ), we compared the test performance of graduating students who had a traditional lecture-based introductory course to those who had a topic-driven active-learning introductory course. Our results suggest that eliminating the traditional survey of biology and, instead, focusing on quantitative and writing skills at the introductory level do not affect our graduating students' overall breadth of knowledge of the various biosciences.

Image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

Predictive Models and Computational Embryology

EPA Science Inventory

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

Shock Compression Induced Hot Spots in Energetic Material Detected by Thermal Imaging Microscopy

NASA Astrophysics Data System (ADS)

Chen, Ming-Wei; Dlott, Dana

2014-06-01

The chemical reaction of powder energetic material is of great interest in energy and pyrotechnic applications since the high reaction temperature. Under the shock compression, the chemical reaction appears in the sub-microsecond to microsecond time scale, and releases a large amount of energy. Experimental and theoretical research progresses have been made in the past decade, in order to characterize the process under the shock compression. However, the knowledge of energy release and temperature change of this procedure is still limited, due to the difficulties of detecting technologies. We have constructed a thermal imaging microscopy apparatus, and studied the temperature change in energetic materials under the long-wavelength infrared (LWIR) and ultrasound exposure. Additionally, the real-time detection of the localized heating and energy concentration in composite material is capable with our thermal imaging microscopy apparatus. Recently, this apparatus is combined with our laser driven flyer plate system to provide a lab-scale source of shock compression to energetic material. A fast temperature increase of thermite particulars induced by the shock compression is directly observed by thermal imaging with 15-20 μm spatial resolution. Temperature change during the shock loading is evaluated to be at the order of 10^9K/s, through the direct measurement of mid-wavelength infrared (MWIR) emission intensity change. We observe preliminary results to confirm the hot spots appear with shock compression on energetic crystals, and will discuss the data and analysis in further detail. M.-W. Chen, S. You, K. S. Suslick, and D. D. Dlott, {Rev. Sci. Instr., 85, 023705 (2014) M.-W. Chen, S. You, K. S. Suslick, and D. D. Dlott, {Appl. Phys. Lett., 104, 061907 (2014)} K. E. Brown, W. L. Shaw, X. Zheng, and D. D. Dlott, {Rev. Sci. Instr., 83, 103901 (2012)}

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Explosively Driven Particle Fields Imaged Using a High-Speed Framing Camera and Particle Image Velocimetry

DTIC Science & Technology

2011-08-01

inert steel particles and by Frost et al. (2005, 2007) with reactive aluminum and magnesium particles. All used sensitized nitromethane and were...particles in a spherical or cylindrical charge case was used with sensitized nitromethane . Frost et al. (2002), determined that for a given charge

Making Microscopy Motivating, Memorable, & Manageable for Undergraduate Students with Digital Imaging Laboratories

ERIC Educational Resources Information Center

Weeks, Andrea; Bachman. Beverly; Josway, Sarah; North, Brittany; Tsuchiya, Mirian T.N.

2013-01-01

Microscopy and precise observation are essential skills that are challenging to teach effectively to large numbers of undergraduate biology students. We implemented student-driven digital imaging assignments for microscopy in a large enrollment laboratory for organismal biology. We detail how we promoted student engagement with the material and…

Imaging and spectroscopy of copper dopant migration of indirectly driven Beryllium capsule implosion on the National Ignition Facility

NASA Astrophysics Data System (ADS)

Kyrala, George; Zylstra, A.; Yi, S. A.; Klline, J. L.; Shah, R. C.; Lopez, F. E.; Batha, S. A.; Doppner, T.; Thorn, D. B.; MacLaren, S.; Masters, N.; Callahan, D.; Hurricane, O.; Rice, N.; Huang, H.; Krauland, C. M.; MacDonald, M.

2017-10-01

Using beryllium, as an ablator material for indirectly driven inertial fusion, requires the use of a Copper dopant to block preheat from the hohlraum M-band radiation. However, due to the microstructure and imperfections of the capsule, some of the copper may be injected into the core of the implosion, affecting the yield and performance. Alternatively, the copper dopant may blow into the ablated plasma affecting the hohlraum performance as well. We will present some of data on time integrated imaging of the copper dopant into the core of the capsule using either the 2-dimensional multiple monochromatic imaging of the implosion, as well as the 1D spectrally resolved imaging of the copper dopant emission. In either case we found that the copper did migrate to the hot core, while fewer copper ions ablated into the hohlraum. This work performed under the auspices of the U.S. DOE by LANL under contract DE-AC52-06NA25396, and by LLNL under Contract DE-AC52-07NA27344.

User-Driven Sampling Strategies in Image Exploitation

DOE PAGES

Harvey, Neal R.; Porter, Reid B.

2013-12-23

Visual analytics and interactive machine learning both try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human-computer interaction. This paper focuses on one aspect of the human-computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteration, we investigate situations where the user selects which data is to be labeled at each iteration. User-drivenmore » sampling strategies can emerge in many visual analytics applications but they have not been fully developed in machine learning. We discovered that in user-driven sampling strategies suggest new theoretical and practical research questions for both visualization science and machine learning. In this paper we identify and quantify the potential benefits of these strategies in a practical image analysis application. We find user-driven sampling strategies can sometimes provide significant performance gains by steering tools towards local minima that have lower error than tools trained with all of the data. Furthermore, in preliminary experiments we find these performance gains are particularly pronounced when the user is experienced with the tool and application domain.« less

Light-driven solute transport in Halobacterium halobium

NASA Technical Reports Server (NTRS)

Lanyi, J. K.

1979-01-01

The cell membrane of Halobacterium halobium exhibits differential regions which contain crystalline arrays of a single kind of protein, termed bacteriorhodopsin. This bacterial retinal-protein complex resembles the visual pigment and, after the absorption of protons, translocates H(+) across the cell membrane, leading to an electrochemical gradient for protons between the inside and the outside of the cell. Thus, light is an alternate source of energy in these bacteria, in addition to terminal oxidation. The paper deals with work on light-driven transport in H. halobium with cell envelope vesicles. The discussion covers light-driven movements of H(+), Na(+), and K(+); light-driven amino acid transport; and apparent allosteric control of amino acid transport. The scheme of energy coupling in H. halobium vesicles appears simple, its quantitative details are quite complex and reveal regulatory phenomena. More knowledge is required of the way the coupling components are regulated by the ion gradients present.

Real-time divergent evolution in plants driven by pollinators

PubMed Central

Gervasi, Daniel D. L.; Schiestl, Florian P

2017-01-01

Pollinator-driven diversification is thought to be a major source of floral variation in plants. Our knowledge of this process is, however, limited to indirect assessments of evolutionary changes. Here, we employ experimental evolution with fast cycling Brassica rapa plants to demonstrate adaptive evolution driven by different pollinators. Our study shows pollinator-driven divergent selection as well as divergent evolution in plant traits. Plants pollinated by bumblebees evolved taller size and more fragrant flowers with increased ultraviolet reflection. Bumblebees preferred bumblebee-pollinated plants over hoverfly-pollinated plants at the end of the experiment, showing that plants had adapted to the bumblebees' preferences. Plants with hoverfly pollination became shorter, had reduced emission of some floral volatiles, but increased fitness through augmented autonomous self-pollination. Our study demonstrates that changes in pollinator communities can have rapid consequences on the evolution of plant traits and mating system. PMID:28291771

A knowledge-based system for patient image pre-fetching in heterogeneous database environments--modeling, design, and evaluation.

PubMed

Wei, C P; Hu, P J; Sheng, O R

2001-03-01

When performing primary reading on a newly taken radiological examination, a radiologist often needs to reference relevant prior images of the same patient for confirmation or comparison purposes. Support of such image references is of clinical importance and may have significant effects on radiologists' examination reading efficiency, service quality, and work satisfaction. To effectively support such image reference needs, we proposed and developed a knowledge-based patient image pre-fetching system, addressing several challenging requirements of the application that include representation and learning of image reference heuristics and management of data-intensive knowledge inferencing. Moreover, the system demands an extensible and maintainable architecture design capable of effectively adapting to a dynamic environment characterized by heterogeneous and autonomous data source systems. In this paper, we developed a synthesized object-oriented entity- relationship model, a conceptual model appropriate for representing radiologists' prior image reference heuristics that are heuristic oriented and data intensive. We detailed the system architecture and design of the knowledge-based patient image pre-fetching system. Our architecture design is based on a client-mediator-server framework, capable of coping with a dynamic environment characterized by distributed, heterogeneous, and highly autonomous data source systems. To adapt to changes in radiologists' patient prior image reference heuristics, ID3-based multidecision-tree induction and CN2-based multidecision induction learning techniques were developed and evaluated. Experimentally, we examined effects of the pre-fetching system we created on radiologists' examination readings. Preliminary results show that the knowledge-based patient image pre-fetching system more accurately supports radiologists' patient prior image reference needs than the current practice adopted at the study site and that radiologists may become more efficient, consultatively effective, and better satisfied when supported by the pre-fetching system than when relying on the study site's pre-fetching practice.

Parental knowledge is an environmental influence on adolescent externalizing.

PubMed

Marceau, Kristine; Narusyte, Jurgita; Lichtenstein, Paul; Ganiban, Jody M; Spotts, Erica L; Reiss, David; Neiderhiser, Jenae M

2015-02-01

There is evidence both that parental monitoring is an environmental influence serving to diminish adolescent externalizing problems and that this association may be driven by adolescents' characteristics via genetic and/or environmental mechanisms, such that adolescents with fewer problems tell their parents more, and therefore appear to be better monitored. Without information on how parents' and children's genes and environments influence correlated parent and child behaviors, it is impossible to clarify the mechanisms underlying this association. The present study used the Extended Children of Twins model to distinguish types of gene-environment correlation and direct environmental effects underlying associations between parental knowledge and adolescent (age 11-22 years) externalizing behavior with a Swedish sample of 909 twin parents and their adolescent offspring and a US-based sample of 405 White adolescent siblings and their parents. Results suggest that more parental knowledge is associated with less adolescent externalizing via a direct environmental influence independent of any genetic influences. There was no evidence of a child-driven explanation of the association between parental knowledge and adolescent externalizing problems. In this sample of adolescents, parental knowledge exerted an environmental influence on adolescent externalizing after accounting for genetic influences of parents and adolescents. Because the association between parenting and child development originates in the parent, treatment for adolescent externalizing must not only include parents but should also focus on altering their parental style. Thus, findings suggest that teaching parents better knowledge-related monitoring strategies is likely to help reduce externalizing problems in adolescents. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

Parental Knowledge is an Environmental Influence on Adolescent Externalizing

PubMed Central

Marceau, Kristine; Narusyte, Jurgita; Lichtenstein, Paul; Ganiban, Jody M.; Spotts, Erica L.; Reiss, David; Neiderhiser, Jenae M.

2014-01-01

Background There is evidence both that parental monitoring is an environmental influence serving to diminish adolescent externalizing problems and that this association may be driven by adolescents’ characteristics via genetic and/or environmental mechanisms, such that adolescents with fewer problems tell their parents more, and therefore appear to be better monitored. Without information on how parents’ and children’s genes and environments influence correlated parent and child behaviors, it is impossible to clarify the mechanisms underlying this association. Method The present study used the Extended Children of Twins model to distinguish types of gene-environment correlation and direct environmental effects underlying associations between parental knowledge and adolescent (age 11-22 years) externalizing behavior with a Swedish sample of 909 twin parents and their adolescent offspring and a US-based sample of 405 White adolescent siblings and their parents. Results Results suggest that more parental knowledge is associated with less adolescent externalizing via a direct environmental influence independent of any genetic influences. There was no evidence of a child-driven explanation of the association between parental knowledge and adolescent externalizing problems. Conclusions In this sample of adolescents, parental knowledge exerted an environmental influence on adolescent externalizing after accounting for genetic influences of parents and adolescents. Because the association between parenting and child development originates in the parent, treatment for adolescent externalizing must not only include parents but should focus on altering their parental style. Thus, findings suggest that teaching parents better knowledge-related monitoring strategies is likely to help reduce externalizing problems in adolescents. PMID:24975929

Event-Driven Random-Access-Windowing CCD Imaging System

NASA Technical Reports Server (NTRS)

Monacos, Steve; Portillo, Angel; Ortiz, Gerardo; Alexander, James; Lam, Raymond; Liu, William

2004-01-01

A charge-coupled-device (CCD) based high-speed imaging system, called a realtime, event-driven (RARE) camera, is undergoing development. This camera is capable of readout from multiple subwindows [also known as regions of interest (ROIs)] within the CCD field of view. Both the sizes and the locations of the ROIs can be controlled in real time and can be changed at the camera frame rate. The predecessor of this camera was described in High-Frame-Rate CCD Camera Having Subwindow Capability (NPO- 30564) NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 26. The architecture of the prior camera requires tight coupling between camera control logic and an external host computer that provides commands for camera operation and processes pixels from the camera. This tight coupling limits the attainable frame rate and functionality of the camera. The design of the present camera loosens this coupling to increase the achievable frame rate and functionality. From a host computer perspective, the readout operation in the prior camera was defined on a per-line basis; in this camera, it is defined on a per-ROI basis. In addition, the camera includes internal timing circuitry. This combination of features enables real-time, event-driven operation for adaptive control of the camera. Hence, this camera is well suited for applications requiring autonomous control of multiple ROIs to track multiple targets moving throughout the CCD field of view. Additionally, by eliminating the need for control intervention by the host computer during the pixel readout, the present design reduces ROI-readout times to attain higher frame rates. This camera (see figure) includes an imager card consisting of a commercial CCD imager and two signal-processor chips. The imager card converts transistor/ transistor-logic (TTL)-level signals from a field programmable gate array (FPGA) controller card. These signals are transmitted to the imager card via a low-voltage differential signaling (LVDS) cable assembly. The FPGA controller card is connected to the host computer via a standard peripheral component interface (PCI).

Active vision and image/video understanding with decision structures based on the network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2003-08-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.

PubMed

Gurcan, Metin N; Tomaszewski, John; Overton, James A; Doyle, Scott; Ruttenberg, Alan; Smith, Barry

2017-02-01

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts. Copyright © 2016 Elsevier Inc. All rights reserved.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Enhancing Ground Based Telescope Performance with Image Processing

DTIC Science & Technology

2013-11-13

driven by the need to detect small faint objects with relatively short integration times to avoid streaking of the satellite image across multiple...the time right before the eclipse. The orbital elements of the satellite were entered into the SST’s tracking system, so that the SST could be...short integration times , thereby avoiding streaking of the satellite image across multiple CCD pixels so that the objects are suitably modeled as point

Data-driven development of AOP knowledge

EPA Science Inventory

The Adverse Outcome Pathway framework represents a systematic way to organize mechanistic information underlying toxicology, and it is specifically designed to connect early stage molecular perturbations by chemicals and other stressors with adverse outcomes in humans and wildlif...

From the Director: The Joy of Science, the Courage of Research

MedlinePlus

... Dr. Zerhouni , one that combines an appreciation of biological complexity with the fearless search for scientific knowledge. ... techniques for greater understanding of the complexity of biological systems. The one thing that has driven my ...

Predictive Models and Computational Toxicology (II IBAMTOX)

EPA Science Inventory

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

X-ray Thomson scattering measurements from hohlraum-driven spheres on the OMEGA laser [X-ray Thomson scattering measurements from hohlraum targets on the OMEGA laser

DOE PAGES

Saunders, A. M.; Jenei, A.; Doppner, T.; ...

2016-08-30

X-ray Thomson scattering (XRTS) is a powerful diagnostic for probing warm and hot dense matter. We present the design and results of the first XRTS experiments with hohlraum-driven CH 2 targets on the OMEGA laser. X-rays seen directly from the XRTS x-ray source overshadow the elastic scattering signal from the target capsule, but can be controlled in future experiments. From the inelastic scattering signal, an average plasma temperature is inferred that is in reasonable agreement with the temperatures predicted by simulations. Here, knowledge gained in this experiment show a promising future for further XRTS measurements on indirectly driven OMEGA targets.

X-ray Thomson scattering measurements from hohlraum-driven spheres on the OMEGA laser [X-ray Thomson scattering measurements from hohlraum targets on the OMEGA laser

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

Saunders, A. M.; Jenei, A.; Doppner, T.

X-ray Thomson scattering (XRTS) is a powerful diagnostic for probing warm and hot dense matter. We present the design and results of the first XRTS experiments with hohlraum-driven CH 2 targets on the OMEGA laser. X-rays seen directly from the XRTS x-ray source overshadow the elastic scattering signal from the target capsule, but can be controlled in future experiments. From the inelastic scattering signal, an average plasma temperature is inferred that is in reasonable agreement with the temperatures predicted by simulations. Here, knowledge gained in this experiment show a promising future for further XRTS measurements on indirectly driven OMEGA targets.

Imaging and the new biology: What's wrong with this picture?

NASA Astrophysics Data System (ADS)

Vannier, Michael W.

2004-05-01

The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement. Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely understood type. Imaging creates another form of biological information, providing the ability to study morphology, growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale. The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and other "-ome's." To date, the imaging science community has not set a high priority on the unification of their results with genomics, proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of biological data, impairing our ability to conceive and address many fundamental questions in research and clinical practice. This presentation will explain the challenge of biological knowledge integration in basic research and clinical applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the imaging community, and mainstream of new and future biological science will be identified, so the critical and immediate need for change can be highlighted.

Application of statistical mining in healthcare data management for allergic diseases

NASA Astrophysics Data System (ADS)

Wawrzyniak, Zbigniew M.; Martínez Santolaya, Sara

2014-11-01

The paper aims to discuss data mining techniques based on statistical tools in medical data management in case of long-term diseases. The data collected from a population survey is the source for reasoning and identifying disease processes responsible for patient's illness and its symptoms, and prescribing a knowledge and decisions in course of action to correct patient's condition. The case considered as a sample of constructive approach to data management is a dependence of allergic diseases of chronic nature on some symptoms and environmental conditions. The knowledge summarized in a systematic way as accumulated experience constitutes to an experiential simplified model of the diseases with feature space constructed of small set of indicators. We have presented the model of disease-symptom-opinion with knowledge discovery for data management in healthcare. The feature is evident that the model is purely data-driven to evaluate the knowledge of the diseases` processes and probability dependence of future disease events on symptoms and other attributes. The example done from the outcomes of the survey of long-term (chronic) disease shows that a small set of core indicators as 4 or more symptoms and opinions could be very helpful in reflecting health status change over disease causes. Furthermore, the data driven understanding of the mechanisms of diseases gives physicians the basis for choices of treatment what outlines the need of data governance in this research domain of discovered knowledge from surveys.

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models.

PubMed

Nazem-Zadeh, Mohammad-Reza; Elisevich, Kost V; Schwalb, Jason M; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Soltanian-Zadeh, Hamid

2014-12-15

Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment. Copyright © 2014 Elsevier B.V. All rights reserved.

Challenges and complexities of multifrequency atomic force microscopy in liquid environments.

PubMed

Solares, Santiago D

2014-01-01

This paper illustrates through numerical simulation the complexities encountered in high-damping AFM imaging, as in liquid enviroments, within the specific context of multifrequency atomic force microscopy (AFM). The focus is primarily on (i) the amplitude and phase relaxation of driven higher eigenmodes between successive tip-sample impacts, (ii) the momentary excitation of non-driven higher eigenmodes and (iii) base excitation artifacts. The results and discussion are mostly applicable to the cases where higher eigenmodes are driven in open loop and frequency modulation within bimodal schemes, but some concepts are also applicable to other types of multifrequency operations and to single-eigenmode amplitude and frequency modulation methods.

A system for the real-time display of radar and video images of targets

NASA Technical Reports Server (NTRS)

Allen, W. W.; Burnside, W. D.

1990-01-01

Described here is a software and hardware system for the real-time display of radar and video images for use in a measurement range. The main purpose is to give the reader a clear idea of the software and hardware design and its functions. This system is designed around a Tektronix XD88-30 graphics workstation, used to display radar images superimposed on video images of the actual target. The system's purpose is to provide a platform for tha analysis and documentation of radar images and their associated targets in a menu-driven, user oriented environment.

Table-driven image transformation engine algorithm

NASA Astrophysics Data System (ADS)

Shichman, Marc

1993-04-01

A high speed image transformation engine (ITE) was designed and a prototype built for use in a generic electronic light table and image perspective transformation application code. The ITE takes any linear transformation, breaks the transformation into two passes and resamples the image appropriately for each pass. The system performance is achieved by driving the engine with a set of look up tables computed at start up time for the calculation of pixel output contributions. Anti-aliasing is done automatically in the image resampling process. Operations such as multiplications and trigonometric functions are minimized. This algorithm can be used for texture mapping, image perspective transformation, electronic light table, and virtual reality.

NOUS: Construction and Querying of Dynamic Knowledge Graphs

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

Choudhury, Sutanay; Agarwal, Khushbu; Purohit, Sumit

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a trans- formative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowl- edge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queriesmore » where the answer is embedded across multiple data sources.« less

Corkscrew Structures and Precessing Jets

NASA Astrophysics Data System (ADS)

Sahai, Raghvendra

2005-07-01

Collimated jets are one of the most intriguing, yet poorly understood phenomena in astrophysics. Jets have been found in a wide variety of object classes which include AGNs, YSOs, massive X-ray binaries {e.g. SS433}, black hole X-ray transients, symbiotic stars, supersoft X-ray sources, and finally, planetary and preplanetary nebulae {PNs & PPNs}. In the case of PNs and PPNs, we have propsoed that wobbling collimated jets are the universal mechanism which can shape the wide variety of bipolar and multipolar morphologies seen in these objects. Most of our knowledge of post-AGB jets is indirectly inferred from their effects on the circumstellar envelopes of the progenitor AGB stars and, for that reason, these jets remain very poorly understood. Thus the mechanism that powers and collimates these jet-like post-AGB outflows remains as one of the most important, unsolved issues in post-AGB evolution. We propose an archival study of two bipolar PPNs, motivated by two recent discoveries which indicate that precessing jets are likely to be operational in them, and that the properties of the jets and the bipolar lobes produced by them, may be directly measured. One of these is IRAS16342-3814 {IRAS1634}, previously imaged with WPFC2, in which new Adaptive Optics {AO} observations at near-IR wavelengths show a remarkable corkscrew-shaped structure, the tell-tale signature of a precessing jet. Inspection of WFPC2 images of another PPN, OH231.8+4.2 in which we have recently discovered a A-type companion to the central mass-losing star, shows a sinuous nebulosity in a broad-band continuum image, resembling a corkscrew structure. We will use the latter to constrain the phsyical properties of the jet {precession period, opening angle, jet beam diameter, temporal history} in OH231.8. Using the multi-wavelength data on both sources, we will build models of the density distribution of the lobes and their interiors. In the case of IRAS1634, these models will be used to investigate the hypothesis that the HST images do not show the corkscrew structure because of opacity effects. Under the assumption that the jets are driven by an accretion disk around the companion, we will use theoretical relationships between disk precession and binary rotation period to estimate the properties of the binary {period, separation}. The results of this study will provide quantitative constraints for jet-driven shaping of PNs and inspire new models for the launching of jets from accretion disks in dying stars with binary companions.

Fault Diagnosis in HVAC Chillers

NASA Technical Reports Server (NTRS)

Choi, Kihoon; Namuru, Setu M.; Azam, Mohammad S.; Luo, Jianhui; Pattipati, Krishna R.; Patterson-Hine, Ann

2005-01-01

Modern buildings are being equipped with increasingly sophisticated power and control systems with substantial capabilities for monitoring and controlling the amenities. Operational problems associated with heating, ventilation, and air-conditioning (HVAC) systems plague many commercial buildings, often the result of degraded equipment, failed sensors, improper installation, poor maintenance, and improperly implemented controls. Most existing HVAC fault-diagnostic schemes are based on analytical models and knowledge bases. These schemes are adequate for generic systems. However, real-world systems significantly differ from the generic ones and necessitate modifications of the models and/or customization of the standard knowledge bases, which can be labor intensive. Data-driven techniques for fault detection and isolation (FDI) have a close relationship with pattern recognition, wherein one seeks to categorize the input-output data into normal or faulty classes. Owing to the simplicity and adaptability, customization of a data-driven FDI approach does not require in-depth knowledge of the HVAC system. It enables the building system operators to improve energy efficiency and maintain the desired comfort level at a reduced cost. In this article, we consider a data-driven approach for FDI of chillers in HVAC systems. To diagnose the faults of interest in the chiller, we employ multiway dynamic principal component analysis (MPCA), multiway partial least squares (MPLS), and support vector machines (SVMs). The simulation of a chiller under various fault conditions is conducted using a standard chiller simulator from the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE). We validated our FDI scheme using experimental data obtained from different types of chiller faults.

Ethical Considerations of Children's Digital Image-Making and Image-Audiancing in Early Childhood Environments

ERIC Educational Resources Information Center

Eckhoff, Angela

2015-01-01

This research examines a multi-year investigation of preschoolers' experiences participating in a media-driven exploration of informal play experiences as a means to engage children as artists, researchers, and documenters of their own worlds. In this writing, I will explore the ethical issues that arise for adult researchers engaged in…

Rule-driven defect detection in CT images of hardwood logs

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt

2000-01-01

This paper deals with automated detection and identification of internal defects in hardwood logs using computed tomography (CT) images. We have developed a system that employs artificial neural networks to perform tentative classification of logs on a pixel-by-pixel basis. This approach achieves a high level of classification accuracy for several hardwood species (...

Body image, weight management behavior, nutritional knowledge and dietary habits in high school boys in Korea and China.

PubMed

Hyun, Hwajin; Lee, Hongmie; Ro, Yoona; Gray, Heewon L; Song, Kyunghee

2017-01-01

Adolescence is an important period with rapid physical growth transitioning from childhood to adulthood. Distorted body image can result in eating disorders or inadequate nutrient intakes in adolescence. Limited research has been done with high school boys in both Korea and China. To examine body image, weight control behaviors, nutritional knowledge, and dietary habits in Korean and Chinese teenage boys, and to evaluate any differences in these measures between two countries. High school boys in Yongin of Korea and Weihai region of China (n=201 Korean and n=196 Chinese) participated in a selfreport survey. A previously validated questionnaire assessed height and weight, body image, nutritional knowledge, and dietary habits. Descriptive statistics, t-test, Chi-square, and Pearson correlations were used for data analysis. About 41.4% of Korean students and 40.8% of Chinese students desired to be thinner. The majority of the students from both countries showed a perception gap between ideal body image and current body image. Korean students had a higher frequency of weight control attempts compared with Chinese students (p=0.004). Overall, Korean students had higher scores in nutritional knowledge (p<0.001), while Chinese students had higher scores in dietary habits (p<0.001). Nutrition knowledge in Korean students and dietary habit in Chinese students showed positive correlation with body shape satisfaction (p<0.01). The findings of this study support that developing proper body image among high school boys is important in Korea and China. Different educational strategies might be beneficial to Korean or Chinese students.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

PubMed

DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

Measuring implosion velocities in experiments and simulations of laser-driven cylindrical implosions on the OMEGA laser

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

Hansen, E. C.; Barnak, D. H.; Betti, R.

Laser-driven magnetized liner inertial fusion (MagLIF) on OMEGA involves cylindrical implosions, a preheat beam, and an applied magnetic field. Initial experiments excluded the preheat beam and magnetic field to better characterize the implosion. X-ray self-emission as measured by framing cameras was used to determine the shell trajectory. The 1-D code LILAC was used to model the central region of the implosion, and results were compared to 2-D simulations from the HYDRA code. Post-processing of simulation output with SPECT3D and Yorick produced synthetic x-ray images that were used to compare the simulation results with the x-ray framing camera data. Quantitative analysismore » shows that higher measured neutron yields correlate with higher implosion velocities. The future goal is to further analyze the x-ray images to characterize the uniformity of the implosions and apply these analysis techniques to integrated laser-driven MagLIF shots to better understand the effects of preheat and the magnetic field.« less

Measuring implosion velocities in experiments and simulations of laser-driven cylindrical implosions on the OMEGA laser

DOE PAGES

Hansen, E. C.; Barnak, D. H.; Betti, R.; ...

2018-04-04

Laser-driven magnetized liner inertial fusion (MagLIF) on OMEGA involves cylindrical implosions, a preheat beam, and an applied magnetic field. Initial experiments excluded the preheat beam and magnetic field to better characterize the implosion. X-ray self-emission as measured by framing cameras was used to determine the shell trajectory. The 1-D code LILAC was used to model the central region of the implosion, and results were compared to 2-D simulations from the HYDRA code. Post-processing of simulation output with SPECT3D and Yorick produced synthetic x-ray images that were used to compare the simulation results with the x-ray framing camera data. Quantitative analysismore » shows that higher measured neutron yields correlate with higher implosion velocities. The future goal is to further analyze the x-ray images to characterize the uniformity of the implosions and apply these analysis techniques to integrated laser-driven MagLIF shots to better understand the effects of preheat and the magnetic field.« less

A data-driven approach for quality assessment of radiologic interpretations.

PubMed

Hsu, William; Han, Simon X; Arnold, Corey W; Bui, Alex At; Enzmann, Dieter R

2016-04-01

Given the increasing emphasis on delivering high-quality, cost-efficient healthcare, improved methodologies are needed to measure the accuracy and utility of ordered diagnostic examinations in achieving the appropriate diagnosis. Here, we present a data-driven approach for performing automated quality assessment of radiologic interpretations using other clinical information (e.g., pathology) as a reference standard for individual radiologists, subspecialty sections, imaging modalities, and entire departments. Downstream diagnostic conclusions from the electronic medical record are utilized as "truth" to which upstream diagnoses generated by radiology are compared. The described system automatically extracts and compares patient medical data to characterize concordance between clinical sources. Initial results are presented in the context of breast imaging, matching 18 101 radiologic interpretations with 301 pathology diagnoses and achieving a precision and recall of 84% and 92%, respectively. The presented data-driven method highlights the challenges of integrating multiple data sources and the application of information extraction tools to facilitate healthcare quality improvement. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Laser-ablation-based ion source characterization and manipulation for laser-driven ion acceleration

NASA Astrophysics Data System (ADS)

Sommer, P.; Metzkes-Ng, J.; Brack, F.-E.; Cowan, T. E.; Kraft, S. D.; Obst, L.; Rehwald, M.; Schlenvoigt, H.-P.; Schramm, U.; Zeil, K.

2018-05-01

For laser-driven ion acceleration from thin foils (∼10 μm–100 nm) in the target normal sheath acceleration regime, the hydro-carbon contaminant layer at the target surface generally serves as the ion source and hence determines the accelerated ion species, i.e. mainly protons, carbon and oxygen ions. The specific characteristics of the source layer—thickness and relevant lateral extent—as well as its manipulation have both been investigated since the first experiments on laser-driven ion acceleration using a variety of techniques from direct source imaging to knife-edge or mesh imaging. In this publication, we present an experimental study in which laser ablation in two fluence regimes (low: F ∼ 0.6 J cm‑2, high: F ∼ 4 J cm‑2) was applied to characterize and manipulate the hydro-carbon source layer. The high-fluence ablation in combination with a timed laser pulse for particle acceleration allowed for an estimation of the relevant source layer thickness for proton acceleration. Moreover, from these data and independently from the low-fluence regime, the lateral extent of the ion source layer became accessible.

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

NASA Astrophysics Data System (ADS)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

Specific in vivo labeling with GFP retroviruses, lentiviruses, and adenoviruses for imaging

NASA Astrophysics Data System (ADS)

Hoffman, Robert M.; Kishimoto, Hiroyuki; Fujiwara, Toshiyoshi

2008-02-01

Fluorescent proteins have revolutionized the field of imaging. Our laboratory pioneered in vivo imaging with fluorescent proteins. Fluorescent proteins have enabled imaging at the subcellular level in mice. We review here the use of different vectors carrying fluorescent proteins to selectively label normal and tumor tissue in vivo. We show that a GFP retrovirus and telomerase-driven GFP adenovirus can selectively label tumors in mice. We also show that a GFP lentivirus can selectively label the liver in mice. The practical application of these results are discussed.

Hybrid reflecting objectives for functional multiphoton microscopy in turbid media

PubMed Central

Vučinić, Dejan; Bartol, Thomas M.; Sejnowski, Terrence J.

2010-01-01

Most multiphoton imaging of biological specimens is performed using microscope objectives optimized for high image quality under wide-field illumination. We present a class of objectives designed de novo without regard for these traditional constraints, driven exclusively by the needs of fast multiphoton imaging in turbid media: the delivery of femtosecond pulses without dispersion and the efficient collection of fluorescence. We model the performance of one such design optimized for a typical brain-imaging setup and show that it can greatly outperform objectives commonly used for this task. PMID:16880851

Are we at a crossroads or a plateau? Radiomics and machine learning in abdominal oncology imaging.

PubMed

Summers, Ronald M

2018-05-05

Advances in radiomics and machine learning have driven a technology boom in the automated analysis of radiology images. For the past several years, expectations have been nearly boundless for these new technologies to revolutionize radiology image analysis and interpretation. In this editorial, I compare the expectations with the realities with particular attention to applications in abdominal oncology imaging. I explore whether these technologies will leave us at a crossroads to an exciting future or to a sustained plateau and disillusionment.

Knowledge-driven lead discovery.

PubMed

Pirard, Bernard

2005-11-01

Virtual screening encompasses several computational approaches which have proven valuable for identifying novel leads. These approaches rely on available information. Herein, we review recent successful applications of virtual screening. The extension of virtual screening methodologies to target families is also briefly discussed.

Development of solid tunable optics for ultra-miniature imaging systems

NASA Astrophysics Data System (ADS)

Yongchao, Zou

This thesis focuses on the optimal design, fabrication and testing of solid tunable optics and exploring their applications in miniature imaging systems. It starts with the numerical modelling of such lenses, followed by the optimum design method and alignment tolerance analysis. A miniature solid tunable lens driven by a piezo actuator is then developed. To solve the problem of limited maximum optical power and tuning range in conventional lens designs, a novel multi-element solid tunable lens is proposed and developed. Inspired by the Alvarez principle, a novel miniature solid tunable dual-focus lens, which is designed using freeform surfaces and driven by one micro-electro-mechanical-systems (MEMS) rotary actuator, is demonstrated. To explore the applications of these miniature solid tunable lenses, a miniature adjustable-focus endoscope and one compact adjustable-focus camera module are developed. The adjustable-focus capability of these two miniature imaging systems is fully proved by electrically focusing targets placed at different positions.

New Herbig-Haro objects in the L1617 and L1646 dark clouds

NASA Astrophysics Data System (ADS)

Wang, H.; Stecklum, B.; Henning, Th.

2005-07-01

Optical imaging towards L1617 and L1646 revealed three new Herbig-Haro (HH) objects, HH 182, 439, and 866. Spectroscopic observations of HH 182 A and 439 A confirmed their HH object nature. Molecular hydrogen v = 1-0 S(1) narrow band imaging revealed three H2 emission features in the HH 182 region which coincide with the optical emission. Based on the position angles of the different parts of the HH 111 flow and that of HH 182, HH 182 may be the outermost southeastern part of the giant HH 111 flow. One deeply embedded star is revealed in our near-infrared imaging of the HH 439 region. HH 439 A and the associated bow shock are probably driven by the newly detected embedded star. HH 439 B-D are probably driven by the Herbig AeBe star candidate GSC 04794-00827 (IRAS 06045-0554). The embedded source IRAS 06046-0603 is identified to be the exciting source of HH 866.

Cerebrospinal fluid bulk flow is driven by the cardiac cycle

NASA Astrophysics Data System (ADS)

Tithof, Jeffrey; Mestre, Humberto; Thomas, John; Nedergaard, Maiken; Kelley, Douglas

2017-11-01

Recent discoveries have uncovered a cerebrospinal fluid (CSF) transport system in the perivascular spaces (PVS) of the mammalian brain which clears excess extracellular fluid and protein waste products. The oscillatory pattern of CSF flow has long been attributed to arterial pulsations due to cardiac contractility but limitations in imaging techniques have impeded quantitative measurement of flow rates within the PVS. In this talk, we describe quantitative measurements from the first ever direct imaging of CSF flow in the PVS of a mouse brain. We perform particle tracking velocimetry to obtain time-resolved velocity measurements. To identify the cardiac and/or respiratory dependence of the flow, while imaging, we simultaneously record the mouse's electrocardiogram and respiration. Our measurements conclusively indicate that CSF pulsatility in the arterial PVS is directly driven by the cardiac cycle and not by the respiratory cycle or cerebral vasomotion. These results offer a substantial step forward in understanding bulk flow of CSF in the mammalian brain and may have important implications related to neurodegenerative diseases.

Test Platform for Advanced Digital Control of Brushless DC Motors (MSFC Center Director's Discretionary Fund)

NASA Technical Reports Server (NTRS)

Gwaltney, D. A.

2002-01-01

A FY 2001 Center Director's Discretionary Fund task to develop a test platform for the development, implementation. and evaluation of adaptive and other advanced control techniques for brushless DC (BLDC) motor-driven mechanisms is described. Important applications for BLDC motor-driven mechanisms are the translation of specimens in microgravity experiments and electromechanical actuation of nozzle and fuel valves in propulsion systems. Motor-driven aerocontrol surfaces are also being utilized in developmental X vehicles. The experimental test platform employs a linear translation stage that is mounted vertically and driven by a BLDC motor. Control approaches are implemented on a digital signal processor-based controller for real-time, closed-loop control of the stage carriage position. The goal of the effort is to explore the application of advanced control approaches that can enhance the performance of a motor-driven actuator over the performance obtained using linear control approaches with fixed gains. Adaptive controllers utilizing an exact model knowledge controller and a self-tuning controller are implemented and the control system performance is illustrated through the presentation of experimental results.

Data Mining and Knowledge Discovery tools for exploiting big Earth-Observation data

NASA Astrophysics Data System (ADS)

Espinoza Molina, D.; Datcu, M.

2015-04-01

The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform's goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

Automated segmentation of middle hepatic vein in non-contrast x-ray CT images based on an atlas-driven approach

NASA Astrophysics Data System (ADS)

Kitagawa, Teruhiko; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki

2008-03-01

In order to support the diagnosis of hepatic diseases, understanding the anatomical structures of hepatic lobes and hepatic vessels is necessary. Although viewing and understanding the hepatic vessels in contrast media-enhanced CT images is easy, the observation of the hepatic vessels in non-contrast X-ray CT images that are widely used for the screening purpose is difficult. We are developing a computer-aided diagnosis (CAD) system to support the liver diagnosis based on non-contrast X-ray CT images. This paper proposes a new approach to segment the middle hepatic vein (MHV), a key structure (landmark) for separating the liver region into left and right lobes. Extraction and classification of hepatic vessels are difficult in non-contrast X-ray CT images because the contrast between hepatic vessels and other liver tissues is low. Our approach uses an atlas-driven method by the following three stages. (1) Construction of liver atlases of left and right hepatic lobes using a learning datasets. (2) Fully-automated enhancement and extraction of hepatic vessels in liver regions. (3) Extraction of MHV based on the results of (1) and (2). The proposed approach was applied to 22 normal liver cases of non-contrast X-ray CT images. The preliminary results show that the proposed approach achieves the success in 14 cases for MHV extraction.

CIFAR10-DVS: An Event-Stream Dataset for Object Classification

PubMed Central

Li, Hongmin; Liu, Hanchao; Ji, Xiangyang; Li, Guoqi; Shi, Luping

2017-01-01

Neuromorphic vision research requires high-quality and appropriately challenging event-stream datasets to support continuous improvement of algorithms and methods. However, creating event-stream datasets is a time-consuming task, which needs to be recorded using the neuromorphic cameras. Currently, there are limited event-stream datasets available. In this work, by utilizing the popular computer vision dataset CIFAR-10, we converted 10,000 frame-based images into 10,000 event streams using a dynamic vision sensor (DVS), providing an event-stream dataset of intermediate difficulty in 10 different classes, named as “CIFAR10-DVS.” The conversion of event-stream dataset was implemented by a repeated closed-loop smooth (RCLS) movement of frame-based images. Unlike the conversion of frame-based images by moving the camera, the image movement is more realistic in respect of its practical applications. The repeated closed-loop image movement generates rich local intensity changes in continuous time which are quantized by each pixel of the DVS camera to generate events. Furthermore, a performance benchmark in event-driven object classification is provided based on state-of-the-art classification algorithms. This work provides a large event-stream dataset and an initial benchmark for comparison, which may boost algorithm developments in even-driven pattern recognition and object classification. PMID:28611582

Interactive High-Relief Reconstruction for Organic and Double-Sided Objects from a Photo.

PubMed

Yeh, Chih-Kuo; Huang, Shi-Yang; Jayaraman, Pradeep Kumar; Fu, Chi-Wing; Lee, Tong-Yee

2017-07-01

We introduce an interactive user-driven method to reconstruct high-relief 3D geometry from a single photo. Particularly, we consider two novel but challenging reconstruction issues: i) common non-rigid objects whose shapes are organic rather than polyhedral/symmetric, and ii) double-sided structures, where front and back sides of some curvy object parts are revealed simultaneously on image. To address these issues, we develop a three-stage computational pipeline. First, we construct a 2.5D model from the input image by user-driven segmentation, automatic layering, and region completion, handling three common types of occlusion. Second, users can interactively mark-up slope and curvature cues on the image to guide our constrained optimization model to inflate and lift up the image layers. We provide real-time preview of the inflated geometry to allow interactive editing. Third, we stitch and optimize the inflated layers to produce a high-relief 3D model. Compared to previous work, we can generate high-relief geometry with large viewing angles, handle complex organic objects with multiple occluded regions and varying shape profiles, and reconstruct objects with double-sided structures. Lastly, we demonstrate the applicability of our method on a wide variety of input images with human, animals, flowers, etc.

Infrared surface temperature measurements for the surface tension driven convection experiment. M.S. Thesis - Case Western Reserve Univ., Aug. 1988

NASA Technical Reports Server (NTRS)

Pline, Alexander D.

1989-01-01

In support of the Surface Tension Driven Convection Experiment (STDCE), a planned space transportation system (STS) flight experiment, a commercially available infrared thermal imaging system is used to quantify the imposed thermal signature along the free surface. The system was tested and calibrated for the STDCE with ground-based equivalents of the STDCE hardware. Before using the system, consideration was given to the radiation characteristics of the target (silicone oil). Absorption coefficients were calculated to understand the surface depth as seen by the imager and the penetration depth of the surface heater (CO2 laser). The performance and operational specifications for the imager and image processing system are described in detail to provide an understanding of the equipment. Measurements made with the system were compared to thermocouple measurements and a calculated surface temperature distribution. This comparison showed that in certain regions the IR imager measurements were within 5 percent of the overall temperature difference across the free surface. In other regions the measurements were within + or - 10 percent of the overall temperature gradient across the free surface. The effective emissivity of silicone oil for these experimental conditions was also determined. Measurement errors and their possible solutions are discussed.

CIFAR10-DVS: An Event-Stream Dataset for Object Classification.

PubMed

Li, Hongmin; Liu, Hanchao; Ji, Xiangyang; Li, Guoqi; Shi, Luping

2017-01-01

Neuromorphic vision research requires high-quality and appropriately challenging event-stream datasets to support continuous improvement of algorithms and methods. However, creating event-stream datasets is a time-consuming task, which needs to be recorded using the neuromorphic cameras. Currently, there are limited event-stream datasets available. In this work, by utilizing the popular computer vision dataset CIFAR-10, we converted 10,000 frame-based images into 10,000 event streams using a dynamic vision sensor (DVS), providing an event-stream dataset of intermediate difficulty in 10 different classes, named as "CIFAR10-DVS." The conversion of event-stream dataset was implemented by a repeated closed-loop smooth (RCLS) movement of frame-based images. Unlike the conversion of frame-based images by moving the camera, the image movement is more realistic in respect of its practical applications. The repeated closed-loop image movement generates rich local intensity changes in continuous time which are quantized by each pixel of the DVS camera to generate events. Furthermore, a performance benchmark in event-driven object classification is provided based on state-of-the-art classification algorithms. This work provides a large event-stream dataset and an initial benchmark for comparison, which may boost algorithm developments in even-driven pattern recognition and object classification.

Perspectives of Frailty and Frailty Screening: Protocol for a Collaborative Knowledge Translation Approach and Qualitative Study of Stakeholder Understandings and Experiences.

PubMed

Archibald, Mandy M; Ambagtsheer, Rachel; Beilby, Justin; Chehade, Mellick J; Gill, Tiffany K; Visvanathan, Renuka; Kitson, Alison L

2017-04-17

Accompanying the unprecedented growth in the older adult population worldwide is an increase in the prevalence of frailty, an age-related clinical state of increased vulnerability to stressor events. This increased vulnerability results in lower social engagement and quality of life, increased dependency, and higher rates of morbidity, health service utilization and mortality. Early identification of frailty is necessary to guide implementation of interventions to prevent associated functional decline. Consensus is lacking on how to clinically recognize and manage frailty. It is unknown how healthcare providers and healthcare consumers understand and perceive frailty, whether or not they regard frailty as a public health concern; and information on the indirect and direct experiences of consumer and healthcare provider groups towards frailty are markedly limited. We will conduct a qualitative study of consumer, practice nurse, general practitioner, emergency department physician, and orthopedic surgeons' perspectives of frailty and frailty screening in metropolitan and non-metropolitan South Australia. We will use tailored combinations of semi-structured interviews and arts-based data collection methods depending on each stakeholder group, followed by inductive and iterative analysis of data using qualitative description. Using stakeholder driven approaches to understanding and addressing frailty and frailty screening in context is critical as the prevalence and burden of frailty is likely to increase worldwide. We will use the findings from the Perceptions of Frailty and Frailty Screening study to inform a context-driven identification, implementation and evaluation of a frailty-screening tool; drive awareness, knowledge, and skills development strategies across stakeholder groups; and guide future efforts to embed emerging knowledge about frailty and its management across diverse South Australian contexts using a collaborative knowledge translation approach. Study findings will help achieve a coordinated frailty and healthy ageing strategy with relevance to other jurisdictions in Australia and abroad, and application of the stakeholder driven approach will help illuminate how its applicability to other jurisdictions.

A novel computer-assisted image analysis of [123I]β-CIT SPECT images improves the diagnostic accuracy of parkinsonian disorders.

PubMed

Goebel, Georg; Seppi, Klaus; Donnemiller, Eveline; Warwitz, Boris; Wenning, Gregor K; Virgolini, Irene; Poewe, Werner; Scherfler, Christoph

2011-04-01

The purpose of this study was to develop an observer-independent algorithm for the correct classification of dopamine transporter SPECT images as Parkinson's disease (PD), multiple system atrophy parkinson variant (MSA-P), progressive supranuclear palsy (PSP) or normal. A total of 60 subjects with clinically probable PD (n = 15), MSA-P (n = 15) and PSP (n = 15), and 15 age-matched healthy volunteers, were studied with the dopamine transporter ligand [(123)I]β-CIT. Parametric images of the specific-to-nondisplaceable equilibrium partition coefficient (BP(ND)) were generated. Following a voxel-wise ANOVA, cut-off values were calculated from the voxel values of the resulting six post-hoc t-test maps. The percentages of the volume of an individual BP(ND) image remaining below and above the cut-off values were determined. The higher percentage of image volume from all six cut-off matrices was used to classify an individual's image. For validation, the algorithm was compared to a conventional region of interest analysis. The predictive diagnostic accuracy of the algorithm in the correct assignment of a [(123)I]β-CIT SPECT image was 83.3% and increased to 93.3% on merging the MSA-P and PSP groups. In contrast the multinomial logistic regression of mean region of interest values of the caudate, putamen and midbrain revealed a diagnostic accuracy of 71.7%. In contrast to a rater-driven approach, this novel method was superior in classifying [(123)I]β-CIT-SPECT images as one of four diagnostic entities. In combination with the investigator-driven visual assessment of SPECT images, this clinical decision support tool would help to improve the diagnostic yield of [(123)I]β-CIT SPECT in patients presenting with parkinsonism at their initial visit.

Multi-GPU Acceleration of Branchless Distance Driven Projection and Backprojection for Clinical Helical CT.

PubMed

Mitra, Ayan; Politte, David G; Whiting, Bruce R; Williamson, Jeffrey F; O'Sullivan, Joseph A

2017-01-01

Model-based image reconstruction (MBIR) techniques have the potential to generate high quality images from noisy measurements and a small number of projections which can reduce the x-ray dose in patients. These MBIR techniques rely on projection and backprojection to refine an image estimate. One of the widely used projectors for these modern MBIR based technique is called branchless distance driven (DD) projection and backprojection. While this method produces superior quality images, the computational cost of iterative updates keeps it from being ubiquitous in clinical applications. In this paper, we provide several new parallelization ideas for concurrent execution of the DD projectors in multi-GPU systems using CUDA programming tools. We have introduced some novel schemes for dividing the projection data and image voxels over multiple GPUs to avoid runtime overhead and inter-device synchronization issues. We have also reduced the complexity of overlap calculation of the algorithm by eliminating the common projection plane and directly projecting the detector boundaries onto image voxel boundaries. To reduce the time required for calculating the overlap between the detector edges and image voxel boundaries, we have proposed a pre-accumulation technique to accumulate image intensities in perpendicular 2D image slabs (from a 3D image) before projection and after backprojection to ensure our DD kernels run faster in parallel GPU threads. For the implementation of our iterative MBIR technique we use a parallel multi-GPU version of the alternating minimization (AM) algorithm with penalized likelihood update. The time performance using our proposed reconstruction method with Siemens Sensation 16 patient scan data shows an average of 24 times speedup using a single TITAN X GPU and 74 times speedup using 3 TITAN X GPUs in parallel for combined projection and backprojection.

Low-level contrast statistics are diagnostic of invariance of natural textures

PubMed Central

Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

2012-01-01

Texture may provide important clues for real world object and scene perception. To be reliable, these clues should ideally be invariant to common viewing variations such as changes in illumination and orientation. In a large image database of natural materials, we found textures with low-level contrast statistics that varied substantially under viewing variations, as well as textures that remained relatively constant. This led us to ask whether textures with constant contrast statistics give rise to more invariant representations compared to other textures. To test this, we selected natural texture images with either high (HV) or low (LV) variance in contrast statistics and presented these to human observers. In two distinct behavioral categorization paradigms, participants more often judged HV textures as “different” compared to LV textures, showing that textures with constant contrast statistics are perceived as being more invariant. In a separate electroencephalogram (EEG) experiment, evoked responses to single texture images (single-image ERPs) were collected. The results show that differences in contrast statistics correlated with both early and late differences in occipital ERP amplitude between individual images. Importantly, ERP differences between images of HV textures were mainly driven by illumination angle, which was not the case for LV images: there, differences were completely driven by texture membership. These converging neural and behavioral results imply that some natural textures are surprisingly invariant to illumination changes and that low-level contrast statistics are diagnostic of the extent of this invariance. PMID:22701419

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

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

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

Imaging of acute cervical spine injuries: review and outlook.

PubMed

Tins, B J; Cassar-Pullicino, V N

2004-10-01

Advances in imaging technology have been successfully applied in the emergency trauma setting with great benefit providing early, accurate and efficient diagnoses. Gaps in the knowledge of imaging acute spinal injury remain, despite a vast wealth of useful research and publications on the role of CT and MRI. This article reviews in a balanced manner the main questions that still face the attending radiologist by embracing the current and evolving concepts to help define and provide answers to the following; Imaging techniques -- strengths and weaknesses; what are the implications of a missed cervical spine injury?; who should be imaged?; how should they be imaged?; spinal immobilisation -- help or hazard?; residual open questions; what does all this mean?; and what are the implications for the radiologist? Although there are many helpful guidelines, the residual gaps in the knowledge base result in incomplete answers to the questions posed. The identification of these gaps in knowledge however should act as the initiating stimulus for further research. All too often there is a danger that the performance and productivity of the imaging modalities is the main research focus and not enough attention is given to the two fundamental prerequisites to the assessment of any imaging technology -- the clinical selection criteria for imaging and the level of expertise of the appropriate clinician interpreting the images.

EarthCube: Advancing Partnerships, Collaborative Platforms and Knowledge Networks in the Ocean Sciences

NASA Astrophysics Data System (ADS)

Stephen, Diggs; Lee, Allison

2014-05-01

The National Science Foundation's EarthCube initiative aims to create a community-driven data and knowledge management system that will allow for unprecedented data sharing across the geosciences. More than 2,500 participants through forums, work groups, EarthCube events, and virtual and in-person meetings have participated. The individuals that have engaged represent the core earth-system sciences of solid Earth, Atmosphere, Oceans, and Polar Sciences. EarthCube is a cornerstone of NSF's Cyberinfrastructure for the 21st Century (CIF21) initiative, whose chief objective is to develop a U.S. nationwide, sustainable, and community-based cyberinfrastructure for researchers and educators. Increasingly effective community-driven cyberinfrastructure allows global data discovery and knowledge management and achieves interoperability and data integration across scientific disciplines. There is growing convergence across scientific and technical communities on creating a networked, knowledge management system and scientific data cyberinfrastructure that integrates Earth system and human dimensions data in an open, transparent, and inclusive manner. EarthCube does not intend to replicate these efforts, but build upon them. An agile development process is underway for the development and governance of EarthCube. The agile approach was deliberately selected due to its iterative and incremental nature while promoting adaptive planning and rapid and flexible response. Such iterative deployment across a variety of EarthCube stakeholders encourages transparency, consensus, accountability, and inclusiveness.

Effectiveness of a Theory-Driven Nutritional Education Program in Improving Calcium Intake among Older Mauritian Adults

PubMed Central

Jeewon, Rajesh

2013-01-01

Background. Low calcium intake, a risk factor of osteoporosis and subsequent fractures, has been previously reported among post-menopausal women in Mauritius. Objective. To assess the effectiveness of a theory-based educational intervention in improving the calcium intake, self-efficacy, and knowledge of older Mauritians. Methodology. The study was conducted as a pre- and post-test design which was evaluated through a baseline, immediate postintervention, and 2-month follow-up assessments. Participants were adults (n = 189) aged ≥40 years old from 2 urban community-based centres. The intervention group (IG) (n = 98) participated in 6 weekly interactive lessons based on the health belief model (HBM). The main outcome measures were calcium intake, HB scale scores, knowledge scores, and physical activity level (PAL). Anthropometric measurements were also assessed. Results. The IG significantly increased its baseline calcium intake, knowledge and self-efficacy (P < 0.001) at post-assessments. A significant decrease in waist circumference in the IG was noted (P < 0.05) after intervention. PAL significantly increased by 12.3% at post-test and by 29.6% at follow-up among intervention adults when compared to the CG (P < 0.001). Conclusion. A theory-driven educational intervention is effective in improving the dietary calcium intake, knowledge, self-efficacy, and PAL of older community-based Mauritian adults. PMID:24453901

Food as Risk: How Eating Habits and Food Knowledge Affect Reactivity to Pictures of Junk and Healthy Foods.

PubMed

Yegiyan, Narine S; Bailey, Rachel L

2016-01-01

This study explores how people respond to images of junk versus healthy food as a function of their eating habits and food knowledge. The experiment reported here proposed and tested the idea that those with unhealthy eating habits but highly knowledgeable about healthy eating would feel more positive and also more negative toward junk food images compared to images of healthy food because they may perceive them as risky--desirable but potentially harmful. The psychophysiological data collected from participants during their exposure to pictures of junk versus healthy food supported this idea. In addition, unhealthy eaters compared to healthy eaters with the same degree of food knowledge responded more positively to all food items. The findings are critical from a health communication perspective. Because unhealthy eaters produce stronger emotional responses to images of junk food, they are more likely to process information associated with junk food with more cognitive effort and scrutiny. Thus, when targeting this group and using images of junk food, it is important to combine these images with strong message claims and relevant arguments; otherwise, if the arguments are perceived as irrelevant or weak, the motivational activation associated with junk food itself may transfer into an increased desire to consume the unhealthy product.

The micronutrient genomics project: a community-driven knowledge base for micronutrient research

USDA-ARS?s Scientific Manuscript database

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it...

Troubleshooting Portfolios

ERIC Educational Resources Information Center

Crismond, David; Peterie, Matthew

2017-01-01

The Troubleshooting Portfolios approach was developed at the Olathe Northwest High School in Olathe, Kansas. This approach supports integrated STEM and "informed design" thinking and learning, in which students: (1) use design strategies effectively; (2) work creatively and collaboratively in teams; (3) make knowledge-driven decisions;…

MOPEX: a software package for astronomical image processing and visualization

NASA Astrophysics Data System (ADS)

Makovoz, David; Roby, Trey; Khan, Iffat; Booth, Hartley

2006-06-01

We present MOPEX - a software package for astronomical image processing and display. The package is a combination of command-line driven image processing software written in C/C++ with a Java-based GUI. The main image processing capabilities include creating mosaic images, image registration, background matching, point source extraction, as well as a number of minor image processing tasks. The combination of the image processing and display capabilities allows for much more intuitive and efficient way of performing image processing. The GUI allows for the control over the image processing and display to be closely intertwined. Parameter setting, validation, and specific processing options are entered by the user through a set of intuitive dialog boxes. Visualization feeds back into further processing by providing a prompt feedback of the processing results. The GUI also allows for further analysis by accessing and displaying data from existing image and catalog servers using a virtual observatory approach. Even though originally designed for the Spitzer Space Telescope mission, a lot of functionalities are of general usefulness and can be used for working with existing astronomical data and for new missions. The software used in the package has undergone intensive testing and benefited greatly from effective software reuse. The visualization part has been used for observation planning for both the Spitzer and Herschel Space Telescopes as part the tool Spot. The visualization capabilities of Spot have been enhanced and integrated with the image processing functionality of the command-line driven MOPEX. The image processing software is used in the Spitzer automated pipeline processing, which has been in operation for nearly 3 years. The image processing capabilities have also been tested in off-line processing by numerous astronomers at various institutions around the world. The package is multi-platform and includes automatic update capabilities. The software package has been developed by a small group of software developers and scientists at the Spitzer Science Center. It is available for distribution at the Spitzer Science Center web page.

Enhancing the T-shaped learning profile when teaching hydrology using data, modeling, and visualization activities

NASA Astrophysics Data System (ADS)

Sanchez, Christopher A.; Ruddell, Benjamin L.; Schiesser, Roy; Merwade, Venkatesh

2016-03-01

Previous research has suggested that the use of more authentic learning activities can produce more robust and durable knowledge gains. This is consistent with calls within civil engineering education, specifically hydrology, that suggest that curricula should more often include professional perspective and data analysis skills to better develop the "T-shaped" knowledge profile of a professional hydrologist (i.e., professional breadth combined with technical depth). It was expected that the inclusion of a data-driven simulation lab exercise that was contextualized within a real-world situation and more consistent with the job duties of a professional in the field, would provide enhanced learning and appreciation of job duties beyond more conventional paper-and-pencil exercises in a lower-division undergraduate course. Results indicate that while students learned in both conditions, learning was enhanced for the data-driven simulation group in nearly every content area. This pattern of results suggests that the use of data-driven modeling and visualization activities can have a significant positive impact on instruction. This increase in learning likely facilitates the development of student perspective and conceptual mastery, enabling students to make better choices about their studies, while also better preparing them for work as a professional in the field.

Enhancing the T-shaped learning profile when teaching hydrology using data, modeling, and visualization activities

NASA Astrophysics Data System (ADS)

Sanchez, C. A.; Ruddell, B. L.; Schiesser, R.; Merwade, V.

2015-07-01

Previous research has suggested that the use of more authentic learning activities can produce more robust and durable knowledge gains. This is consistent with calls within civil engineering education, specifically hydrology, that suggest that curricula should more often include professional perspective and data analysis skills to better develop the "T-shaped" knowledge profile of a professional hydrologist (i.e., professional breadth combined with technical depth). It was expected that the inclusion of a data driven simulation lab exercise that was contextualized within a real-world situation and more consistent with the job duties of a professional in the field, would provide enhanced learning and appreciation of job duties beyond more conventional paper-and-pencil exercises in a lower division undergraduate course. Results indicate that while students learned in both conditions, learning was enhanced for the data-driven simulation group in nearly every content area. This pattern of results suggests that the use of data-driven modeling and visualization activities can have a significant positive impact on instruction. This increase in learning likely facilitates the development of student perspective and conceptual mastery, enabling students to make better choices about their studies, while also better preparing them for work as a professional in the field.

Condom Use among Immigrant Latino Sexual Minorities: Multilevel Analysis after Respondent-Driven Sampling

PubMed Central

Rhodes, Scott D.; McCoy, Thomas P.

2014-01-01

This study explored correlates of condom use within a respondent-driven sample of 190 Spanish-speaking immigrant Latino sexual minorities, including gay and bisexual men, other men who have sex with men (MSM), and transgender person, in North Carolina. Five analytic approaches for modeling data collected using respondent-driven sampling (RDS) were compared. Across most approaches, knowledge of HIV and sexually transmitted infections (STIs) and increased condom use self-efficacy predicted consistent condom use and increased homophobia predicted decreased consistent condom use. The same correlates were not significant in all analyses but were consistent in most. Clustering due to recruitment chains was low, while clustering due to recruiter was substantial. This highlights the importance accounting for clustering when analyzing RDS data. PMID:25646728

Stable solutions of inflation driven by vector fields

NASA Astrophysics Data System (ADS)

Emami, Razieh; Mukohyama, Shinji; Namba, Ryo; Zhang, Ying-li

2017-03-01

Many models of inflation driven by vector fields alone have been known to be plagued by pathological behaviors, namely ghost and/or gradient instabilities. In this work, we seek a new class of vector-driven inflationary models that evade all of the mentioned instabilities. We build our analysis on the Generalized Proca Theory with an extension to three vector fields to realize isotropic expansion. We obtain the conditions required for quasi de-Sitter solutions to be an attractor analogous to the standard slow-roll one and those for their stability at the level of linearized perturbations. Identifying the remedy to the existing unstable models, we provide a simple example and explicitly show its stability. This significantly broadens our knowledge on vector inflationary scenarios, reviving potential phenomenological interests for this class of models.

Enabling Science Integration through the Marine Geoscience Data System Media Bank

NASA Astrophysics Data System (ADS)

Leung, A.; Ferrini, V.; Arko, R.; Carbotte, S. M.; Goehring, L.; Simms, E.

2008-12-01

The Marine Geoscience Data System Media Bank (http://media.marine-geo.org) was constructed to enable the sharing of high quality images, illustrations and animations among members of the science community and to provide a new forum for education and public outreach (EPO). The initial focus of Media Bank was to serve Ridge 2000 research and EPO efforts, but it was constructed as a flexible system that could accommodate media from other multidisciplinary marine geoscience research initiatives. Media Bank currently contains digital photographs, maps, 3-D visualizations, and video clips from the Ridge 2000 and MARGINS focus sites as well as the Antarctic and Southern Ocean. We actively seek contributions of other high quality marine geoscience media for inclusion in Media Bank. Media Bank is driven by a relational database backend, enabling image browsing, sorting by category, keyword search functionality, and the creation of media galleries. All media are accompanied by a descriptive figure caption that provides easy access to expert knowledge to help foster data integration across disciplines as well as EPO efforts. In addition to access to high quality media, Media Bank also provides basic metadata including geographic position, investigator name and affiliation, as well as copyright information, and links to references and relevant data sets. Since media are tied to geospatial coordinates, a map-based interface is also provided for access to media.

Optimal sampling with prior information of the image geometry in microfluidic MRI.

PubMed

Han, S H; Cho, H; Paulsen, J L

2015-03-01

Recent advances in MRI acquisition for microscopic flows enable unprecedented sensitivity and speed in a portable NMR/MRI microfluidic analysis platform. However, the application of MRI to microfluidics usually suffers from prolonged acquisition times owing to the combination of the required high resolution and wide field of view necessary to resolve details within microfluidic channels. When prior knowledge of the image geometry is available as a binarized image, such as for microfluidic MRI, it is possible to reduce sampling requirements by incorporating this information into the reconstruction algorithm. The current approach to the design of the partial weighted random sampling schemes is to bias toward the high signal energy portions of the binarized image geometry after Fourier transformation (i.e. in its k-space representation). Although this sampling prescription is frequently effective, it can be far from optimal in certain limiting cases, such as for a 1D channel, or more generally yield inefficient sampling schemes at low degrees of sub-sampling. This work explores the tradeoff between signal acquisition and incoherent sampling on image reconstruction quality given prior knowledge of the image geometry for weighted random sampling schemes, finding that optimal distribution is not robustly determined by maximizing the acquired signal but from interpreting its marginal change with respect to the sub-sampling rate. We develop a corresponding sampling design methodology that deterministically yields a near optimal sampling distribution for image reconstructions incorporating knowledge of the image geometry. The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry. Copyright © 2015 Elsevier Inc. All rights reserved.

Incarnation, Image, and Story: Toward a Postmodern Orthodoxy for Christian Educators

ERIC Educational Resources Information Center

Wineland, Richard K.

2005-01-01

As Christian educators we must take seriously the gospel command to "go, and teach them all that I have commanded you." But how are we to proclaim the ancient faith in a relativistic, image-driven, post-modern age that long ago abandoned modernism's holy crusade to either prove or disprove the orthodox faith through reason? Using the example of…

Capillary electrophoresis: Imaging of electroosmotic and pressure driven flow profiles in fused silica capillaries

NASA Technical Reports Server (NTRS)

Williams, George O., Jr.

1996-01-01

This study is a continuation of the summer of 1994 NASA/ASEE Summer Faculty Fellowship Program. This effort is a portion of the ongoing work by the Biophysics Branch of the Marshall Space Flight Center. The work has focused recently on the separation of macromolecules using capillary electrophoresis (CE). Two primary goals were established for the effort this summer. First, we wanted to use capillary electrophoresis to study the electrohydrodynamics of a sample stream. Secondly, there was a need to develop a methodology for using CE for separation of DNA molecules of various sizes. In order to achieve these goals we needed to establish a procedure for detection of a sample plug under the influence of an electric field Detection of the sample with the microscope and image analysis system would be helpful in studying the electrohydrodynamics of this stream under load. Videotaping this process under the influence of an electric field in real time would also be useful. Imaging and photography of the sample/background electrolyte interface would be vital to this study. Finally, detection and imaging of electroosmotic flow and pressure driven flow must be accomplished.

Particle image velocimetry for the Surface Tension Driven Convection Experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Psychophysiological Responsivity to Script-Driven Imagery: An Exploratory Study of the Effects of Eye Movements on Public Speaking Flashforwards.

PubMed

Kearns, Michelle; Engelhard, Iris M

2015-01-01

A principle characteristic of public speaking anxiety relates to intrusive mental images of potential future disasters. Previous research has found that the self-reported emotionality of such "flashforwards" can be reduced by a cognitively demanding, dual-task (e.g., making eye movements) performed whilst holding the mental image in-mind. The outcome measure in these earlier studies was participants' self-reported emotional intensity of the mental image. The current study (N = 34) explored whether an objective measure of emotionality would yield similar results in students with public speaking anxiety. A script-driven imagery procedure was used to measure psychophysiological responsivity to an audio script depicting a feared (public speaking) scenario before and after an eye movement intervention. Relative to the control condition (imagery only), those who made eye movements whilst holding a mental image of this scenario in-mind demonstrated a significant decrease in heart rate, which acted as a measure of emotionality. These findings add to a previous body of research demonstrating the beneficial qualities of dual-tasks and their potential for treatment of both past and future-oriented anxieties.

Psychophysiological Responsivity to Script-Driven Imagery: An Exploratory Study of the Effects of Eye Movements on Public Speaking Flashforwards

PubMed Central

Kearns, Michelle; Engelhard, Iris M.

2015-01-01

A principle characteristic of public speaking anxiety relates to intrusive mental images of potential future disasters. Previous research has found that the self-reported emotionality of such “flashforwards” can be reduced by a cognitively demanding, dual-task (e.g., making eye movements) performed whilst holding the mental image in-mind. The outcome measure in these earlier studies was participants’ self-reported emotional intensity of the mental image. The current study (N = 34) explored whether an objective measure of emotionality would yield similar results in students with public speaking anxiety. A script-driven imagery procedure was used to measure psychophysiological responsivity to an audio script depicting a feared (public speaking) scenario before and after an eye movement intervention. Relative to the control condition (imagery only), those who made eye movements whilst holding a mental image of this scenario in-mind demonstrated a significant decrease in heart rate, which acted as a measure of emotionality. These findings add to a previous body of research demonstrating the beneficial qualities of dual-tasks and their potential for treatment of both past and future-oriented anxieties. PMID:26321964

Particle image velocimetry for the surface tension driven convection experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Safety and efficacy for new techniques and imaging using new equipment to support European legislation: an EU coordination action.

PubMed

Zoetelief, J; Faulkner, K

2008-01-01

The past two decades have witnessed a technologically driven revolution in radiology. At the centre of these developments has been the use of computing. These developments have also been driven by the introduction of new detector and imaging devices in radiology and nuclear medicine, as well as the widespread application of computing techniques to enhance and extract information within the images acquired. Further advances have been introduced into digital practice. These technological developments, however, have not been matched by justification and optimisation studies to ensure that these new imaging devices and techniques are as effective as they might be, or performed at the lowest possible dose. The work programme of the SENTINEL Coordination Action was subdivided into eight work packages: functional performance and standards; efficacy and safety in digital radiology, dentistry and nuclear medicine, cardiology, interventional radiology, population screening/sensitive groups; justification, ethics and efficacy; good practice guidance and training; and project management. The intention of the work programme was to underwrite the safety, efficacy and ethical aspects of digital practice as well as to protect and add value to the equipment used in radiology.

View subspaces for indexing and retrieval of 3D models

NASA Astrophysics Data System (ADS)

Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel

2010-02-01

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

Correlates of parental feeding practices with pre-schoolers: Parental body image and eating knowledge, attitudes, and behaviours.

PubMed

Damiano, Stephanie R; Hart, Laura M; Paxton, Susan J

2016-06-01

Parental feeding practices have been linked to eating and weight status in young children; however, more research is needed to understand what influences these feeding practices. The aim of this study was to examine how parental feeding practices that are linked to unhealthy eating patterns in young children, are related to parental body image and eating knowledge, attitudes, and behaviours . Participants were 330 mothers of a 2- to 6-year-old child. Mothers completed measures of knowledge of child body image and eating patterns, overvaluation of weight and shape, internalization of general media and athletic ideals, dieting, and parental feeding practices. Higher maternal knowledge of strategies to promote positive child body image and eating patterns predicted lower weight restriction, instrumental, emotional, and pushing to eat feeding practices. Overvaluation of weight and shape predicted use of fat restriction. Maternal internalization of the athletic ideal predicted instrumental and pushing to eat feeding practices. As these feeding practices have been associated with long-term risk of children's weight gain and/or disordered eating, these findings highlight the need for prevention interventions to target knowledge, attitudes, and behaviours of parents of pre-schoolers. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Between images and texts: manuals as a praxis of knowledge].

PubMed

Schiavinatto, Iara Lis; Pataca, Ermelinda Moutinho

2016-01-01

We investigate a series of writing genres from the Enlightenment in Portugal, especially between 1720 and 1800, comprehending them as manuals of knowledge, and we highlight some of the meanings of the images in these writings that were widely circulated in the Portuguese-speaking world.

The Relationship between Immediate Relevant Basic Science Knowledge and Clinical Knowledge: Physiology Knowledge and Transthoracic Echocardiography Image Interpretation

ERIC Educational Resources Information Center

Nielsen, Dorte Guldbrand; Gotzsche, Ole; Sonne, Ole; Eika, Berit

2012-01-01

Two major views on the relationship between basic science knowledge and clinical knowledge stand out; the Two-world view seeing basic science and clinical science as two separate knowledge bases and the encapsulated knowledge view stating that basic science knowledge plays an overt role being encapsulated in the clinical knowledge. However, resent…

Relationship of college student characteristics and inquiry-based geometrical optics instruction to knowledge of image formation with light-ray tracing

NASA Astrophysics Data System (ADS)

Isik, Hakan

This study is premised on the fact that student conceptions of optics appear to be unrelated to student characteristics of gender, age, years since high school graduation, or previous academic experiences. This study investigated the relationships between student characteristics and student performance on image formation test items and the changes in student conceptions of optics after an introductory inquiry-based physics course. Data was collected from 39 college students who were involved in an inquiry-based physics course teaching topics of geometrical optics. Student data concerning characteristics and previous experiences with optics and mathematics were collected. Assessment of student understanding of optics knowledge for pinholes, plane mirrors, refraction, and convex lenses was collected with, the Test of Image Formation with Light-Ray Tracing instrument. Total scale and subscale scores representing the optics instrument content were derived from student pretest and posttest responses. The types of knowledge, needed to answer each optics item correctly, were categorized as situational, conceptual, procedural, and strategic knowledge. These types of knowledge were associated with student correct and incorrect responses to each item to explain the existences and changes in student scientific and naive conceptions. Correlation and stepwise multiple regression analyses were conducted to identify the student characteristics and academic experiences that significantly predicted scores on the subscales of the test. The results showed that student experience with calculus was a significant predictor of student performance on the total scale as well as on the refraction subscale of the Test of Image Formation with Light-Ray Tracing. A combination of student age and previous academic experience with precalculus was a significant predictor of student performance on the pretest pinhole subscale. Student characteristic of years since high school graduation significantly predicted the gain in student scores on pinhole and plane-mirror items from the pretest to the posttest with those students who were most recent graduates from high school doing better. Multivariate and univariate analyses of variance of the Test of Image Formation with Light-Ray Tracing pinhole scale and individual item changes from the pretest to the posttest resulted in statistically significant mean differences between total scores as well as between various individual pinhole items. There were no significant changes for individual plane-mirror items from pretest to posttest. Results revealed that there is a perceivable relationship between student optics-content knowledge and the types of knowledge required by items. At the pretest, the greatest selection of wrong responses related to the items requiring situational type of knowledge and the fewest selection of wrong responses was relate to the items requiring procedural type of knowledge. Student selection of wrong options for each item revealed the following naive optics conceptions: pinholes do not create reversed images (pretest), size and sharpness of pinhole images are related to the focus of a pinhole camera (pretest and posttest); propagation of light rays are interpreted as being radial rather than directional (pretest and posttest); no conception of image formation and observation for parallel mirrors (pretest and posttest), the place of an image depends on the position of the observer (pretest and posttest), a plane mirror reflects the images of the objects placed at one side of the mirror and the observers who were positioned at the other side of the mirror can see them (pretest and posttest); applying the law of reflection to plane mirrors without considering the variations in angles of incidence and reflection (pretest and posttest), and image observation is confused with the image formation in mirrors placed perpendicular to one another (pretest and posttest). Future research should focus on the acquisition, development, and identification of reliable measures of optics concepts, processes, types of knowledge, and specific optics understanding (i.e., pinhole, plane-mirror). Future research should focus on the identification of the more critical concepts such as changes in size and sharpness of pinhole images, image observation, image formation in general, and image formation and observation in parallel mirrors. Future research can be conducted with a larger set of participants so as to compare different instructional methods and address instructional deficiencies using more efficient statistical methods. Comparative studies can be conducted to investigate the relations of various instructional strategies on student conceptions of optics.

Challenges and complexities of multifrequency atomic force microscopy in liquid environments

PubMed Central

2014-01-01

Summary This paper illustrates through numerical simulation the complexities encountered in high-damping AFM imaging, as in liquid enviroments, within the specific context of multifrequency atomic force microscopy (AFM). The focus is primarily on (i) the amplitude and phase relaxation of driven higher eigenmodes between successive tip–sample impacts, (ii) the momentary excitation of non-driven higher eigenmodes and (iii) base excitation artifacts. The results and discussion are mostly applicable to the cases where higher eigenmodes are driven in open loop and frequency modulation within bimodal schemes, but some concepts are also applicable to other types of multifrequency operations and to single-eigenmode amplitude and frequency modulation methods. PMID:24778952

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

PubMed

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.

Energy-dispersive neutron imaging and diffraction of magnetically driven twins in a Ni2MnGa single crystal magnetic shape memory alloy

NASA Astrophysics Data System (ADS)

Kabra, Saurabh; Kelleher, Joe; Kockelmann, Winfried; Gutmann, Matthias; Tremsin, Anton

2016-09-01

Single crystals of a partially twinned magnetic shape memory alloy, Ni2MnGa, were imaged using neutron diffraction and energy-resolved imaging techniques at the ISIS spallation neutron source. Single crystal neutron diffraction showed that the crystal produces two twin variants with a specific crystallographic relationship. Transmission images were captured using a time of flight MCP/Timepix neutron counting detector. The twinned and untwinned regions were clearly distinguishable in images corresponding to narrow-energy transmission images. Further, the spatially-resolved transmission spectra were used to elucidate the orientations of the crystallites in the different volumes of the crystal.

Statistical and engineering methods for model enhancement

NASA Astrophysics Data System (ADS)

Chang, Chia-Jung

Models which describe the performance of physical process are essential for quality prediction, experimental planning, process control and optimization. Engineering models developed based on the underlying physics/mechanics of the process such as analytic models or finite element models are widely used to capture the deterministic trend of the process. However, there usually exists stochastic randomness in the system which may introduce the discrepancy between physics-based model predictions and observations in reality. Alternatively, statistical models can be used to develop models to obtain predictions purely based on the data generated from the process. However, such models tend to perform poorly when predictions are made away from the observed data points. This dissertation contributes to model enhancement research by integrating physics-based model and statistical model to mitigate the individual drawbacks and provide models with better accuracy by combining the strengths of both models. The proposed model enhancement methodologies including the following two streams: (1) data-driven enhancement approach and (2) engineering-driven enhancement approach. Through these efforts, more adequate models are obtained, which leads to better performance in system forecasting, process monitoring and decision optimization. Among different data-driven enhancement approaches, Gaussian Process (GP) model provides a powerful methodology for calibrating a physical model in the presence of model uncertainties. However, if the data contain systematic experimental errors, the GP model can lead to an unnecessarily complex adjustment of the physical model. In Chapter 2, we proposed a novel enhancement procedure, named as “Minimal Adjustment”, which brings the physical model closer to the data by making minimal changes to it. This is achieved by approximating the GP model by a linear regression model and then applying a simultaneous variable selection of the model and experimental bias terms. Two real examples and simulations are presented to demonstrate the advantages of the proposed approach. Different from enhancing the model based on data-driven perspective, an alternative approach is to focus on adjusting the model by incorporating the additional domain or engineering knowledge when available. This often leads to models that are very simple and easy to interpret. The concepts of engineering-driven enhancement are carried out through two applications to demonstrate the proposed methodologies. In the first application where polymer composite quality is focused, nanoparticle dispersion has been identified as a crucial factor affecting the mechanical properties. Transmission Electron Microscopy (TEM) images are commonly used to represent nanoparticle dispersion without further quantifications on its characteristics. In Chapter 3, we developed the engineering-driven nonhomogeneous Poisson random field modeling strategy to characterize nanoparticle dispersion status of nanocomposite polymer, which quantitatively represents the nanomaterial quality presented through image data. The model parameters are estimated through the Bayesian MCMC technique to overcome the challenge of limited amount of accessible data due to the time consuming sampling schemes. The second application is to calibrate the engineering-driven force models of laser-assisted micro milling (LAMM) process statistically, which facilitates a systematic understanding and optimization of targeted processes. In Chapter 4, the force prediction interval has been derived by incorporating the variability in the runout parameters as well as the variability in the measured cutting forces. The experimental results indicate that the model predicts the cutting force profile with good accuracy using a 95% confidence interval. To conclude, this dissertation is the research drawing attention to model enhancement, which has considerable impacts on modeling, design, and optimization of various processes and systems. The fundamental methodologies of model enhancement are developed and further applied to various applications. These research activities developed engineering compliant models for adequate system predictions based on observational data with complex variable relationships and uncertainty, which facilitate process planning, monitoring, and real-time control.

Original non-stationary eddy current imaging process for the evaluation of defects in metallic structures

NASA Astrophysics Data System (ADS)

Placko, Dominique; Bore, Thierry; Rivollet, Alain; Joubert, Pierre-Yves

2015-10-01

This paper deals with the problem of imaging defects in metallic structures through eddy current (EC) inspections, and proposes an original process for a possible tomographical crack evaluation. This process is based on a semi analytical modeling, called "distributed point source method" (DPSM) which is used to describe and equate the interactions between the implemented EC probes and the structure under test. Several steps will be successively described, illustrating the feasibility of this new imaging process dedicated to the quantitative evaluation of defects. The basic principles of this imaging process firstly consist in creating a 3D grid by meshing the volume potentially inspected by the sensor. As a result, a given number of elemental volumes (called voxels) are obtained. Secondly, the DPSM modeling is used to compute an image for all occurrences in which only one of the voxels has a different conductivity among all the other ones. The assumption consists to consider that a real defect may be truly represented by a superimposition of elemental voxels: the resulting accuracy will naturally depend on the density of space sampling. On other hand, the excitation device of the EC imager has the capability to be oriented in several directions, and driven by an excitation current at variable frequency. So, the simulation will be performed for several frequencies and directions of the eddy currents induced in the structure, which increases the signal entropy. All these results are merged in a so-called "observation matrix" containing all the probe/structure interaction configurations. This matrix is then used in an inversion scheme in order to perform the evaluation of the defect location and geometry. The modeled EC data provided by the DPSM are compared to the experimental images provided by an eddy current imager (ECI), implemented on aluminum plates containing some buried defects. In order to validate the proposed inversion process, we feed it with computed images of various acquisition configurations. Additive noise was added to the images so that they are more representative of actual EC data. In the case of simple notch type defects, for which the relative conductivity may only take two extreme values (1 or 0), a threshold was introduced on the inverted images, in a post processing step, taking advantage of a priori knowledge of the statistical properties of the restored images. This threshold allowed to enhance the image contrast and has contributed to eliminate both the residual noise and the pixels showing non-realistic values.

Using Two Different Approaches to Assess Dietary Patterns: Hypothesis-Driven and Data-Driven Analysis.

PubMed

Previdelli, Ágatha Nogueira; de Andrade, Samantha Caesar; Fisberg, Regina Mara; Marchioni, Dirce Maria

2016-09-23

The use of dietary patterns to assess dietary intake has become increasingly common in nutritional epidemiology studies due to the complexity and multidimensionality of the diet. Currently, two main approaches have been widely used to assess dietary patterns: data-driven and hypothesis-driven analysis. Since the methods explore different angles of dietary intake, using both approaches simultaneously might yield complementary and useful information; thus, we aimed to use both approaches to gain knowledge of adolescents' dietary patterns. Food intake from a cross-sectional survey with 295 adolescents was assessed by 24 h dietary recall (24HR). In hypothesis-driven analysis, based on the American National Cancer Institute method, the usual intake of Brazilian Healthy Eating Index Revised components were estimated. In the data-driven approach, the usual intake of foods/food groups was estimated by the Multiple Source Method. In the results, hypothesis-driven analysis showed low scores for Whole grains, Total vegetables, Total fruit and Whole fruits), while, in data-driven analysis, fruits and whole grains were not presented in any pattern. High intakes of sodium, fats and sugars were observed in hypothesis-driven analysis with low total scores for Sodium, Saturated fat and SoFAA (calories from solid fat, alcohol and added sugar) components in agreement, while the data-driven approach showed the intake of several foods/food groups rich in these nutrients, such as butter/margarine, cookies, chocolate powder, whole milk, cheese, processed meat/cold cuts and candies. In this study, using both approaches at the same time provided consistent and complementary information with regard to assessing the overall dietary habits that will be important in order to drive public health programs, and improve their efficiency to monitor and evaluate the dietary patterns of populations.

SU-D-9A-01: Listmode-Driven Optimal Gating (OG) Respiratory Motion Management: Potential Impact On Quantitative PET Imaging

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

Lee, K; Hristov, D

2014-06-01

Purpose: To evaluate the potential impact of listmode-driven amplitude based optimal gating (OG) respiratory motion management technique on quantitative PET imaging. Methods: During the PET acquisitions, an optical camera tracked and recorded the motion of a tool placed on top of patients' torso. PET event data were utilized to detect and derive a motion signal that is directly coupled with a specific internal organ. A radioactivity-trace was generated from listmode data by accumulating all prompt counts in temporal bins matching the sampling rate of the external tracking device. Decay correction for 18F was performed. The image reconstructions using OG respiratorymore » motion management technique that uses 35% of total radioactivity counts within limited motion amplitudes were performed with external motion and radioactivity traces separately with ordered subset expectation maximization (OSEM) with 2 iterations and 21 subsets. Standard uptake values (SUVs) in a tumor region were calculated to measure the effect of using radioactivity trace for motion compensation. Motion-blurred 3D static PET image was also reconstructed with all counts and the SUVs derived from OG images were compared with SUVs from 3D images. Results: A 5.7 % increase of the maximum SUV in the lesion was found for optimal gating image reconstruction with radioactivity trace when compared to a static 3D image. The mean and maximum SUVs on the image that was reconstructed with radioactivity trace were found comparable (0.4 % and 4.5 % increase, respectively) to the values derived from the image that was reconstructed with external trace. Conclusion: The image reconstructed using radioactivity trace showed that the blurring due to the motion was reduced with impact on derived SUVs. The resolution and contrast of the images reconstructed with radioactivity trace were comparable to the resolution and contrast of the images reconstructed with external respiratory traces. Research supported by Siemens.« less

An adaptive optics imaging system designed for clinical use

PubMed Central

Zhang, Jie; Yang, Qiang; Saito, Kenichi; Nozato, Koji; Williams, David R.; Rossi, Ethan A.

2015-01-01

Here we demonstrate a new imaging system that addresses several major problems limiting the clinical utility of conventional adaptive optics scanning light ophthalmoscopy (AOSLO), including its small field of view (FOV), reliance on patient fixation for targeting imaging, and substantial post-processing time. We previously showed an efficient image based eye tracking method for real-time optical stabilization and image registration in AOSLO. However, in patients with poor fixation, eye motion causes the FOV to drift substantially, causing this approach to fail. We solve that problem here by tracking eye motion at multiple spatial scales simultaneously by optically and electronically integrating a wide FOV SLO (WFSLO) with an AOSLO. This multi-scale approach, implemented with fast tip/tilt mirrors, has a large stabilization range of ± 5.6°. Our method consists of three stages implemented in parallel: 1) coarse optical stabilization driven by a WFSLO image, 2) fine optical stabilization driven by an AOSLO image, and 3) sub-pixel digital registration of the AOSLO image. We evaluated system performance in normal eyes and diseased eyes with poor fixation. Residual image motion with incremental compensation after each stage was: 1) ~2–3 arc minutes, (arcmin) 2) ~0.5–0.8 arcmin and, 3) ~0.05–0.07 arcmin, for normal eyes. Performance in eyes with poor fixation was: 1) ~3–5 arcmin, 2) ~0.7–1.1 arcmin and 3) ~0.07–0.14 arcmin. We demonstrate that this system is capable of reducing image motion by a factor of ~400, on average. This new optical design provides additional benefits for clinical imaging, including a steering subsystem for AOSLO that can be guided by the WFSLO to target specific regions of interest such as retinal pathology and real-time averaging of registered images to eliminate image post-processing. PMID:26114033

Big data analytics in hyperspectral imaging for detection of microbial colonies on agar plates (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yoon, Seung-Chul; Park, Bosoon; Lawrence, Kurt C.

2017-05-01

Various types of optical imaging techniques measuring light reflectivity and scattering can detect microbial colonies of foodborne pathogens on agar plates. Until recently, these techniques were developed to provide solutions for hypothesis-driven studies, which focused on developing tools and batch/offline machine learning methods with well defined sets of data. These have relatively high accuracy and rapid response time because the tools and methods are often optimized for the collected data. However, they often need to be retrained or recalibrated when new untrained data and/or features are added. A big-data driven technique is more suitable for online learning of new/ambiguous samples and for mining unknown or hidden features. Although big data research in hyperspectral imaging is emerging in remote sensing and many tools and methods have been developed so far in many other applications such as bioinformatics, the tools and methods still need to be evaluated and adjusted in applications where the conventional batch machine learning algorithms were dominant. The primary objective of this study is to evaluate appropriate big data analytic tools and methods for online learning and mining of foodborne pathogens on agar plates. After the tools and methods are successfully identified, they will be applied to rapidly search big color and hyperspectral image data of microbial colonies collected over the past 5 years in house and find the most probable colony or a group of colonies in the collected big data. The meta-data, such as collection time and any unstructured data (e.g. comments), will also be analyzed and presented with output results. The expected results will be novel, big data-driven technology to correctly detect and recognize microbial colonies of various foodborne pathogens on agar plates.

The evolution of colour polymorphism in British winter-active Lepidoptera in response to search image use by avian predators.

PubMed

Weir, Jamie C

2018-05-10

Phenotypic polymorphism in cryptic species is widespread. This may evolve in response to search image use by predators exerting negative frequency-dependent selection on intraspecific colour morphs, 'apostatic selection'. Evidence exists to indicate search image formation by predators and apostatic selection operating on wild prey populations, though not to demonstrate search image use directly resulting in apostatic selection. The present study attempted to address this deficiency, using British Lepidoptera active in winter as a model system. It has been proposed that the typically polymorphic wing colouration of these species represents an anti-search image adaptation against birds. To test (a) for search image-driven apostatic selection, dimorphic populations of artificial moth-like models were established in woodland at varying relative morph frequencies and exposed to predation by natural populations of birds. In addition, to test (b) whether abundance and degree of polymorphism are correlated across British winter-active moths, as predicted where search image use drives apostatic selection, a series of phylogenetic comparative analyses were conducted. There was a positive relationship between artificial morph frequency and probability of predation, consistent with birds utilizing search images and exerting apostatic selection. Abundance and degree of polymorphism were found to be positively correlated across British Lepidoptera active in winter, though not across all taxonomic groups analysed. This evidence is consistent with polymorphism in this group having evolved in response to search image-driven apostatic selection and supports the viability of this mechanism as a means by which phenotypic and genetic variation may be maintained in natural populations. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Exponentiation: A New Basic?

ERIC Educational Resources Information Center

Davis, Brent

2015-01-01

For centuries, the basic operations of school mathematics have been identified as addition, subtraction, multiplication, and division. Notably, these operations are "basic," not because they are foundational to mathematics knowledge, but because they were vital to a newly industrialized and market-driven economy several hundred years…

Career Advising in a VUCA Environment

ERIC Educational Resources Information Center

Shaffer, Leigh S.; Zalewski, Jacqueline M.

2011-01-01

Recent developments in the knowledge-driven, postindustrial economy have radically affected college students' prospects for entering and completing successful careers. In this volatile, uncertain, complex, and ambiguous (VUCA) environment, fewer organizations find profitability in hiring, training, and retaining workers. Over the last 20 years,…

Realizing the promise of AOPs: A stakeholder-driven roadmap to the future

EPA Science Inventory

The adverse outcome pathway (AOP) framework was developed to serve as a knowledge assembly and communication tool to facilitate translation of mechanistic (e.g., molecular, biochemical, histological) data into adverse apical outcomes meaningful to chemical risk assessment. Althou...

Heat release and flame structure measurements of self-excited acoustically-driven premixed methane flames

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

Kopp-Vaughan, Kristin M.; Tuttle, Steven G.; Renfro, Michael W.

An open-open organ pipe burner (Rijke tube) with a bluff-body ring was used to create a self-excited, acoustically-driven, premixed methane-air conical flame, with equivalence ratios ranging from 0.85 to 1.05. The feed tube velocities corresponded to Re = 1780-4450. Coupled oscillations in pressure, velocity, and heat release from the flame are naturally encouraged at resonant frequencies in the Rijke tube combustor. This coupling creates sustainable self-excited oscillations in flame front area and shape. The period of the oscillations occur at the resonant frequency of the combustion chamber when the flame is placed {proportional_to}1/4 of the distance from the bottom ofmore » the tube. In this investigation, the shape of these acoustically-driven flames is measured by employing both OH planar laser-induced fluorescence (PLIF) and chemiluminescence imaging and the images are correlated to simultaneously measured pressure in the combustor. Past research on acoustically perturbed flames has focused on qualitative flame area and heat release relationships under imposed velocity perturbations at imposed frequencies. This study reports quantitative empirical fits with respect to pressure or phase angle in a self-generated pressure oscillation. The OH-PLIF images were single temporal shots and the chemiluminescence images were phase averaged on chip, such that 15 exposures were used to create one image. Thus, both measurements were time resolved during the flame oscillation. Phase-resolved area and heat release variations throughout the pressure oscillation were computed. A relation between flame area and the phase angle before the pressure maximum was derived for all flames in order to quantitatively show that the Rayleigh criterion was satisfied in the combustor. Qualitative trends in oscillating flame area were found with respect to feed tube flow rates. A logarithmic relation was found between the RMS pressure and both the normalized average area and heat release rate for all flames. (author)« less

A population-based tissue probability map-driven level set method for fully automated mammographic density estimations.

PubMed

Kim, Youngwoo; Hong, Byung Woo; Kim, Seung Ja; Kim, Jong Hyo

2014-07-01

A major challenge when distinguishing glandular tissues on mammograms, especially for area-based estimations, lies in determining a boundary on a hazy transition zone from adipose to glandular tissues. This stems from the nature of mammography, which is a projection of superimposed tissues consisting of different structures. In this paper, the authors present a novel segmentation scheme which incorporates the learned prior knowledge of experts into a level set framework for fully automated mammographic density estimations. The authors modeled the learned knowledge as a population-based tissue probability map (PTPM) that was designed to capture the classification of experts' visual systems. The PTPM was constructed using an image database of a selected population consisting of 297 cases. Three mammogram experts extracted regions for dense and fatty tissues on digital mammograms, which was an independent subset used to create a tissue probability map for each ROI based on its local statistics. This tissue class probability was taken as a prior in the Bayesian formulation and was incorporated into a level set framework as an additional term to control the evolution and followed the energy surface designed to reflect experts' knowledge as well as the regional statistics inside and outside of the evolving contour. A subset of 100 digital mammograms, which was not used in constructing the PTPM, was used to validate the performance. The energy was minimized when the initial contour reached the boundary of the dense and fatty tissues, as defined by experts. The correlation coefficient between mammographic density measurements made by experts and measurements by the proposed method was 0.93, while that with the conventional level set was 0.47. The proposed method showed a marked improvement over the conventional level set method in terms of accuracy and reliability. This result suggests that the proposed method successfully incorporated the learned knowledge of the experts' visual systems and has potential to be used as an automated and quantitative tool for estimations of mammographic breast density levels.

Brain and nervous system (image)

MedlinePlus

The nervous system controls the many complicated and interconnected functions of the body and mind. Motor, sensory cognitive and autonomic function are all coordinated and driven by the brain and nerves. As people age, ...

Research, the lifeline of medicine.

PubMed

Kornberg, A

1976-05-27

Advances in medicine spring from discoveries in physics, chemistry and biology. Among key contributions to the diagnosis, treatment and prevention of cardiovascular and pulmonary diseases, a recent Comroe-Dripps analysis shows two thirds to have been basic rather than applied research. Without a firm foundation in basic knowledge innovations perceived as advances prove hollow and collapse. Strong social, economic and political pressures now threaten acquisition of basic knowledge. Scientists feel driven to undertake excessively complex problems and gamble against the historical record that science generally progresses by tackling discrete and well defined questions. Regardless of circumstances, professional standards require the physician and scientist to be creative and enlarge the fund of knowledge.

Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

Knowledge-Based Vision Techniques for the Autonomous Land Vehicle Program

DTIC Science & Technology

1991-10-01

Knowledge System The CKS is an object-oriented knowledge database that was originally designed to serve as the central information manager for a...34 Representation Space: An Approach to the Integra- tion of Visual Information ," Proc. of DARPA Image Understanding Workshop, Palo Alto, CA, pp. 263-272, May 1989...Strat, " Information Management in a Sensor-Based Au- tonomous System," Proc. DARPA Image Understanding Workshop, University of Southern CA, Vol.1, pp

A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis.

PubMed

Vafaee, Fatemeh; Diakos, Connie; Kirschner, Michaela B; Reid, Glen; Michael, Michael Z; Horvath, Lisa G; Alinejad-Rokny, Hamid; Cheng, Zhangkai Jason; Kuncic, Zdenka; Clarke, Stephen

2018-01-01

Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed a multi-objective optimisation method that effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. The proposed multi-objective framework has the capacity to adjust for conflicting biomarker objectives and to incorporate heterogeneous information facilitating systems approaches to biomarker discovery. We have found a prognostic signature of colorectal cancer comprising 11 circulating microRNAs. The identified signature predicts the patients' survival outcome and targets pathways underlying colorectal cancer progression. The altered expression of the identified microRNAs was confirmed in an independent public data set of plasma samples of patients in early stage vs advanced colorectal cancer. Furthermore, the generality of the proposed method was demonstrated across three publicly available miRNA data sets associated with biomarker studies in other diseases.

An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

PubMed Central

Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

2008-01-01

Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495