We propose to continue the research and development within the Center for Bioelectric Field Simulation, Modeling, and Visualization, which officially began operations in September, 1999. In the intervening two years, we have developed a foundation in infrastructure, personnel, and the software engineering of their integrated problem solving environment, BioPSE. In this time, we have achieved many of the milestones proposed in the initial application: we have released several versions of both BioPSE and map3D to the scientific community; we have carried out development in all areas of the grant and published widely on the topics of original research; we have hosted a highly successful meeting of the Resource External Advisory board; and working closely with a subset of the Resource collaborators, we have shown the feasibility and utility of their approach to integrated software design and implementation. We are well poised to continue the Resource and have strong endorsements from their External Advisory Board, the collaborators who have benefitted from the Resource, and the University of Utah through its strong matching contributions. ? ? The broad application of the Resource remains bioelectric field research with special interest in cardiac and neurological electrophysiology. The recent growth in computational capabilities has made it feasible to begin to simulate the complexity of bioelectric sources and fields. We propose that the most efficient means of making optimal use of these computational resources is through a highly integrated, modular, extensible and portable open standard. We have created such a system in our Bioelectric Problem Solving Environment (BioPSE) and made available as open source code. ? ? The organization of the proposal reflects that of the Resource itself with four components dealing with each of BioPSE, modeling, simulation, and visualization. There are development and original research goals in each component t
| Burton, B M; Aras, K K; Good, W W et al. (2018) Image-based modeling of acute myocardial ischemia using experimentally derived ischemic zone source representations. J Electrocardiol 51:725-733 |
| Tong, Xin; Edwards, John; Chen, Chun-Ming et al. (2016) View-Dependent Streamline Deformation and Exploration. IEEE Trans Vis Comput Graph 22:1788-801 |
| Burton, Brett M; Tate, Jess D; Good, Wilson et al. (2016) The Role of Reduced Left Ventricular, Systolic Blood Volumes in ST Segment Potentials Overlying Diseased Tissue of the Ischemic Heart. Comput Cardiol (2010) 43:209-212 |
| Erem, Burak; Martinez Orellana, Ramon; Hyde, Damon E et al. (2016) Extensions to a manifold learning framework for time-series analysis on dynamic manifolds in bioelectric signals. Phys Rev E 93:042218 |
| Raj, Mukund; Mirzargar, Mahsa; Preston, J Samuel et al. (2016) Evaluating Shape Alignment via Ensemble Visualization. IEEE Comput Graph Appl 36:60-71 |
| Gao, Yi; Zhu, Liangjia; Cates, Joshua et al. (2015) A Kalman Filtering Perspective for Multiatlas Segmentation. SIAM J Imaging Sci 8:1007-1029 |
| Gillette, Karli; Tate, Jess; Kindall, Brianna et al. (2015) Generation of Combined-Modality Tetrahedral Meshes. Comput Cardiol (2010) 2015:953-956 |
| Erem, B; Hyde, D E; Peters, J M et al. (2015) COMBINED DELAY AND GRAPH EMBEDDING OF EPILEPTIC DISCHARGES IN EEG REVEALS COMPLEX AND RECURRENT NONLINEAR DYNAMICS. Proc IEEE Int Symp Biomed Imaging 2015:347-350 |
| Coll-Font, J; Erem, B; Štóví?ek, P et al. (2015) A STATISTICAL APPROACH TO INCORPORATE MULTIPLE ECG OR EEG RECORDINGS WITH ARTIFACTUAL VARIABILITY INTO INVERSE SOLUTIONS. Proc IEEE Int Symp Biomed Imaging 2015:1053-1056 |
| Elhabian, Shireen; Gur, Yaniv; Vachet, Clement et al. (2014) Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences. Front Neurol 5:240 |
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