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SCI Publications

2011

J.C. Bennett, V. Krishnamoorthy, S. Liu, R.W. Grout, E.R. Hawkes, J.H. Chen, J. Shepherd, V. Pascucci, P.-T. Bremer. “Feature-Based Statistical Analysis of Combustion Simulation Data,” In IEEE Transactions on Visualization and Computer Graphics, Proceedings of the 2011 IEEE Visualization Conference, Vol. 17, No. 12, pp. 1822--1831. 2011.

M. Berger, J.A. Levine, L.G. Nonato, G. Taubin, C.T. Silva. “An End-to-End Framework for Evaluating Surface Reconstruction,” SCI Technical Report, No. UUSCI-2011-001, SCI Institute, University of Utah, 2011.

M.L. Berlanga, S. Phan, E.A. Bushong, S. Lamont, S. Wu, O. Kwon, B.S. Phung, M. Terada, T. Tasdizen, E. Martone, M.H. Ellisman. “Three-dimensional reconstruction of serial mouse brain sections using high-resolution large-scale mosaics,” In Frontiers in Neuroscience Methods, Vol. 5, pp. (published online). March, 2011.
DOI: 10.3389/fnana.2011.00017

H. Bhatia, S. Jadhav, P.-T. Bremer, G. Chen, J.A. Levine, L.G. Nonato, V. Pascucci. “Edge Maps: Representing Flow with Bounded Error,” In Proceedings of IEEE Pacific Visualization Symposium 2011, Hong Kong, China, Note: Won Best Paper Award!, pp. 75--82. March, 2011.
DOI: 10.1109/PACIFICVIS.2011.5742375

H. Bhatia, S. Jadhav, P.-T. Bremer, G. Chen, J.A. Levine, L.G. Nonato, V. Pascucci. “Flow Visualization with Quantified Spatial and Temporal Errors using Edge Maps,” In IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol. 18, No. 9, IEEE Society, pp. 1383--1396. 2011.
DOI: 10.1109/TVCG.2011.265

C. Brownlee, V. Pegoraro, S. Shankar, P.S. McCormick, C.D. Hansen. “Physically-Based Interactive Flow Visualization Based on Schlieren and Interferometry Experimental Techniques,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 17, No. 11, pp. 1574--1586. 2011.

ABSTRACT

Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics (CFD) produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph, interferometry, and schlieren imaging for centuries, which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. Interferometry tracks changes in phase-shift resulting in bands appearing. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraph, schlieren and interferometry images of time-varying scalar fields derived from computational fluid dynamics data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Applications of our method to multifield data and custom application-dependent color filter creation are explored. Results comparing this method to previous schlieren approximations are finally presented.

Keywords: uintah, c-safe

B.M. Burton, J.D. Tate, B. Erem, D.J. Swenson, D.F. Wang, D.H. Brooks, P.M. van Dam, R.S. MacLeod. “A Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment,” In Proceedings of the 2011 IEEE Int. Conf. Engineering and Biology Society (EMBC), pp. 267--270. 2011.
DOI: 10.1109/IEMBS.2011.6090052
PubMed ID: 22254301
PubMed Central ID: PMC3337752

ABSTRACT

Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems.

C.R. Butson, S.E. Cooper, J.M. Henderson, B. Wolgamuth, C.C. McIntyre. “Probabilistic Analysis of Activation Volumes Generated During Deep Brain Stimulation,” In NeuroImage, Vol. 54, pp. 2096--2104. 2011.
ISSN: 1095-9572
DOI: 10.1016/j.neuroimage.2010.10.059
PubMed ID: 20974269

ABSTRACT

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease (PD) and shows great promise for the treatment of several other disorders. However, while the clinical analysis of DBS has received great attention, a relative paucity of quantitative techniques exists to define the optimal surgical target and most effective stimulation protocol for a given disorder. In this study we describe a methodology that represents an evolutionary addition to the concept of a probabilistic brain atlas, which we call a probabilistic stimulation atlas (PSA). We outline steps to combine quantitative clinical outcome measures with advanced computational models of DBS to identify regions where stimulation-induced activation could provide the best therapeutic improvement on a per-symptom basis. While this methodology is relevant to any form of DBS, we present example results from subthalamic nucleus (STN) DBS for PD. We constructed patient-specific computer models of the volume of tissue activated (VTA) for 163 different stimulation parameter settings which were tested in six patients. We then assigned clinical outcome scores to each VTA and compiled all of the VTAs into a PSA to identify stimulation-induced activation targets that maximized therapeutic response with minimal side effects. The results suggest that selection of both electrode placement and clinical stimulation parameter settings could be tailored to the patient's primary symptoms using patient-specific models and PSAs.

C.R. Butson, I.O. Miller, R.A. Normann, G.A. Clark. “Selective neural activation in a histologically derived model of peripheral nerve,” In Journal of Neural Engineering, Vol. 8, No. 3, pp. 036009. June, 2011.
ISSN: 1741-2552
DOI: 10.1088/1741-2560/8/3/036009
PubMed ID: 21478574

ABSTRACT

Functional electrical stimulation (FES) is a general term for therapeutic methods that use electrical stimulation to aid or replace lost ability. For FES systems that communicate with the nervous system, one critical component is the electrode interface through which the machine-body information transfer must occur. In this paper, we examine the influence of inhomogeneous tissue conductivities and positions of nodes of Ranvier on activation of myelinated axons for neuromuscular control as a function of electrode configuration. To evaluate these effects, we developed a high-resolution bioelectric model of a fascicle from a stained cross-section of cat sciatic nerve. The model was constructed by digitizing a fixed specimen of peripheral nerve, extruding the image along the axis of the nerve, and assigning each anatomical component to one of several different tissue types. Electrodes were represented by current sources in monopolar, transverse bipolar, and longitudinal bipolar configurations; neural activation was determined using coupled field-neuron simulations with myelinated axon cable models. We found that the use of an isotropic tissue medium overestimated neural activation thresholds compared with the use of physiologically based, inhomogeneous tissue medium, even after controlling for mean impedance levels. Additionally, the positions of the cathodic sources relative to the nodes of Ranvier had substantial effects on activation, and these effects were modulated by the electrode configuration. Our results indicate that physiologically based tissue properties cause considerable variability in the neural response, and the inclusion of these properties is an important component in accurately predicting activation. The results are used to suggest new electrode designs to enable selective stimulation of small diameter fibers.

G.T. Buzzard, D. Xiu. “Variance-based Global Sensitivity Analysis via Sparse-grid Interpolation and Cubature,” In Communications in Computational Physics, Vol. 9, No. 3, pp. 542--567. 2011.
DOI: 10.4208/cicp.230909.160310s

ABSTRACT

The stochastic collocation method using sparse grids has become a popular choice for performing stochastic computations in high dimensional (random) parameter space. In addition to providing highly accurate stochastic solutions, the sparse grid collocation results naturally contain sensitivity information with respect to the input random parameters. In this paper, we use the sparse grid interpolation and cubature methods of Smolyak together with combinatorial analysis to give a computationally efficient method for computing the global sensitivity values of Sobol'. This method allows for approximation of all main effect and total effect values from evaluation of f on a single set of sparse grids. We discuss convergence of this method, apply it to several test cases and compare to existing methods. As a result which may be of independent interest, we recover an explicit formula for evaluating a Lagrange basis interpolating polynomial associated with the Chebyshev extrema. This allows one to manipulate the sparse grid collocation results in a highly efficient manner.

Keywords: Stochastic collocation, sparse grids, sensitivity analysis, Smolyak, Sobol

C.D. Cantwell, S.J. Sherwin, R.M. Kirby, P.H.J. Kelly. “From h to p Efficiently: Strategy Selection for Operator Evaluation on Hexahedral and Tetrahedral Elements,” In Computers and Fluids, Vol. 43, No. 1, pp. 23--28. 2011.
DOI: 10.1016/j.compfluid.2010.08.012

C.D. Cantwell, S.J. Sherwin, R.M. Kirby, P.H.J. Kelly. “From h to p Efficiently: Selecting the Optimal Spectral/hp Discretisation in Three Dimensions,” In Mathematical Modelling of Natural Phenomena, Vol. 6, No. 3, pp. 84--96. 2011.

G. Chen, D. Palke, Z. Lin, H. Yeh, P. Vincent, R.S. Laramee, E. Zhang. “Asymmetric Tensor Field Visualization for Surfaces,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 17, No. 12, IEEE, pp. 1979-1988. Dec, 2011.
DOI: 10.1109/tvcg.2011.170

Guoning Chen, Qingqing Deng, Andrzej Szymczak, Robert S. Laramee, and Eugene Zhang. “Morse Set Classification and Hierarchical Refinement using Conley Index,” In IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol. 18, No. 5, pp. 767--782. June, 2011.
DOI: 10.1109/TVCG.2011.107
PubMed ID: 21690641

ABSTRACT

Morse decomposition provides a numerically stable topological representation of vector fields that is crucial for their rigorous interpretation. However, Morse decomposition is not unique, and its granularity directly impacts its computational cost. In this paper, we propose an automatic refinement scheme to construct the Morse Connection Graph (MCG) of a given vector field in a hierarchical fashion. Our framework allows a Morse set to be refined through a local update of the flow combinatorialization graph, as well as the connection regions between Morse sets. The computation is fast because the most expensive computation is concentrated on a small portion of the domain. Furthermore, the present work allows the generation of a topologically consistent hierarchy of MCGs, which cannot be obtained using a global method. The classification of the extracted Morse sets is a crucial step for the construction of the MCG, for which the Poincaré index is inadequate. We make use of an upper bound for the Conley index, provided by the Betti numbers of an index pair for a translation along the flow, to classify the Morse sets. This upper bound is sufficiently accurate for Morse set classification and provides supportive information for the automatic refinement process. An improved visualization technique for MCG is developed to incorporate the Conley indices. Finally, we apply the proposed techniques to a number of synthetic and real-world simulation data to demonstrate their utility.

A.N.M. Imroz Choudhury, P. Rosen. “Abstract Visualization of Runtime Memory Behavior,” In 6th IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT 2011), pp. 22--29. 2011.

ABSTRACT

We present a system for visualizing memory reference traces, the records of the memory transactions performed by a program at runtime. The visualization consists of a structured layout representing the levels of a cache and a set of data glyphs representing the pieces of data in memory being operated on during application runtime. The data glyphs move in response to events generated by a cache simulator, indicating their changing residency in the various levels of the memory hierarchy. Within the levels, the glyphs arrange themselves into higher-order shapes representing the structure of the cache levels, including the composition of their associative cache sets and eviction ordering. We make careful use of different visual channels, including structure, motion, color, and size, to convey salient events as they occur. Our abstract visualization provides a high-level, global view of memory behavior, while giving insight about important events that may help students or software engineers to better understand their software’s performance and behavior.

A. Cuadros-Vargas, L.G. Nonato, V. Pascucci. “Combinatorial Laplacian Image Cloning,” In Proceedings of XXIV Sibgrapi – Conference on Graphics, Patterns and Images, pp. 236--241. 2011.
DOI: 10.1109/SIBGRAPI.2011.7

ABSTRACT

Seamless image cloning has become one of the most important editing operation for photomontage. Recent coordinate-based methods have lessened considerably the computational cost of image cloning, thus enabling interactive applications. However, those techniques still bear severe limitations as to concavities and dynamic shape deformation. In this paper we present novel methodology for image cloning that turns out to be highly efficient in terms of computational times while still being more flexible than existing techniques. Our approach builds on combinatorial Laplacian and fast Cholesky factorization to ensure interactive image manipulation, handling holes, concavities, and dynamic deformations during the cloning process. The provided experimental results show that the proposed technique outperforms existing methods in requisites such as accuracy and flexibility.

M. Daccarett, T.J. Badger, N. Akoum, N.S. Burgon, C. Mahnkopf, G.R. Vergara, E.G. Kholmovski, C.J. McGann, D.L. Parker, J. Brachmann, R.S. Macleod, N.F. Marrouche. “Association of left atrial fibrosis detected by delayed-enhancement magnetic resonance imaging and the risk of stroke in patients with atrial fibrillation,” In Journal of the American College of Cardiology, Vol. 57, No. 7, pp. 831--838. 2011.
PubMed ID: 21310320

M. Daccarett, C.J. McGann, N.W. Akoum, R.S. MacLeod, N.F. Marrouche. “MRI of the left atrium: predicting clinical outcomes in patients with atrial fibrillation,” In Expert Review of Cardiovascular Therapy, Vol. 9, No. 1, pp. 105--111. 2011.
PubMed ID: 21166532

M. Datar, Y. Gur, B. Paniagua, M. Styner, R.T. Whitaker. “Geometric Correspondence for Ensembles of Nonregular Shapes,” In Proceedings of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Lecture Notes in Computer Science (LNCS), Vol. 6892, pp. 368--375. 2011.
DOI: 10.1007/978-3-642-23629-7_45
PubMed ID: 21995050
PubMed Central ID: PMC3346950

ABSTRACT

An ensemble of biological shapes can be represented and analyzed with a dense set of point correspondences. In previous work, optimal point placement was determined by optimizing an information theoretic criterion that depends on relative spatial locations on different shapes combined with pairwise Euclidean distances between nearby points on the same shape. These choices have prevented such methods from effectively characterizing shapes with complex geometry such as thin or highly curved features. This paper extends previous methods for automatic shape correspondence by taking into account the underlying geometry of individual shapes. This is done by replacing the Euclidean distance for intrashape pairwise particle interactions by the geodesic distance. A novel set of numerical techniques for fast distance computations on curved surfaces is used to extract these distances. In addition, we introduce an intershape penalty term that incorporates surface normal information to achieve better particle correspondences near sharp features. Finally, we demonstrate this new method on synthetic and biological datasets.

Keywords: namic

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