SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

An internationally recognized leader in visualization, scientific computing, and image analysis

SCI Publications

2008


G. Draper, R. Riesenfeld. “Who Votes For What? A Visual Query Language for Opinion Data,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 14, No. 6, IEEE, pp. 1197--1204. Nov, 2008.
DOI: 10.1109/tvcg.2008.187


G. Draper, Y. Livnat, R. Riesenfeld. “A Visual Query Language for Correlation Discovery and Management,” In Proceedings of Visual and Iconic Language Conference (VaIL 2008), pp. 14--23. 2008.


T. Ellkvist, D. Koop, E.W. Anderson, J. Freire, C.T. Silva. “Using Provenance to Support Real-Time Collaborative Design of Workflows,” In Proceedings of the Second International Provenance and Annotation Workshop (IPAW 2008), pp. 266--279. 2008.


T. Ellkvist, D. Koop, J. Freire, C.T. Silva, L. Stromback. “Using Mediation to Achieve Provenance Interoperability,” In Proceedings of the 2008 Fourth IEEE International Conference on eScience, pp. 398--399. 2008.


A. Fedorov, E. Billet, M.W. Prastawa, G. Gerig, A. Radmanesh, S.K. Warfield, R. Kikinis, N. Chrisochoides. “Evaluation of Brain MRI Alignment with the Robust Hausdorff Distance Measures,” In Lecture Notes in Computer Science, Vol. 5358, Springer, pp. 594--603. 2008.
DOI: 10.1007/978-3-540-89639-5_57


P.T. Fletcher, S. Venkatasubramanian, S. Joshi. “Robust Statistics on Riemannian Manifolds via the Geometric Median,” In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), pp. 1--8. 2008.
DOI: 10.1109/CVPR.2008.4587747


N.L. Foster, A.Y. Wang, T. Tasdizen, P.T. Fletcher, J.M. Hoffman, R.A. Koeppe. “Realizing the Potential of Positron Emission Tomography with 18F-Fluorodeoxyglucose to Improve the Treatment of Alzheimer,” In Journal of the Alzheimer, Vol. 4, No. 1, Suppl. 1, pp. S29--36. 2008.
PubMed ID: 18631997


N. L. Foster, A.Y. Wang, T. Tasdizen, K. Chen, W. Jagust, R.A. Koeppe, E. Reiman, M.W. Weiner, S. Minoshima. “Cerebral Hypometabolism Suggesting Frototemporal Dementia in an Alzheimer’s Disease Clinical Trial,” In Neurology, Vol. 70, No. 11, pp. A103. 2008.


J. Freire, C.T. Silva. “Towards Enabling Social Analysis of Scientific Data,” In Proceedings of CHI Social Data Analysis Workshop 2008, 2008.

ABSTRACT

Computing has been an enormous accelerator to science and it has led to an information explosion in many different fields. Future advances in science depend on the ability to comprehend these vast amounts of data. In this paper, we discuss challenges and opportunities for social data analysis in the scientific domain.


J. Freire, D. Koop, C.T. Silva. “Provenance for Computational Tasks: A Survey,” In Computing in Science and Engineering, Vol. 10, No. 3, pp. 11--21. 2008.


M. Fuchs, S. Gerber. “Variational Shape Detection in Microscope Images Based on Joint Shape and Image Feature Statistics,” In Proceedings of the IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2008), pp. 1--8. 2008.
DOI: 10.1109/CVPRW.2008.4563012

ABSTRACT

This paper presents a novel variational formulation incorporating statistical knowledge to detect shapes in images. We propose to train an energy based on joint shape and feature statistics inferred from training data. Variational approaches to shape detection traditionally involve energies consisting of a feature term and a regularization term. The feature term forces the detected object to be optimal with respect to image properties such as contrast, pattern or edges whereas the regularization term stabilizes the shape of the object. Our trained energy does not rely on these two separate terms, hence avoids the non-trivial task of balancing them properly. This enables us to incorporate more complex image features while still relying on a moderate number of training samples. Cell detection in microscope images illustrates the capability of the proposed method to automatically adapt itself to different image features. We also introduce a nonlinear energy and exemplarily compare it to the linear approach.


W. Gao, Y. Chen, G. Gerig, J.K. Smith, V. Jewells, J.H. Gilmore, W. Lin. “Temporal and Spatial Development of Axonal Maturation and Myelination of White Matter in the Developing Brain,” In American Journal of Neuroradiology, pp. (published online). Nov 11, 2008.
DOI: 10.3174/ajnr.A1363


S.E. Geneser, R.M. Kirby, R.S. MacLeod. “Application of Stochastic Finite Element Methods to Study the Sensitivity of ECG Forward Modeling to Organ Conductivity,” In IEEE Transations on Biomedical Engineering, Vol. 55, No. 1, pp. 31--40. January, 2008.


J.H. Gilmore, L. Smith, H. Wolfe, B. Hertzberg, J.K. Smith, N. Chescheir, D. Evans, C. Kang, R.M. Hamer, W. Lin, G. Gerig. “Prenatal Mild Ventriculomegaly Predicts Abnormal Development of the Neonatal Brain,” In Biological Psychiatry, Vol. 64, No. 12, pp. 1069-1076. Dec, 2008.
PubMed ID: 18835482


C. Goodlett, P.T. Fletcher, J. Gilmore, G. Gerig. “Group Statistics of DTI Fiber Bundles Using Spatial Functions of Tensor Measures,” In Medical Image Computing and Computer-Assisted Intervention (MICCAI 2008), Springer Verlag, pp. 1068--1075. 2008.
PubMed ID: 18979851


C.E. Goodyer, J. Wood, M. Berzins. “Mathematical modeling of chemical diffusion through skin using Grid-based PSEs,” In Modeling, Simulation and Optimization of Complex Processes: Proceedings of the Third International Conference on High Performance Scientific Computing, Edited by H.G. Bock and E. Kostina and H.X. Phu and R. Rannacher, Springer, pp. 249--258. 2008.


D. Gottlieb, D. Xiu. “Galerkin Method for Wave Equations with Uncertain Coefficients,” In Communications in Computational Physics, Vol. 3, No. 2, pp. 505--518. 2008.

ABSTRACT

Polynomial chaos methods (and generalized polynomial chaos methods) have been extensively applied to analyze PDEs that contain uncertainties. However this approach is rarely applied to hyperbolic systems. In this paper we analyze the properties of the resulting deterministic system of equations obtained by stochastic Galerkin projection. We consider a simple model of a scalar wave equation with random wave speed. We show that when uncertainty causes the change of characteristic directions, the resulting deterministic system of equations is a symmetric hyperbolic system with both positive and negative eigenvalues. A consistent method of imposing the boundary conditions is proposed and its convergence is established. Numerical examples are presented to support the analysis.

Keywords: Generalized polynomial chaos, stochastic PDE, Galerkin method, hyperbolic equation, uncertainty quantification


S. Gouttard, M. Styner, M.W. Prastawa, J. Piven, G. Gerig. “Assessment of Reliability of Multi-site Neuroimaging via Traveling Phantom Study,” In Proceedings of Medical Image Computing and Computer Assisted Intervention 2008, Lecture Notes in Computer Science LNCS, Vol. 5242, pp. 263--270. September, 2008.


C. Gribble, C. Brownlee, S.G. Parker. “Practical Global Illumination for Interactive Particle Visualization,” In Computers and Graphics, Vol. 32, No. 1, pp. 14--24. February, 2008.
DOI: 10.1016/j.cag.2007.11.001

ABSTRACT

Particle-based simulation methods are used to model a wide range of complex phenomena and to solve time-dependent problems of various scales. Effective visualizations of the resulting state will communicate subtle changes in the three-dimensional structure, spatial organization, and qualitative trends within a simulation as it evolves. We present two algorithms targeting upcoming, highly parallel multicore desktop systems to enable interactive navigation and exploration of large particle data sets with global illumination effects. Monte Carlo path tracing and texture mapping are used to capture computationally expensive illumination effects such as soft shadows and diffuse interreflection. The first approach is based on precomputation of luminance textures and removes expensive illumination calculations from the interactive rendering pipeline. The second approach is based on dynamic luminance texture generation and decouples interactive rendering from the computation of global illumination effects. These algorithms provide visual cues that enhance the ability to perform analysis and feature detection tasks while interrogating the data at interactive rates. We explore the performance of these algorithms and demonstrate their effectiveness using several large data sets.

Keywords: Interactive particle visualization, Global illumination, Ray tracing


C.W. Hamman, J.C. Klewicki, R.M. Kirby. “On the Lamb Vector Divergence in Navier-Stokes Flows,” In Journal of Fluid Mechanics, Vol. 610, pp. 261--284. 2008.