Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

SCI Publications

2002


A.A. Samsonov, E.G. Kholmovski. “Method for Quality Improvement of Images Reconstructed From Sensitivity-Encoded Data,” In Proceedings of The 10th Annual Scientific Meeting of The International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, pp. 2408. 2002.



Y. Serinagaoglu, D.H. Brooks, R.S. MacLeod. “Including Sparse Noisy Epicardial Potential Measurements Into Bayesian Inverse Electrocardiography,” In Proceedings of EMBC 2002, 2002.



Y. Serinagaoglu, R.S. MacLeod, B. Yilmaz, D.H. Brooks. “Multielectrode Venous Catheter Mapping as a High Quality Constraint for Electrocardiographic Inverse Solution,” In J. Electrocardiol., Vol. 35 (supplement), 2002.



J. Simpson, A.R. Sanderson, E. Luke, K. Balling, R. Coffey. “Collaborative Remote Visualization,” In Proceedings of the IEEE/ACM SC2002 Conference, Baltimore, Maryland, November, 2002.



J. Simpson, A.R. Sanderson, E. Luke, K. Balling, R. Coffey. “Collaborative Remote Visualization,” In Presented before the Utah State Legislature, 2002.



J. Stinstra, M. Peters. “The Influence of Fetoabdominal Tissues on Fetal ECGs and MCGs,” In Arch Physiol Biochem, Vol. 110, No. 3, pp. 165--176. 2002.



B. Taccardi, B.B. Punske, R.S. MacLeod, Q. Ni. “Visualization, Analysis and Physiological Interpretation of Three-dimentional Cardiac Electric Fields,” In Proceedings of 24th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2002.



T. Tasdizen, R.T. Whitaker, P. Burchard, S. Osher. “Geometric Surface Smoothing via Anisotropic Diffusion of Normals,” In Proceeding of IEEE Visualization 2002, pp. 125--132. 2002.



X. Tricoche, T. Wischgoll, G. Scheuermann, H. Hagen. “Topology Tracking for the Visualization of Time-Dependent Two-Dimensional Flows,” In Computer & Graphics, Vol. 26, pp. 249--257. 2002.



X. Tricoche, G. Scheuermann, H. Hagen. “Scaling the Topology of Symmetric Second Order Tensor Fields,” In Hierarchical and Geometrical Methods in Scientific Visualization, Springer, Berlin, pp. 171-184. 2002.



X. Tricoche. “Vector and Tensor Topology Simplification, Tracking, and Visualization,” Note: Schriftenreihe Fachbereich Informatik (3), Universitat Kaiserslautern, 2002.



R. Van Uitert, C.R. Johnson. “Can a Spherical Model Substitute for a Realistic Head Model in Forward and Inverse MEG Simulations?,” In Proceedings of The 13th International Conference on Biomagnetism, Jena, Germany, August, 2002.



A.I. Veress, J.A. Weiss, G.T. Gullberg, D.G. Vince, R.D. Rabbitt. “Strain Measurement In Coronary Arteries Using Intravascular Ultrasound And Deformable Images,” In ASME J. Biom. Eng., Vol. 124, pp. 734--741. 2002.



M. Walkley, P.K. Jimack, M. Berzins. “Anisotropic Adaptivity for Finite Element Solutions of 3-D Convection-Dominated Problems,” In Int. J. Numer. Meth. Fluids, Vol. 40, No. 3-4, pp. 551--559. 2002.



M. Walkley, M. Berzins. “A finite element model for the two-dimensional extended Boussinesq equations,” In International Journal for Numerical Methods in Fluids, Vol. 39, No. 10, pp. 865--885. 2002.



J.A. Weiss, J.C. Gardiner, C. Bonifasi-Lista. “Ligament Material Behavior is Nonlinear, Viscoelastic and Rate-Independent Under Shear Loading,” In Journal of Biomechanics, Vol. 35, pp. 943--950. 2002.



R.T. Whitaker, V. Elangovan. “A Direct Approach to Estimating Surfaces in Tomographic Data,” In J. Med. Img. Anal., Vol. 6, No. 3, pp. 235--249. 2002.



R.T. Whitaker, J. Gregor. “A Maximum Likelihood Surface Estimator for Dense Range Data,” In IEEE Trans. Pattern Anal. & Mach. Intel., pp. 1372--1387. 2002.



R.T. Whitaker, E. L. Valdes-Juarez. “On the Reconstruction of Height Functions and Terrain Maps from Dense Range Data,” In IEEE Trans. Imag. Proc., Vol. 11, No. 7, pp. 704--716. 2002.



D. Xiu, G.E. Karniadakis. “The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations,” In SIAM Journal on Scientific Computing, Vol. 24, No. 2, pp. 619--644. 2002.
DOI: 10.1137/S1064827501387826

ABSTRACT

We present a new method for solving stochastic differential equations based on Galerkin projections and extensions of Wiener's polynomial chaos. Specifically, we represent the stochastic processes with an optimum trial basis from the Askey family of orthogonal polynomials that reduces the dimensionality of the system and leads to exponential convergence of the error. Several continuous and discrete processes are treated, and numerical examples show substantial speed-up compared to Monte Carlo simulations for low dimensional stochastic inputs.

Keywords: polynomial chaos, Askey scheme, orthogonal polynomials, stochastic differential equations, spectral methods, Galerkin projection