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

1992


 D. Forslunk, P. Hinker, C.D. Hansen, W.St. John, S. Tenbrink, J. Brewton. “High-speed Networks, Visualization and Massive Parallelism in the Advanced Computing Laboratory,” In Computing Systems in Engineering, Vol. 3, No. 1-4, 1992.


C.D. Hansen, P. Hinker. “Massively Parallel Isosurface Extraction,” In Visualization 1992, Boston, Ma., pp. 77--83. October, 1992.


C.D. Hansen, D. Butler. “Visualization '91 Workshop Report: Scientific Visualization Environments,” In Computer Graphics Quarterly, Vol. 26, No. 3, pp. 213--216. August, 1992.


C.R. Johnson, R.S. MacLeod, P.R. Ershler. “A Computer Model for the Study of Electrical Current Flow in the Human Thorax,” In Computers in Biology and Medicine, Vol. 22, No. 5, Elsevier BV, pp. 305--323. 1992.

ABSTRACT

Electrocardiography has played an important role in the detection and characterization of heart function, both in normal and abnormal states. In this paper we present an inhomogeneous, anisotropic computer model of the human thorax for use in electrocardiography with emphasis on the calculation of transthoracic potential and current distributions. Knowledge of the current pathways in the thorax has many applications in electrocardiography and has direct utility in studies pertaining to cardiac defibrillation, forward and inverse problems, impedance tomography, and electrode placement in electrocardiography.

Keywords: scalar field methods, vector field methods, tensor field methods, cardiac heart, scientific visualization


 C.R. Johnson, R.S. MacLeod, M.A. Matheson. “Computer Simulations Reveal Complexity of Electrical Activity in the Human Thorax,” In Computers in Physics, Vol. 6, pp. 230--237. May/June, 1992.


C.R. Johnson, R.S. MacLeod, A. Dutson. “Effects of Anistropy and Inhomogeneity on Electrocardiographic Fields: A Finite Element Study,” In Engineering in Medicine and Biology Society 14th Annual International Conference, IEEE Press, pp. 2009--2010. 1992.


C.R. Johnson, R.S. MacLeod. “Computational Studies of Forward and Inverse Problems in Electrocardiology,” In Biomedical Modeling and Simulation, Edited by J. Eisenfeld and D.S. Levine and M. Witten, Elsevier Science Publishers, Elsevier, Amsterdam pp. 283--290. 1992.


C.R. Johnson, R.S. MacLeod. “Nonuniform Spatial Mesh Adaption Using a Posteriori Error Estimate: Applications to Forward and Inverse Problems,” In Adaptive Methods for Partial Differential Equations, Vol. 14, Edited by J.E. Flaherty and M.S. Shephard, Elsevier, pp. 311--326. 1992.


J. Lawson, M. Berzins. “Towards an Automatic Algorithm for the Numerical Solution of Parabolic P.D.E.s Using the Method of Lines,” In proc of I.M.A. 1989 O.D.E. Conference, Edited by I. Gladwell and J. Cash and A. Iserles, Oxford University Press, pp. 309--322. 1992.
ISBN: 0-19-853659-3


R.S. MacLeod, C.R. Johnson, M.A. Matheson. “Visualization Tools for Computational Electrocardiology,” In Visualization in Biomedical Computing, pp. 433--444. 1992.


R.S. MacLeod, C.R. Johnson, M.A. Matheson. “Visualization of cardiac bioelectricity --- a case study,” In IEEE Visualization `92, pp. 411--418. 1992.


R.S. MacLeod, C.R. Johnson, M.J. Gardner B.M.. “Localization of Ischemia during Coronary Angioplasty using Body Surface Potential Mapping and an Electrocardiographic Inverse Solution,” In Computers in Cardiology, IEEE Press, pp. 251--254. 1992.


A. Pascucci, V. Pascucci. “Uso del calcolatore nella produzione, elaborazione ed archiviazione di proiezioni parallele (Using the computer for generating, processing and archiving parallel projections),” In Atti del convegno L'immagine nel rilievo, Edited by C. Cundari, Gangemi, pp. 540--561. 1992.


C. Walshaw, M. Berzins. “Dynamic Load Balancing for PDE Solvers on Adaptive Unstructured Meshes,” School of Computer Studies Research Report, No. 92.32, University of Leeds, December, 1992.


J.M. Ware, M. Berzins. “Finite Volume Techniques for Time-dependent Fluid-Flow Problems,” In Advances in Comp. Meths. for P.D.E.s VII, New Jersey, Rutgers Univ., pp. 794--798. 1992.


C. Williams, J. Rasure, C.D. Hansen. “The State of the Art of Visual Languages for Visualization,” In Visualization 1992, Boston, Ma., pp. 202--209. October, 1992.

1991


 M. Berzins, P. Baehmann, J.E. Flaherty, J. Lawson. “Towards An Automated Finite Element Solver for Time-Dependent Fluid-Flow Problems,” In MAFELAP 90, Edited by J.R. Whiteman, Academic Press, pp. 181--188. 1991.


M. Berzins, P.M. Dew. “Chebyshev Polynomial Software for Elliptic-Parabolic Systems of P.D.E.s,” In A.C.M. Transactions on Mathematical Software, Vol. 17, No. 2, pp. 178--206. June, 1991.

ABSTRACT

PDECHEB is a FORTRAN 77 software package that semidiscretizes a wide range of time dependent partial differential equations in one space variable. The software implements a family of spatial discretization formulas, based on piecewise Chebyshev polynomial expansions with C0 continuity. The package has been designed to be used in conjunction with a general integrator for initial value problems to provide a powerful software tool for the solution of parabolic-elliptic PDEs with coupled differential algebraic equations. Examples are provided to illustrate the use of the package with the DASSL d.a.e, integrator of Petzold [18].


 M. Berzins. “Balancing Space and Time Errors for Spectral Methods used with the Method of Lines for Parabolic equations,” 1991.


C.D. Hansen, S. Tenbrink. “The Impact of Gigabit Networking on Imaging,” In Digital Imaging, Anaheim, Ca., pp. 191--194. April, 1991.