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


J.D. Brederson, M. Ikits, C.R. Johnson, C.D. Hansen. “A Prototype System For Synergistic Data Display,” In IEEE Virtual Reality 2001, 2001.

C. DeTar, A.L. Fogelson, C.R. Johnson, C.A. Sikorski. “Computational Engineering and Science Program at the University of Utah,” In Proceedings of the International Conference on Computational Science (ICCS) 2001, San Francisco, Edited by V. Alexandrov and J. Dongarra and B. Juliano and R. Renner and K. Tan, pp. 1176--1185. May, 2001.

G. Higgins, B. Athey, J. Bassingthwaighte, J. Burgess, H. Champion, K. Cleary, P. Dev, J. Duncan, M. Hopmeier, D. Jenkins, C.R. Johnson, H. Kelly, R. Leitch, W. Lorensen, D. Metaxas, V. Spitzer, N. Vaidehi, K. Vosburgh, R. Winslow. “Modeling and Simulation in Medicine: Towards an Integrated Framework,” In Computer Aided Surgery, Vol. 6, No. 1, Note: Final report of the meeting of the same title held July 20-21, 2000, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA., 2001.
DOI: 10.1002/igs.1008

C.R. Johnson, D. Brederson, C.D. Hansen, M. Ikits, G. Kindlmann, Y. Livnat, S.G. Parker, D.M. Weinstein, R.T. Whitaker. “Computational Field Visualization,” In Computer Graphics, Vol. 35, No. 4, pp. 5--9. 2001.

C.R. Johnson, Y. Livnat, L. Zhukov, D. Hart, G. Kindlmann. “Computational Field Visualization,” In Mathematics Unlimited -- 2001 and Beyond, Vol. 2, Edited by B. Engquist and W. Schmid, Springer-Verlag, pp. 605--630. 2001.

C.R. Johnson, M. Mohr, U. Ruede, A. Samsonov, K. Zyp. “Multilevel Methods for Inverse Bioelelectric Field Problems,” In Lecture Notes in Computational Science and Engineering - Multiscale and Multiresolution Methods: Theory and Applications, Vol. 20, Edited by T.J. Barth and T.F. Chan and R. Haimes, Springer-Verlag Publishing, Heidelberg pp. 331--346. October, 2001.

C.R. Johnson. “Adaptive Finite Element and Local Regularization Methods for the Inverse ECG Problem,” In Inverse Problems in Electrocardiology, Advances in Computational Biomedicine, Vol. 5, Edited by Peter Johnston, WIT Press, pp. 51--88. 2001.

C.R. Johnson. “Computational Bioimaging for Medical Diagnosis and Treatment,” In Communications of the ACM, Vol. 44, No. 3, pp. 74--76. March, 2001.

Y. Livnat, C.D. Hansen, S.G. Parker, C.R. Johnson. “Isosurface extraction for large-scale datasets,” In Proceedings of Scientific Visualization -Dagstuhl`2000, Edited by F. Post, 2001.

J. McCorquodale, J.D. de St. Germain, S.G. Parker, C.R. Johnson. “The Uintah Parallelism Infrastructure: A Performance Evaluation on the SGI Origin 2000,” In Proceedings of The 5th International Conference on High-Performance Computing, Seattle, Mar, 2001.

M. Miller, C. Moulding, J. Dongarra, C.R. Johnson. “Grid-enabling Problem Solving Environments: A Case Study of SCIRun and Netsolv,” In Proceedings of The 5th International Conference on High-Performance Computing, 2001 Advanced Simulation Technologies Conference, Society for Modeling and Simulation International, pp. 98--103. April, 2001.

O. Portniaguine, D.M. Weinstein, C.R. Johnson. “Focusing Inversion of Electroencephalography and Magnetoencephalography Data,” In 3rd International Symposium On Noninvasive Functional Source Imaging, Journal of Biomedizinische Technik (special issue), Vol. 46, Innsbruck, Austria pp. 115--117. Sep, 2001.

R. Rawat, S.G. Parker, P.J. Smith, C.R. Johnson. “Parallelization and Integration of Fire Simulations in the Uintah PSE,” In Proceedings of the Tenth SIAM Conference on Parallel Processing for Scientific Computing, Portsmouth, Virginia, March 12-14, 2001.

R. Van Uitert, D. Weinstein, C.R. Johnson, L. Zhukov. “Finite Element EEG and MEG Simulations for Realistic Head Models: Quadratic vs. Linear Approximations,” In Biomed. Technik, Vol. 46, pp. 32--34. 2001.

R. Westermann, C.R. Johnson, T. Ertl. “Topology Preserving Smoothing of Vector Fields,” In IEEE Trans. Vis & Comp. Graph., Vol. 7, No. 3, pp. 222--229. 2001.
DOI: 10.1109/2945.942690


Proposes a technique for topology-preserving smoothing of sampled vector fields. The vector field data is first converted into a scalar representation in which time surfaces implicitly exist as level sets. We then locally analyze the dynamic behavior of the level sets by placing geometric primitives in the scalar field and by subsequently distorting these primitives with respect to local variations in this field. From the distorted primitives, we calculate the curvature normal and we use the normal magnitude and its direction to separate distinct flow features. Geometrical and topological considerations are then combined to successively smooth dense flow fields, at the same time retaining their topological structure.

Keywords: vector field methods, ip image processing signal processing, surface processing, ncrr

L. Zhukov, D.M. Weinstein, C.R. Johnson, R.S. Macleod. “Spatio-temporal Multi-dipole Source Localization Using ICA and Lead-Fields in FEM Head Models,” In Proceedings of the IEEE Engineering in Medicine and Biology Society 23rd Annual International Conference, Istanbul, Turkey Oct, 2001.


R. Bramley, C.R. Johnson, D. Gannon, J. Reynders, T. Hewett, J. Rice. “Workshop on Scientific Knowledge, Information and Computing, SIDEKIC 98,” In Enabling Technologies for Computational Science, Springer, pp. 19-32. 2000.
DOI: 10.1007/978-1-4615-4541-5_2


On 4-5 December 1998 researchers from several universities, national laboratories, software companies, and government funding agencies met at Santa Fe, NM for the 1998 Scientific Integrated Development Environments for Knowledge, Information, and Computing Workshop. The purpose of this meeting was to summarize the state-of-the-art in the area of problem-solving environments (PSEs) for scientific and engineering computation, and to map out directions for future research in the area. This report presents some of the results from the meeting and recommends promising areas for further work. This report begins with a justification of the need for PSEs, which are also commonly called computational workbenches. Next a listing of characteristics that many PSEs share is presented, followed by a small sample listing of current systems. Design goals and future directions, with an emphasis on research issues, are outlined, followed by summary findings and conclusions.

J.D. Brederson, M. Ikits, C.R. Johnson, C.D. Hansen, J.M. Hollerbach. “The Visual Haptic Workbench,” In Proceedings of the Fifth PHANToM Users Group Workshop, pp. 46--49. October, 2000.

A. Deshmukh, C.C. Douglas, M. Ball, R.E. Ewing, C.R. Johnson, C. Kesselman, C. Lee. “Dynamic Data Driven Application Systems: Creating a dynamic and symbiotic coupling of application/simulations with measurements/experiments,” Note: 28 pages, Edited by W. Powell, R. Sharpley, National Science Foundation, 2000.

J.D. de St. Germain, J. McCorquodale, S.G. Parker, C.R. Johnson. “Uintah: A Massively Parallel Problem Solving Environment,” In Ninth IEEE International Symposium on High Performance and Distributed Computing, IEEE, Piscataway, NJ, pp. 33--41. Nov, 2000.