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Biomedical Computing

Biomedical computing combines the diagnostic and investigative aspects of biology and medical science with the power and problem-solving capabilities of modern computing. Computers are used to accelerate research learning, simulate patient behavior and visualize complex biological models.


Chris Johnson

Inverse Problems
Computational Electrophysiology

Rob MacLeod

Inverse Problems
Computational Electrophysiology

Jeff Weiss

Computational Biomechanics

Orly Alter

Computational Biology


Chris Butson

Deep Brain Simulation
Transcranial Magnetic Stimulation (TMS)


Associated Centers:

Publications in Biomedical Computing:

Finite Element Refinements for Inverse Electrocardiography: Hybrid-Shaped Elements, High-Order Element Truncation and Variational Gradient Operator
D.F. Wang, R.M. Kirby, C.R. Johnson. In Proceeding of Computers in Cardiology 2009, Park City, September, 2009.

Subject-specific, multiscale simulation of electrophysiology: a software pipeline for image-based models and application examples
R.S. MacLeod, J.G. Stinstra, S. Lew, R.T. Whitaker, D.J. Swenson, M.J. Cole, J. Krüger, D.H. Brooks, C.R. Johnson. In Philosophical Transactions of The Royal Society A, Mathematical, Physical & Engineering Sciences, Vol. 367, No. 1896, pp. 2293--2310. 2009.

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

Visual Analysis of Bioelectric Fields
X. Tricoche, R.S. MacLeod, C.R. Johnson. In Visualization in Medicine and Life Sciences, Mathematics and Visualization, Springer-Verlag, pp. 205--220. 2008.

CRA-NIH Computing Research Challenges in Biomedicine Workshop Recommendations
D. Reed, C.R. Johnson. Note: Computing Research Association (CRA), 2007.

A Tensor Higher-Order Singular Value Decomposition for Integrative Analysis of DNA Microarray Data From Different Studies,
L. Omberg, G.H. Golub, O. Alter. In Proceedings of the National Academy of Sciences, Vol. 104, No. 47, Proceedings of the National Academy of Sciences, pp. 18371–-18376. November, 2007.
DOI: 10.1073/pnas.0709146104

Genomic Signal Processing: From Matrix Algebra to Genetic Networks
O. Alter. In Microarray Data Analysis: Methods in Molecular Biology, Vol. 377, Edited by M.J. Korenberg, Humana Press, Totowa, pp. 17--59. 2007.
DOI: 10.1007/978-1-59745-390-5_2

BioMesh3D: A Meshing Pipeline for Biomedical Models
SCI Institute Technical Report, M. Callahan, M.J. Cole, J.F. Shepherd, J.G. Stinstra, C.R. Johnson. No. UUSCI-2007-009, University of Utah, 2007.

Hexahedral Mesh Generation for Biomedical Models in SCIRun
SCI Institute Technical Report, J.F. Shepherd, C.R. Johnson. No. UUSCI-2007-008, University of Utah, 2007.

A Meshing Pipeline for Biomedical Computing
M. Callahan, M.J. Cole, J.F. Shepherd, J.G. Stinstra, C.R. Johnson. In Engineering with Computers, Special Issue on Computational Bioengineering, pp. (in press). 2007.

Discovery of Principles of Nature from Mathematical Modeling of DNA Microarray Data
O. Alter. In Proceedings of the National Academy of Sciences, Vol. 103, No. 44, Proceedings of the National Academy of Sciences, pp. 16063--16064. October, 2006.
DOI: 10.1073/pnas.0607650103

Singular Value Decomposition of Genome-Scale mRNA Lengths Distribution Reveals Asymmetry in RNA Gel Electrophoresis Band Broadening,
O. Alter, G. H. Golub. In Proceedings of the National Academy of Sciences, Vol. 103, No. 32, Proceedings of the National Academy of Sciences, pp. 11828--11833. July, 2006.
DOI: 10.1073/pnas.0604756103

Biomedical Computing and Visualization
C.R. Johnson, D.M. Weinstein. In Proceedings of the Twenty-Ninth Australasian Computer Science Conference (ACSC2006): Conferences in Research and Practice in Information Technology (CRPIT), Hobart, Australia, Vol. 48, Edited by Vladimir Estivill-Castro and Gill Dobbie, pp. 3-10. 2006.

Computational Methods and Software for Bioelectric Field Problems
C.R. Johnson. In Biomedical Engineering Handbook, 2nd Edition, Vol. 1, Ch. 23, Edited by J.D. Bronzino, CRC Press, Boca Raton, pp. 1--23. 2006.

Controlled Support MEG Imaging
S. Nagarajan, O. Portniaguine, D. Hwang, C.R. Johnson, K. Sekihara. In NeuroImage, Vol. 15;33, No. 3, pp. 878--885. 2006.

Reconstructing the Pathways of a Cellular System from Genome-Scale Signals by Using Matrix and Tensor Computations,
O. Alter, G.H. Golub. In Proceedings of the National Academy of Sciences, Vol. 102, No. 49, Proceedings of the National Academy of Sciences, pp. 17559--17564. November, 2005.
DOI: 10.1073/pnas.0509033102

Influence of Stochastic Organ Conductivity in 2D ECG Forward Modeling: A Stochastic Finite Element Study
S.E. Geneser, S. Choe, R.M. Kirby, R.S. MacLeod. In Proceedings of The Joint Meeting of The 5th International Conference on Bioelectromagnetism and The 5th International Symposium on Noninvasive Functional Source Imaging within the Human Brain and Heart, pp. 5528--5531. 2005.

Computational Simulation of Penetrating Trauma in Biological Soft Tissues Using the Material Point Method
I. Ionescu, J. Guilkey, M. Berzins, R.M. Kirby, J.A. Weiss. In Proceedings, Medicine Meets Virtual Reality, Vol. 13, Edited by James D Westwood et al., IOS Press, pp. 213--218. 2005.
ISBN: 1-58603-498-7

Influence of Local and Remote White Matter Conductivity Anisotropy for a Thalamic Source on EEG/MEG Field and Return Current Computation
C. H. Wolters, A. Anwander, X. Tricoche, S. Lew, C.R. Johnson. In Int.Journal of Bioelectromagnetism, Vol. 7, No. 1, pp. 203--206. 2005.

Advanced Modeling and Visualization of Cardiothoracic Electrical Fields
F. Sachse, M. Cole, R.M. Kirby, X. Tricoche, C.R. Johnson. In Proceedings of 13th Medicine Meets Virtual Reality (MMVR13), 2005.