Mapping, modeling, and visual exploration of structure-function relationships in the heart

Authors:
R. L. Winslow;D. F. Scollan;J. L. Greenstein;C. K. Yung;W. Baumgartner, Jr.;G. Bhanot;D. L. Gresh;B. E. Rogowitz
Affiliations:
Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland;Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland;Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland;Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland;Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland;IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York;IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York;IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York
Venue:
IBM Systems Journal - Deep computing for the life sciences
Year:
2001

Citing 6
Cited 1

VODE: a variable-coefficient ODE solver

SIAM Journal on Scientific and Statistical Computing
Surface reconstruction from unorganized points

SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Simulating cardiac sinus and atrial network dynamics on the Connection Machine

Physica D
A semi-implicit numerical scheme for reacting flow: I. stiff chemistry

Journal of Computational Physics
A semi-implicit numerical scheme for reacting flow: II. stiff, operator-split formulation

Journal of Computational Physics
WEAVE: a system for visually linking 3-D and statistical visualizations, applied to cardiac simulation and measurement data

Proceedings of the conference on Visualization '00

Non-invasive method for patient-specific virtual heart based on fiber-fluid model

Journal of Mobile Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

It is becoming clear that the emergent, integrative behaviors of biological systems result from complex interactions between all system components, and that knowledge of each component is not sufficient to understand such behaviors. In this paper, we describe our approach to the integrative modeling of cardiac function. This approach spans multiple levels of biological analysis, ranging from subcellular to tissue. We have applied diverse analytical methods, including imaging techniques for measurement of anatomic structure and biophysical and biochemical responses of cells and tissue, parallel computing techniques for the numerical solution of large systems of model equations, and interactive visual exploration of model dynamic behavior.