Model-based analysis of cardiac motion from tagged MRI data

We develop a new method for analyzing the motion of the left ventricle (LV) of a heart from tagged MRI data. Our technique is based on the development of a new class of physics-based deformable models whose parameters are functions allowing the definition of new parameterized primitives and parameterized deformations. These parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional twisting. Furthermore, these parameters require no complex postprocessing in order to be used by a physician. Using a physics-based approach, we convert these geometric models into deformable models that deform due to forces exerted from the datapoints and conform to the given dataset. We present experiments involving the extraction of shape and motion of the LV from MRISPAMM data based on a few parameter functions. Furthermore, by plotting the variations over time of the extracted model parameters from normal and abnormal heart data we are able to characterize quantitatively their differences. Comments Copyright 1994 IEEE. Reprinted from Proceedings of the IEEE Seventh Symposium Computer-Based Medical Systems, July 1994 pages 40-45. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/hms/105 Model-based Analysis of Cardiac Motion from Tagged MRI Data Jinah Park’, Dimitri Metaxas’, Alistair Young2 and Leon Axel2 ‘Department of Computer & Information Science University of Pennsylvania Philadelphia PA 19 104-6389 *Department of Radiology University of Pennsylvania Philadelphia PA 19104