Physiome model based state-space framework for cardiac kinematics recovery

Authors:
Ken C. L. Wong;Heye Zhang;Huafeng Liu;Pengcheng Shi
Affiliations:
Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong;Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong;State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hanzhou, China;Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2006

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Abstract

In order to more reliably recover cardiac information from noise-corrupted patient-specific measurements, it is essential to employ meaningful a priori constraining models and adopt appropriate optimization criteria to couple the models with the measurements. While biomechanical models have been extensively used for myocardial motion recovery with encouraging results, the passive nature of such constraints limits their ability to fully count for the deformation caused by active forces of the myocytes. To overcome such limitations, we propose to adopt a cardiac physiome model as the prior constraint for heart motion analysis. The model is comprised of a cardiac electric wave propagation model, an electromechanical coupling model, and a biomechanical model, and thus more completely describes the macroscopic cardiac physiology. Embedded within a multiframe state-space framework, the uncertainties of the model and the patient-specific measurements are systematically dealt with to arrive at optimal estimates of the cardiac kinematics and possibly beyond. Experiments have been conducted on synthetic data and MR image sequences to illustrate its abilities and benefits.