Knowledge-based boundary detection applied to cardiac magnetic resonance image sequences

摘要

The authors describe a knowledge-based system for detecting the interior and exterior boundaries of the left ventricle (LV) from time-varying cross-sectional images on the beating heart obtained noninvasively by magnetic resonance imaging (MRI). The goal is a system for automatically classifying and measuring cardiac function through estimates of LV wall thickness, wall motion, etc. This knowledge-based system makes use of the Dempster and Shafer (D/S) theory to manage the knowledge. The theory is also used to control the flow of system information for more efficient use of limited computational resources and memory space.