Knowledge-based system for boundary detection of four-dimensional cardiac magnetic resonance image sequences

A strategy for a knowledge-based system to detect the interior and exterior boundaries of the left ventricle from time-varying cross-sectional images obtained by ECG-gated magnetic resonance imaging (MRI) is discussed. The system uses both fuzzy set theory and Dempster and Shafer theory to manage the knowledge and to control the flow of system information for more efficient use of limited computational resources and memory space. The key to the approach is that it performs edge detection on images through integration and unification of knowledge and information from edge candidates on all the slices and phases of the acquired cardiac MRI dataset. The analysis system does not base decisions on individual measurements, but on consensus opinions by combining many knowledge sources, some of which may not be completely accurate.