Dempster-Shafer reasoning for medical image recognition

Abstract

A medical image recognition system is described whose reasoning module uses the features of the Dempster-Shafer (D-S) theory such as compatible frames and multivariate belief functions. The proposed expert system, which is based on the blackboard architecture, is capable of mimicking the reasoning process of a human expert in dividing a set of correlated X-ray CT and T-1 and T2-weighted MR images into semantically meaningful entities. In the blackboard-oriented system, different kinds of evidence provided by various knowledge sources form a hierarchy of evidential space to which D-S theory is applied. Several experimental results are given to illustrate the performance of the proposed system.<>