Dempster-S hafer Reasoning for Medical Image Recognit ion

Dempster-Shafer (0-S) theory has been proposed to represent and propagate uncertain knowledge in exped systems. In this paper, we describe a medical image recognition system whose reasoning module employs the profound features of 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, T1- 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.

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