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Proceedings Paper

Medical image recognition based on Dempster-Shafer reasoning
Author(s): Shiuh-Yung James Chen; Wei-Chung Lin; Chin-Tu Chen
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Paper Abstract

In this paper, we present the basic components of the prototype of an expert system that is capable of recognizing major brain structures given a set of integrated brain images. The proposed medical image understanding system, which is based on the blackboard architecture, employs the Dempster-Shafer (D-S) model as its inference engine to mimic the reasoning process of a human expert in the task of dividing a set of spatially correlated x ray CT, proton density (PD), and T2-weighted MR images into semantically meaningful entities and identifying these entities as respective brain structures. Within the framework of D-S reasoning, belief interval is adopted to represent the strengths of evidence and the likelihoods of hypotheses. By using the complicated blackboard-based architecture and D-S model, the proposed system can perform the task of recognition efficiently. Several experimental results are given to illustrate the performance of the proposed system.

Paper Details

Date Published: 1 June 1992
PDF: 12 pages
Proc. SPIE 1652, Medical Imaging VI: Image Processing, (1 June 1992); doi: 10.1117/12.59465
Show Author Affiliations
Shiuh-Yung James Chen, Univ. of Chicago (United States)
Wei-Chung Lin, Northwestern Univ. (United States)
Chin-Tu Chen, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 1652:
Medical Imaging VI: Image Processing
Murray H. Loew, Editor(s)

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