Medical image recognition based on Dempster-Shafer reasoning

Shiuh Yung Chen*, Wei Chung Lin, Chin Tu Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherPubl by Int Soc for Optical Engineering
Number of pages12
ISBN (Print)0819408042
StatePublished - 1992
EventMedical Imaging VI: Image Processing - Newport Beach, CA, USA
Duration: Feb 24 1992Feb 27 1992

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherMedical Imaging VI: Image Processing
CityNewport Beach, CA, USA

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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