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Proceedings Paper

Segmentation of medical images using explicit anatomical knowledge
Author(s): Laurie S. Wilson; Stephen Brown; Matthew S. Brown; Jeanne Young; Rongxin Li; Suhuai Luo; Lee Brandt
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Paper Abstract

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

Paper Details

Date Published: 8 July 1999
PDF: 14 pages
Proc. SPIE 3747, New Approaches in Medical Image Analysis, (8 July 1999); doi: 10.1117/12.351619
Show Author Affiliations
Laurie S. Wilson, CSIRO (Australia)
Stephen Brown, CSIRO (Australia)
Matthew S. Brown, Univ. of California/Los Angeles (United States)
Jeanne Young, CSIRO (Australia)
Rongxin Li, CSIRO (Australia)
Suhuai Luo, CSIRO (Australia)
Lee Brandt, CSIRO (Australia)


Published in SPIE Proceedings Vol. 3747:
New Approaches in Medical Image Analysis
Binh Pham; Michael Braun; Anthony John Maeder; Michael P. Eckert, Editor(s)

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