Segmentation of medical images using explicit anatomical knowledge

Laurie S. Wilson; Stephen Brown; Matthew S. Brown; Jeanne Young; Rongxin Li; Suhuai Luo; Lee Brandt

doi:10.1117/12.351619

8 July 1999 Segmentation of medical images using explicit anatomical knowledge

Laurie S. Wilson, Stephen Brown, Matthew S. Brown, Jeanne Young, Rongxin Li, Suhuai Luo, Lee Brandt

Proceedings Volume 3747, New Approaches in Medical Image Analysis; (1999) https://doi.org/10.1117/12.351619
Event: Research Workshop on Automated Medical Image Analysis, 1998, Ballarat, Australia

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.

Citation Download Citation

Laurie S. Wilson, Stephen Brown, Matthew S. Brown, Jeanne Young, Rongxin Li, Suhuai Luo, and Lee Brandt "Segmentation of medical images using explicit anatomical knowledge", Proc. SPIE 3747, New Approaches in Medical Image Analysis, (8 July 1999); https://doi.org/10.1117/12.351619

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