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Proceedings Paper

Computer-aided diagnosis system for coronary artery stenosis using a neural network
Author(s): Kenji Suzuki; Isao Horiba; Noboru Sugie; Michio Nanki
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Paper Abstract

We have developed a new computer-aided diagnosis system for coronary artery stenosis, which can learn medical doctors' clinical experiences and medical knowledge. In order to develop such a system, we have employed a multilayer neural network (NN). The NN has the capability to learn experts' experiences and knowledge. The proposed system consists of (a) automatic vessel tracking, (b) automatically extraction of the edges of the vessel, and (c) estimation of stenosis based on the NN. In order to evaluate the performance of the proposed system, two experiments with the phantoms and clinical images were performed. The stenoses estimated by the proposed system agreed well with not only the stenoses based on the actual measurement of the phantoms but also those diagnosed by a medical specialist from coronary arteriograms. The experimental results have shown that the proposed system has the capability to learn medical doctors' clinical experiences and medical knowledge. The proposed system has been proved to be useful to aid to diagnose coronary artery stenosis.

Paper Details

Date Published: 3 July 2001
PDF: 12 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431066
Show Author Affiliations
Kenji Suzuki, Aichi Prefectural Univ. (Japan)
Isao Horiba, Aichi Prefectural Univ. (Japan)
Noboru Sugie, Meijo Univ. (Japan)
Michio Nanki, Chubu Rosai Hospital (Japan)

Published in SPIE Proceedings Vol. 4322:
Medical Imaging 2001: Image Processing
Milan Sonka; Kenneth M. Hanson, Editor(s)

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