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Computer-aided diagnosis system for coronary artery stenosis using a neural network

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.