Intelligent medical diagnosis system using the fuzzy and neural networks

• Published in: IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04 Vol. 2; pp. 550 - 554 Vol.2
• Main Authors: Mitsukura, Y., Miyata, K., Mitsukura, K., Fukumi, M., Akamatsu, N., Pedrycz, W.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway NJ IEEE 2004
• Subjects: Applied sciences; Artificial intelligence; Cardiac disease; Catheterization; Computer science; control theory; systems; Exact sciences and technology; Fuzzy neural networks; Fuzzy systems; Intelligent networks; Intelligent systems; Medical diagnosis; Muscles; Neural networks; Pattern recognition. Digital image processing. Computational geometry; X-ray imaging; Human; Image processing; X ray radiography; Inference; Neural network; Fuzzy neural nets; Left ventricle; Automatic processing; Fuzzy logic; Imaging; Diagnosis; Artificial intelligence; Medical application; Intelligent system
• ISBN: 9780780383760; 0780383761
• DOI: 10.1109/NAFIPS.2004.1337360

Various imaging diagnostic technologies are studied and used in practical. It is necessary to develop the automatic diagnosing processing system for detecting the internal organ. In Japan, cardiac disease is one of the most common cause of death. Therefore, it is necessary to measure cardiac function quantitatively and evaluate the motions of continuous cardiac muscle. Moreover, we propose the developing the system to detect the asynergy in the left ventricle. The processing images are X-ray photograms of the left ventricle by cardiac catheterization. In this paper, we propose the detection system of the asynergy in the left ventricle by using neural networks and the fuzzy inference. Furthermore, in order to show the effectiveness of the proposed method, we show the simulation example by using the real data.