Medical diagnosis system using the intelligent fuzzy systems

Yasue Mitsukura, Kensuke Mitsukura, Minoru Fukumi, Norio Akamatsu, Witold Pedrycz

研究成果: Article

1 引用 (Scopus)

抄録

Recently in the world, 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. By the way, 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. Furthermore, 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.

元の言語English
ページ(範囲)807-826
ページ数20
ジャーナルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3213
出版物ステータスPublished - 2004
外部発表Yes

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Left Ventricle
Fuzzy inference
Fuzzy systems
Intelligent Systems
Fuzzy Systems
Cardiac
Heart Ventricles
Muscle
Image processing
Neural networks
Imaging techniques
X rays
Processing
Cardiac muscle
Necessary
Fuzzy Inference
Diagnostic Imaging
Cardiac Catheterization
Japan
Cause of Death

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

これを引用

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AU - Mitsukura, Yasue

AU - Mitsukura, Kensuke

AU - Fukumi, Minoru

AU - Akamatsu, Norio

AU - Pedrycz, Witold

PY - 2004

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AB - Recently in the world, 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. By the way, 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. Furthermore, 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.

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KW - Contact points

KW - Fuzzy inference

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KW - The left ventricle's axis

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