A Genetic-Algorithm-Based Method for Optimization of Fuzzy Reasoning and Its Application to Classification of Heart Disease from Ultrasonic Images (特集:画像処理技術の新産業応用) A Genetic-Algorithm-Based Method for Optimization of Fuzzy Reasoning and Its Application to Classification of Heart Disease from Ultrasonic Images

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This paper describes a method for optimizing the parameters of fuzzy rules using genetic algorithms (GAs) for classification of myocardial heart disease from ultrasonic images. Gaussian-distributed membership functions (GDMFs) constructed from the texture features inherent in the ultrasound images are used, and the coefficients acted as a set of parameters to adjust the magnitudes of the standard deviations of the GDMFs are employed. Optimal coefficients are determined through training process using the GA. The GA-based fuzzy classifier is used to discriminate two sets of echocardiographic images, namely, normal case (23 samples) and abnormal case (22 samples), diagnosed by a highly trained physician. The results of our experiments are very promising. In the best case, we achieve a classification rate of 95.8%. The results indicate that the method has potential utility for computer-aided diagnosis of myocardial heart disease.

収録刊行物

  • 電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society  

    電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society 119(1), 30-36, 1999-01 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10002727779
  • NII書誌ID(NCID)
    AN10012320
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    09136339
  • NDL 記事登録ID
    970642
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-1608
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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