Quantitative Diagnosis on Magnetic Resonance Images of Chronic Liver Disease Using Neural Networks (Special Section on Nonlinear Theory and Its Applications)

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概要

• 論文の詳細を見る

• We have classified parenchymal echo patterns of cirrhotic liver into 3 types, according to the size of hypoechoic nodular lesions. We have been studying an ultrasonic image diagnosis system using the three-layer back-propagation neural network. In this paper, we will describe the applications of the neural network techniques for recognizing and classifying chronic liver disease, which use the nodular lesions in the Proton density and T2-weighed magnetic resonance images on the gray level of the pixels in the region of interest.

• 社団法人電子情報通信学会の論文
• 1994-11-25

著者

• Yoshino Shin-ya

  Faculty Of Informatics Teikyo University Of Technology

• FUKUDA Hiroyuki

  First Department of Medicine, School of Medicine, Chiba University

• EBARA Masaaki

  First Department of Medicine, School of Medicine, Chiba University

• FUKUDA Hiroyuki

  Biodevelopment Division, Central Institute, Nagoya Seiraku Co., Ltd.

• Ebara Masaaki

  Chiba University School Of Medicine

• Ebara Masaaki

  First Department Of Medicine Chiba University School Of Medicine

• Yahagi T

  Graduate School Of Science And Technology Chiba University

• OHTO Masao

  First Department of Internal Medicine, Chiba University School of Medicine

• Fukuda Hiroyuki

  Biodevelopment Division Central Institute Nagoya Seiraku Co. Ltd.

• YAHAGI Takashi

  Faculty of Engineering, Chiba University

• Ohto M

  Chiba Univ. School Of Medicine Chiba Jpn

• Ohto Masao

  First Department Of Internal Medicine Chiba University

• KOBAYASHI Akira

  Faculty of Fundamental Engineering, Osaka University

• Kobayashi A

  Kisarazu National College Of Technology

• Yahagi Takashi

  Faculty Of Engineering Department Of Information And Computer Sciences Chiba University

• Yahagi Takashi

  Faculty Of Engineering Chiba University

• Kobayashi Akira

  Faculty Of Agriculture Iwate University

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