Presentation 2001/1/18
Computerized classification of liver disease in MRI using artificial neural network
Xuejun Zhang, Masayuki Kanematsu, Hiroshi Fujita, Takeshi Hara, Hiroaki Hoshi,
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Abstract(in English) To establish a computer-aided diagnosis(CAD) system for distinguishing the categories of liver lesions in MR images, we developed a system named"LiverANN"based on artificial neural network(ANN) technique. The homogeneity of T2-weighted MRI and the brightness of four MRI phases were evaluated into numerical data as the teacher signals of the ANN. The outputs were the 5 categories of hepatic disease. The initial result showed that the LiverANN classified 5 types of liver lesions with sensitivity of 93%. The LiverANN program demonstrated its ability to provide a radiologist with referential opinion during the diagnosis procedure.
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Keyword(in English) MRI / liver lesion / artificial neural network / computer-aided diagnosis(CAD)
Paper # MI2000-62
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Committee MI
Conference Date 2001/1/18(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Computerized classification of liver disease in MRI using artificial neural network
Sub Title (in English)
Keyword(1) MRI
Keyword(2) liver lesion
Keyword(3) artificial neural network
Keyword(4) computer-aided diagnosis(CAD)
1st Author's Name Xuejun Zhang
1st Author's Affiliation Department of Information Science, Faculty of Engineering Gifu University()
2nd Author's Name Masayuki Kanematsu
2nd Author's Affiliation Department of Radiology, Gifu University School of Medicine
3rd Author's Name Hiroshi Fujita
3rd Author's Affiliation Department of Information Science, Faculty of Engineering Gifu University
4th Author's Name Takeshi Hara
4th Author's Affiliation Department of Information Science, Faculty of Engineering Gifu University
5th Author's Name Hiroaki Hoshi
5th Author's Affiliation Department of Radiology, Gifu University School of Medicine
Date 2001/1/18
Paper # MI2000-62
Volume (vol) vol.100
Number (no) 596
Page pp.pp.-
#Pages 6
Date of Issue