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Quantitative Diagnosis on Magnetic Resonance Images of Chronic Liver Disease Using Neural Networks
Shin'ya YOSHINO Akira KOBAYASHI Takashi YAHAGI Hiroyuki FUKUDA Masaaki EBARA Masao OHTO
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1994/11/25
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and Its Applications)
Category: Neural Network and Its Applications
computer–aided diagnosis, image texture, chronic liver disease, neural network applications, MRI,
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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.