NDLI: Discrimination of Liver Diseases from CT Images Based on Gabor Filters

Content Provider	IEEE Xplore Digital Library
Author	Chien-Cheng Lee Sz-Han Chen Hong-Ming Tsai Pau-Choo Chung Yu-Chun Chiang
Copyright Year	2006
Description	Author affiliation: Dept. of Commun. Eng., Yuan Ze Univ., Chung-li (Chien-Cheng Lee; Sz-Han Chen)
Abstract	In this paper, a liver disease diagnosis based on Gabor filters is proposed. Three kinds of liver diseases are identified: cyst, hepatoma and cavernous hemangioma. The diagnosis scheme includes two steps: features extraction and classification. The features derived from Gabor filters are obtained from the ROIs among the normal and abnormal CT images. In the classification step the SVM classifier is used to discriminate the different liver disease types. Finally the receiver operating characteristic curve is employed to evaluate the performance of the diagnosis system. The effectiveness of the proposed method is demonstrated through experimental results on CT images including 76 liver cysts, 30 hepatomas, and 40 cavernous hemangiomas. From the results, we can observe that the discrimination rate of cyst is higher than the other diseases, and the classification accuracy decreases slightly between cavernous hemangiomas and hepatomas. However, a normal region can be discriminated from all of these diseases entirely
Starting Page	203
Ending Page	206
File Size	514692
Page Count	4
File Format	PDF
ISBN	0769525171
ISSN	10637125
DOI	10.1109/CBMS.2006.77
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Liver diseases Computed tomography Gabor filters Feature extraction Support vector machines Support vector machine classification Computer aided diagnosis Image texture analysis Biomedical imaging Medical diagnostic imaging
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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