National Changhua University of Education Institutional Repository : Item 987654321/11736
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 6498/11670
造访人次 : 26021709      在线人数 : 233
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 进阶搜寻


题名: Using a fuzzy engine and complete set of features for hepatic diseases diagnosis: Integrating contrast and non-contrast CT images
作者: Chen, E.-L.;Chung, Yi-Nung;Chung, P.-C.;Tsai, H.-M.;Huang, Y.-S.
贡献者: 電機工程學系
关键词: Contrast-enhanced CT;Fuzzy-diagnosis engine;Hepatic disease diagnosis;Non-contract CT
日期: 2001-08
上传时间: 2012-07-02T02:06:18Z
出版者: World Scientific Publishing Co.
摘要: In the diagnosis of hepatic diseases, "Contrast-Enhanced Computerized Tomography" (CECT) and "Non-Contrast CT" (NCT) are usually simultaneously adopted. In this paper, a system consisting of a fuzzy diagnosis engine and a feature quantizer, which extracts hepatic features from CECT and NCT images is proposed for assisting hepatic disease diagnosis. Compared with existing methods this paper differs in two folds. First a more complete features set composed of not only lesion textures, but also lesion morphological structure and lesion contrast to normal tissues is used. These features are described through mathematical models built inside the feature quantizer and served as the input of fuzzy diagnosis engine. Second, because of the use of the fuzzy diagnosis engine, the system is intrinsically with the capability of storing rules and may infer and adapt its rules according to learning data. Furthermore, uncertainty associated with disease diagnosis can be appropriately taken into considerations. The system has been tested using 131 sets of image data, which are to be classified into 4 types of diseases: liver cyst, hepatoma, cavernous hemagioma and metastatic liver tumor. Experimental results indicate that among these test data 78% of them are accurately classified as one type, while the remaining 22% of data are classified as more than one types of diseases. Even so, within these 22% of multiple-classified data, the correct type is always included in the output in each test, showing a promise of the system.
關聯: Biomedical Engineering - Applications, Basis and Communications, 13(4): 159-167
显示于类别:[電機工程學系] 期刊論文


档案 大小格式浏览次数



DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈