Paper Abstract and Keywords |
Presentation |
2015-03-02 11:30
Information fusion for computer-aided diagnosis of liver fibrosis
-- Integration of shape information into conventional blood test based diagnosis -- Yuto Masaki, Futoshi Yokota, Yoshito Otake (NAIST), Masatoshi Hori (Osaka Univ.), Toshiyuki Okada (Tsukuba Univ.), Noriyuki Tomiyama, Yoshinobu Sato (NAIST) MI2014-64 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Liver biopsy currently used for a definitive diagnosis of liver fibrosis is invasive and causes inconvenience to the patient, thus non-invasive techniques are preferable. Previous works reported classification and estimation method to diagnose liver fibrosis using information of blood test only and the liver shape only acquired from CT image, respectively. The purpose of this study was to improve classification accuracy by integrating the information of shape and blood test. In this study, we built support vector machine from integrating information of shape and blood test. We performed the classification of liver fibrosis presence and evaluated area under the curve (AUC). We conducted one hundred times 3-fold cross-validation, and founded that the average AUC is shown to be 0.990±0.007. The integration of the both information further improved the AUC significantly (p<0.01). |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
information fusion / statistical shape model / support vector machine / liver fibrosis / blood test / computer-aided diagnosis / / |
Reference Info. |
IEICE Tech. Rep., vol. 114, no. 482, MI2014-64, pp. 59-62, March 2015. |
Paper # |
MI2014-64 |
Date of Issue |
2015-02-23 (MI) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2014-64 |
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