Staging the Hepatic Fibrosis on CT Images: Optimizing the Slice Thickness and Texture Features
(0) Texture features are useful in analyzing the hepatic fibrosis on CT images, however properly selecting features and slice thickness is still uncertain. In this paper, five types of slice thickness and 15 features extracted from co-occurrence matrix are investigated to select the optimal parameters. Each combination will be checked by using SVM (Support Vector machine) with leave-one-case-out method. 149 cases including 6 grades of hepatic fibrosis are acquired by CT scanner and divided into two groups: normal & mild fibrosis vs severe fibrosis & typical cirrhosis. Iteration test on all of the subsets indicates that 5 to 7 features with slice thickness of 1.25mm is the optimal combination with relative higher accuracy in classification of fibrosis.
Wendong Li Yufan Zeng Xuejun Zhang Yu Huang Liling Long Hiroshi Fujita
School of Computer, Electronics and Information, Guangxi University, Guangxi 530004, China Department of Radiology, Guangxi University School of Medicine, Guangxi 530022, China. H. Fujita is Department of Intelligent Image Information,Gifu University,Gifu 501-1194,Japan
国际会议
2011 International Symposium on Bioelectronics and Bioinformatics(第二届国际生物医学电子学与生物信息学学术会议 ISBB 2011)
苏州
英文
267-270
2011-11-03（万方平台首次上网日期，不代表论文的发表时间）