Computer-Aided Diagnosis of Liver Cirrhosis Based on Multiple Statistical Shape Models
Mei Uetani, Tomoko Tateyama, Shinya Kohara, Xian‐Hua Han, Y.W Chen, Shuzo Kanasaki, Akira Furukawa, X Wei · Advances in computer science research · 2015
In the fields of medical image analysis and computational anatomy, statistical shape models (SS Ms) is usually used for organ segmentation; SS Ms are statistically constructed from a population of organs.In this paper, we focus on the application of SS Ms for the computer-aided diagnosis of cirrhotic livers.Since chronic liver diseases or cirrhosis will cause significant morphological changes on both the liver and spleen, we constructed multiple SS Ms (i.e., liver SS M, spleen SS M, and a joint SSM of the liver and spleen) for morphological analysis.Coefficients of SS Ms are used as features for the classification of normal and cirrhotic livers.Through this paper, we show that classification accuracy can be significantly improved by effective mode selection, which is based on fisher discriminant analysis, and the use of a non-linear support vector machine.Furthermore, we also construct Computer-aided Diagnosis (CAD) of liver cirrhosis system using SSMs.