Computer-aided diagnosis and quantification of cirrhotic livers based on morphological analysis and machine learning
Yen-Wei Chen1, Jie Luo, Chunhua Dong
1College of Computer Science and Information Technology, Central South University of Forestry and Technology, Hunan, China ; College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan.
Abstract:
It is widely known that morphological changes of the liver and the spleen occur during the clinical course of chronic liver diseases. In this paper, we proposed a morphological analysis method based on statistical shape models (SSMs) of the liver and spleen for computer-aided diagnosis and quantification of the chronic liver. We constructed not only the liver SSM but also the spleen SSM and a joint SSM of the liver and the spleen for a morphologic analysis of the cirrhotic liver in CT images. The effective modes are selected based on both its accumulation contribution rate and its correlation with doctor's opinions (stage labels). We then learn a mapping function between the selected mode and the stage of chronic liver. The mapping function was used for diagnosis and staging of chronic liver diseases.
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