Preliminary study on statistical shape model applied to diagnosis of liver cirrhosis

In computational anatomy, statistical shape model (SSM) is used for the quantitative evaluation of variations in the shapes of different organs. This paper focuses on the construction of a SSM of the liver and its application to computer-assisted diagnosis of cirrhosis. We prove the potential application of SSMs in the classification of normal and cirrhotic livers. In constructing a SSM of the liver, we first normalize volume data followed by the construction of the model using principal component analysis. The coefficients of the model are used as indicators of liver pathology. The effectiveness of the constructed model is evaluated by the classification accuracy of both normal and abnormal data.