Computer-aided diagnosis and quantification of cirrhotic livers based on morphological analysis and machine learning

Comput Math Methods Med. 2013:2013:264809. doi: 10.1155/2013/264809. Epub 2013 Sep 29.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence / statistics & numerical data*
  • Case-Control Studies
  • Diagnosis, Computer-Assisted / statistics & numerical data*
  • Humans
  • Liver / diagnostic imaging
  • Liver / pathology
  • Liver Cirrhosis / diagnosis*
  • Liver Cirrhosis / diagnostic imaging
  • Liver Cirrhosis / pathology
  • Models, Anatomic
  • Neoplasm Staging / statistics & numerical data
  • Radiographic Image Interpretation, Computer-Assisted
  • Spleen / diagnostic imaging
  • Spleen / pathology
  • Support Vector Machine
  • Tomography, X-Ray Computed / statistics & numerical data