title: An ultrasound-based computer-aided diagnosis tool for steatosis detection.
abstract: Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. A Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.
authors.forename: Ricardo T
authors.initials: RT
authors.lastname: Ribeiro
authors.forename: Rui Tato
authors.initials: RT
authors.lastname: Marinho
authors.forename: J Miguel
authors.initials: JM
authors.lastname: Sanches
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016022:Case-Control Studies; D005234:Fatty Liver / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D014463:Ultrasonography