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Orientador(es)
Resumo(s)
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. 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.
Descrição
Palavras-chave
Computer-aided diagnosis Classification Steatosis Textural features Ultrasound Accuracy Design automation Feature extraction Liver Sensitivity Speckle
Contexto Educativo
Citação
Ribeiro R, Marinho R, Sanches J. An ultrasound based computer-aided diagnosis tool for steatosis detection. IEEE J Biomed Health Inform. 2014;18(4):1397-403.