Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.21/3939
Título: Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization
Autor: Ribeiro, Ricardo
Sanches, João
Palavras-chave: Liver steatosis
Hepatic parenchyma
Hepatic vesicles
Fat accumulation
Automatic diagnostic
Data: Out-2009
Citação: Ribeiro R, Sanches J. Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization. In Proceedings of RecPad 2009 - 15th edition of the Portuguese Conference on Pattern Recognition, Aveiro (Portugal), October 2009.
Resumo: Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.
Peer review: yes
URI: http://hdl.handle.net/10400.21/3939
Versão do Editor: http://users.isr.ist.utl.pt/~jmrs/research/publications/myPapers/2009/2009_RECPAD-RR_paper35.pdf
Aparece nas colecções:ESTeSL - Artigos

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