Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes t...

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Bibliographic Details

Published in:	Medical & Biological Engineering & Computing Vol. 56; no. 5; pp. 817 - 833
Main Authors:	Thomaz, Ricardo de Lima, Carneiro, Pedro Cunha, Bonin, João Eliton, Macedo, Túlio Augusto Alves, Patrocinio, Ana Claudia, Soares, Alcimar Barbosa
Format:	Journal Article
Published:	Springer Nature May2018
Online Access:	View this record in EBSCOhost