A novel hepatocellular carcinoma image classification method based on voting ranking random forests

DOI10.1155/2016/2628463zbMath1348.92091OpenAlexW2408311630WikidataQ36949154 ScholiaQ36949154MaRDI QIDQ332979

Dehui Yi, Huiling Liu, Huiyan Jiang, Bingbing Xia

Publication date: 9 November 2016

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/2628463

zbMATH Keywords

gray level cooccurrence matrixhepatocellular carcinoma image classification problemlocal binary patternsvoting ranking random forests

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Medical applications (general) (92C50)

Related Items (1)

Random forest based multiclass classification approach for highly skewed particle data

Cites Work

• A decision support tool for the diagnosis of breast cancer based upon fuzzy ARTMAP

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