Improving the sensitivity of liver tumor classification in ultrasound images via a power-law shot noise model.

Karako, Kenji; Mihara, Yuichiro; Hasegawa, Kiyoshi; Chen, Yu

Karako, Kenji; Mihara, Yuichiro; Hasegawa, Kiyoshi; Chen, Yu.

Afiliação

Karako K; Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Mihara Y; Artificial Organ and Transplantation Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Hasegawa K; Artificial Organ and Transplantation Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Chen Y; Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.

Biosci Trends ; 17(2): 117-125, 2023 May 15.

Article em En | MEDLINE | ID: mdl-37045784

Assuntos

Neoplasias Hepáticas; Humanos; Ultrassonografia; Neoplasias Hepáticas/diagnóstico por imagem

Palavras-chave

classification; deep learning; liver; power-law shot noise model; ultrasonography

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Hepáticas Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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