Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention.

Chung, Minyoung; Lee, Jingyu; Park, Sanguk; Lee, Chae Eun; Lee, Jeongjin; Shin, Yeong-Gil

Chung, Minyoung; Lee, Jingyu; Park, Sanguk; Lee, Chae Eun; Lee, Jeongjin; Shin, Yeong-Gil.

Afiliação

Chung M; School of Software, Soongsil University, 369 Sangdo-Ro, Dongjak-Gu, Seoul 06978, South Korea.
Lee J; Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
Park S; Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
Lee CE; Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
Lee J; School of Computer Science and Engineering, Soongsil University, 369 Sangdo-Ro, Dongjak-Gu, Seoul 06978, South Korea. Electronic address: leejeongjin@ssu.ac.kr.
Shin YG; Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.

Artif Intell Med ; 113: 102023, 2021 03.

Article em En | MEDLINE | ID: mdl-33685586

Assuntos

Processamento de Imagem Assistida por Computador; Redes Neurais de Computação; Atenção; Fígado/diagnóstico por imagem; Tomografia Computadorizada por Raios X

Palavras-chave

Auto-context neural network; Contour attention network; High-level residual shape prior; Liver segmentation; Self-supervised neural network

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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Redes Neurais de Computação Idioma: En Revista: Artif Intell Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Coréia do Sul

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