Deep-learning-based 3D super-resolution MRI radiomics model: superior predictive performance in preoperative T-staging of rectal cancer.

Hou, Min; Zhou, Long; Sun, Jihong

Hou, Min; Zhou, Long; Sun, Jihong.

Afiliação

Hou M; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China.
Zhou L; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China. zhoulong21@zju.edu.cn.
Sun J; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China. sunjihong@zju.edu.cn.

Eur Radiol ; 33(1): 1-10, 2023 Jan.

Article em En | MEDLINE | ID: mdl-35726100

Assuntos

Aprendizado Profundo; Neoplasias Retais; Humanos; Estudos Retrospectivos; Curva ROC; Neoplasias Retais/diagnóstico por imagem; Neoplasias Retais/cirurgia; Imageamento por Ressonância Magnética/métodos

Palavras-chave

Magnetic resonance imaging; Preoperative T-staging; Radiomics; Rectal cancer; Super-resolution

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

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