Comparison of Diagnostic Performance of Spread Through Airspaces of Lung Adenocarcinoma Based on Morphological Analysis and Perinodular and Intranodular Radiomic Features on Chest CT Images.

Qi, Lin; Li, Xiaohu; He, Linyang; Cheng, Guohua; Cai, Yongjun; Xue, Ke; Li, Ming

Qi, Lin; Li, Xiaohu; He, Linyang; Cheng, Guohua; Cai, Yongjun; Xue, Ke; Li, Ming.

Afiliação

Qi L; Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
Li X; Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
He L; Jianpei Technology Co., Ltd., Hangzhou, China.
Cheng G; Jianpei Technology Co., Ltd., Hangzhou, China.
Cai Y; Department of Pathology, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
Xue K; Department of Plastic and Reconstructive Surgery, Shanghai 9th Peoples Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.
Li M; Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China.

Front Oncol ; 11: 654413, 2021.

Article em En | MEDLINE | ID: mdl-34249691

Palavras-chave

adenocarcinoma; lung; machine learning; radiomics; spread through airspaces

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

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