MIL normalization -- prerequisites for accurate MRI radiomics analysis.

Hu, Zhaoyu; Zhuang, Qiyuan; Xiao, Yang; Wu, Guoqing; Shi, Zhifeng; Chen, Liang; Wang, Yuanyuan; Yu, Jinhua

Hu, Zhaoyu; Zhuang, Qiyuan; Xiao, Yang; Wu, Guoqing; Shi, Zhifeng; Chen, Liang; Wang, Yuanyuan; Yu, Jinhua.

Afiliación

Hu Z; School of Information Science and Technology, Fudan University, Shanghai, China.
Zhuang Q; Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
Xiao Y; Department of Biomedical Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Wu G; School of Information Science and Technology, Fudan University, Shanghai, China.
Shi Z; Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
Chen L; Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
Wang Y; School of Information Science and Technology, Fudan University, Shanghai, China.
Yu J; School of Information Science and Technology, Fudan University, Shanghai, China. Electronic address: jhyu@fudan.edu.cn.

Comput Biol Med ; 133: 104403, 2021 06.

Article en En | MEDLINE | ID: mdl-33932645

Asunto(s)

Glioma; Imagen por Resonancia Magnética; Humanos; Área Bajo la Curva; Glioma/diagnóstico por imagen; Estudios Retrospectivos

Palabras clave

Deep learning; MRI; Multicenter; Normalization; Radiomics analysis

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Glioma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2021 Tipo del documento: Article País de afiliación: China

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