Classification of Clinically Significant Prostate Cancer on Multi-Parametric MRI: A Validation Study Comparing Deep Learning and Radiomics.

Castillo T, Jose M; Arif, Muhammad; Starmans, Martijn P A; Niessen, Wiro J; Bangma, Chris H; Schoots, Ivo G; Veenland, Jifke F

Castillo T, Jose M; Arif, Muhammad; Starmans, Martijn P A; Niessen, Wiro J; Bangma, Chris H; Schoots, Ivo G; Veenland, Jifke F.

Afiliación

Castillo T JM; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Arif M; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Starmans MPA; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Niessen WJ; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Bangma CH; Faculty of Applied Sciences, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands.
Schoots IG; Department of Urology, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Veenland JF; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.

Cancers (Basel) ; 14(1)2021 Dec 21.

Article en En | MEDLINE | ID: mdl-35008177

Palabras clave

Gleason score; classification; clinically significant; comparison; deep learning; machine learning; model; mpMRI; prediction; prostate carcinoma; radiomics

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Suiza

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