Comparison of the output of a deep learning segmentation model for locoregional breast cancer radiotherapy trained on 2 different datasets.

Bakx, Nienke; van der Sangen, Maurice; Theuws, Jacqueline; Bluemink, Hanneke; Hurkmans, Coen

Bakx, Nienke; van der Sangen, Maurice; Theuws, Jacqueline; Bluemink, Hanneke; Hurkmans, Coen.

Afiliación

Bakx N; Catharina Hospital, Department of Radiation Oncology, 5602ZA Eindhoven, the Netherlands.
van der Sangen M; Catharina Hospital, Department of Radiation Oncology, 5602ZA Eindhoven, the Netherlands.
Theuws J; Catharina Hospital, Department of Radiation Oncology, 5602ZA Eindhoven, the Netherlands.
Bluemink H; Catharina Hospital, Department of Radiation Oncology, 5602ZA Eindhoven, the Netherlands.
Hurkmans C; Catharina Hospital, Department of Radiation Oncology, 5602ZA Eindhoven, the Netherlands.

Tech Innov Patient Support Radiat Oncol ; 26: 100209, 2023 Jun.

Article en En | MEDLINE | ID: mdl-37213441

Palabras clave

Auto-segmentation; Clinical validation; Deep learning; Loco-regional breast cancer; Radiotherapy

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Qualitative_research Idioma: En Revista: Tech Innov Patient Support Radiat Oncol Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Reino Unido

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