Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer

Abstract Background The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric parameters might be more relevant in clinical practice but is often lacking in the literature. The aim of this study was to investigate the impact of...

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Autors principals:	Maria Kawula, Dinu Purice, Minglun Li, Gerome Vivar, Seyed-Ahmad Ahmadi, Katia Parodi, Claus Belka, Guillaume Landry, Christopher Kurz
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2022-01-01
Col·lecció:	Radiation Oncology
Matèries:	3D U-Net Automatic segmentation Radiation therapy Prostate cancer Neural networks Deep learning
Accés en línia:	https://doi.org/10.1186/s13014-022-01985-9
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