Deep learning-based two-step organs at risk auto-segmentation model for brachytherapy planning in parotid gland carcinoma

PURPOSE: Delineation of organs at risk (OARs) represents a crucial step for both tailored delivery of radiation doses and prevention of radiation-induced toxicity in brachytherapy. Due to lack of studies on auto-segmentation methods in head and neck cancers, our study proposed a deep learning-based...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Zhen-Yu, Yue, Jing-hua, Wang, Wei, Wu, Wen-Jie, Zhou, Fu-gen, Zhang, Jie, Liu, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9924151/
https://www.ncbi.nlm.nih.gov/pubmed/36819465
http://dx.doi.org/10.5114/jcb.2022.123972

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9924151/
https://www.ncbi.nlm.nih.gov/pubmed/36819465
http://dx.doi.org/10.5114/jcb.2022.123972

Ejemplares similares