A Feasibility Study of Deep Learning-Based Auto-Segmentation Directly Used in VMAT Planning Design and Optimization for Cervical Cancer

PURPOSE: To investigate the dosimetric impact on target volumes and organs at risk (OARs) when unmodified auto-segmented OAR contours are directly used in the design of treatment plans. MATERIALS AND METHODS: A total of 127 patients with cervical cancer were collected for retrospective analysis, inc...

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Detalles Bibliográficos
Autores principales: Chen, Along, Chen, Fei, Li, Xiaofang, Zhang, Yazhi, Chen, Li, Chen, Lixin, Zhu, Jinhan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198405/
https://www.ncbi.nlm.nih.gov/pubmed/35719942
http://dx.doi.org/10.3389/fonc.2022.908903

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198405/
https://www.ncbi.nlm.nih.gov/pubmed/35719942
http://dx.doi.org/10.3389/fonc.2022.908903

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