Evaluation of deep learning‐based auto‐segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients

OBJECTIVE: To evaluate the accuracy of a deep learning‐based auto‐segmentation mode to that of manual contouring by one medical resident, where both entities tried to mimic the delineation "habits" of the same clinical senior physician. METHODS: This study included 125 cervical cancer pati...

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Detalles Bibliográficos
Autores principales: Wang, Zhi, Chang, Yankui, Peng, Zhao, Lv, Yin, Shi, Weijiong, Wang, Fan, Pei, Xi, Xu, X. George
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Radiation Oncology Physics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769393/
https://www.ncbi.nlm.nih.gov/pubmed/33238060
http://dx.doi.org/10.1002/acm2.13097

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769393/
https://www.ncbi.nlm.nih.gov/pubmed/33238060
http://dx.doi.org/10.1002/acm2.13097

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