Automatic Segmentation of Clinical Target Volume and Organs-at-Risk for Breast Conservative Radiotherapy Using a Convolutional Neural Network

OBJECTIVE: Delineation of clinical target volume (CTV) and organs at risk (OARs) is important for radiotherapy but is time-consuming. We trained and evaluated a U-ResNet model to provide fast and consistent auto-segmentation. METHODS: We collected 160 patients’ CT scans with breast cancer who underw...

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Detalles Bibliográficos
Autores principales: Liu, Zhikai, Liu, Fangjie, Chen, Wanqi, Tao, Yinjie, Liu, Xia, Zhang, Fuquan, Shen, Jing, Guan, Hui, Zhen, Hongnan, Wang, Shaobin, Chen, Qi, Chen, Yu, Hou, Xiaorong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572021/
https://www.ncbi.nlm.nih.gov/pubmed/34754241
http://dx.doi.org/10.2147/CMAR.S330249

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8572021/
https://www.ncbi.nlm.nih.gov/pubmed/34754241
http://dx.doi.org/10.2147/CMAR.S330249

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