Applying a novel two-step deep learning network to improve the automatic delineation of esophagus in non-small cell lung cancer radiotherapy

PURPOSE: To introduce a model for automatic segmentation of thoracic organs at risk (OARs), especially the esophagus, in non-small cell lung cancer radiotherapy, using a novel two-step deep learning network. MATERIALS AND METHODS: A total of 59 lung cancer patients’ CT images were enrolled, of which...

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Detalles Bibliográficos
Autores principales: Zhang, Fuli, Wang, Qiusheng, Lu, Na, Chen, Diandian, Jiang, Huayong, Yang, Anning, Yu, Yanjun, Wang, Yadi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391539/
https://www.ncbi.nlm.nih.gov/pubmed/37534258
http://dx.doi.org/10.3389/fonc.2023.1174530

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391539/
https://www.ncbi.nlm.nih.gov/pubmed/37534258
http://dx.doi.org/10.3389/fonc.2023.1174530

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