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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...
Autores principales: | Zhang, Fuli, Wang, Qiusheng, Lu, Na, Chen, Diandian, Jiang, Huayong, Yang, Anning, Yu, Yanjun, Wang, Yadi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
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 |
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