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Geometric and Dosimetric Evaluation of the Automatic Delineation of Organs at Risk (OARs) in Non-Small-Cell Lung Cancer Radiotherapy Based on a Modified DenseNet Deep Learning Network
PURPOSE: To introduce an end-to-end automatic segmentation model for organs at risk (OARs) in thoracic CT images based on modified DenseNet, and reduce the workload of radiation oncologists. MATERIALS AND METHODS: The computed tomography (CT) images of 36 lung cancer patients were included in this s...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964972/ https://www.ncbi.nlm.nih.gov/pubmed/35371991 http://dx.doi.org/10.3389/fonc.2022.861857 |