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Fully automated esophagus segmentation with a hierarchical deep learning approach
Segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper we focus on esophagus segmentation, a challenging problem since the walls of the esophagus have a very low contrast in CT images. Making use of Fully Convolutional Networks (FCN), we pre...
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| Publicado no: | Conf Proc IEEE Int Conf Signal Image Process Appl |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6193464/ https://ncbi.nlm.nih.gov/pubmed/30345425 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ICSIPA.2017.8120664 |
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