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Simultaneous cosegmentation of tumors in PET‐CT images using deep fully convolutional networks
PURPOSE: To investigate the use and efficiency of 3‐D deep learning, fully convolutional networks (DFCN) for simultaneous tumor cosegmentation on dual‐modality nonsmall cell lung cancer (NSCLC) and positron emission tomography (PET)‐computed tomography (CT) images. METHODS: We used DFCN cosegmentati...
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| Publicado no: | Med Phys |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
John Wiley and Sons Inc.
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6527327/ https://ncbi.nlm.nih.gov/pubmed/30537103 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mp.13331 |
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