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Cascaded atrous convolution and spatial pyramid pooling for more accurate tumor target segmentation for rectal cancer radiotherapy
Convolutional neural networks (CNN) has become the state-of-the-art method for medical segmentation. However, repeated pooling and striding operations reduce the feature resolution, causing the loss of the detailed information. Additionally, tumors of different patients are of different sizes. Thus...
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| Pubblicato in: | Phys Med Biol |
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| Autori principali: | , , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6207191/ https://ncbi.nlm.nih.gov/pubmed/30109986 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1088/1361-6560/aada6c |
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