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A study of positioning orientation effect on segmentation accuracy using convolutional neural networks for rectal cancer
PURPOSE: Convolutional neural networks (CNN) have greatly improved medical image segmentation. A robust model requires training data can represent the entire dataset. One of the differing characteristics comes from variability in patient positioning (prone or supine) for radiotherapy. In this study,...
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| 出版年: | J Appl Clin Med Phys |
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| 主要な著者: | , , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
John Wiley and Sons Inc.
2018
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6333147/ https://ncbi.nlm.nih.gov/pubmed/30418701 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/acm2.12494 |
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