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Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections
PURPOSE: To compare manual corrections of liver masks produced by a fully automatic segmentation method based on convolutional neural networks (CNN) with manual routine segmentations in MR images in terms of inter-observer variability and interaction time. METHODS: For testing, patient’s precise ref...
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| 出版年: | PLoS One |
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| 主要な著者: | , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6527212/ https://ncbi.nlm.nih.gov/pubmed/31107915 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0217228 |
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