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Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation
BACKGROUND AND PURPOSE: Synthetic FLAIR images are of lower quality than conventional FLAIR images. Here, we aimed to improve the synthetic FLAIR image quality using deep learning with pixel-by-pixel translation through conditional generative adversarial network training. MATERIALS AND METHODS: Fort...
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| 出版年: | AJNR Am J Neuroradiol |
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| 主要な著者: | , , , , , , , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
American Society of Neuroradiology
2019
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7028623/ https://ncbi.nlm.nih.gov/pubmed/30630834 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3174/ajnr.A5927 |
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