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Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning
We present a deep convolutional neural network application based on autoencoders aimed at segmentation of increased signal regions in fluid-attenuated inversion recovery magnetic resonance imaging images. The convolutional autoencoders were trained on the publicly available Brain Tumor Image Segment...
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| Опубликовано в: : | Tomography |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Grapho Publications, LLC
2016
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5215737/ https://ncbi.nlm.nih.gov/pubmed/28066806 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.18383/j.tom.2016.00166 |
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