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Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning
Purpose: Generalizability is an important problem in deep neural networks, especially with variability of data acquisition in clinical magnetic resonance imaging (MRI). Recently, the spatially localized atlas network tiles (SLANT) can effectively segment whole brain, non-contrast T1w MRI with 132 vo...
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| Pubblicato in: | J Med Imaging (Bellingham) |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Society of Photo-Optical Instrumentation Engineers
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7757519/ https://ncbi.nlm.nih.gov/pubmed/33381612 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.7.6.064004 |
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