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SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests
Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore...
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| Udgivet i: | Front Neuroinform |
|---|---|
| Main Authors: | , , , , , , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Frontiers Media S.A.
2017
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5247463/ https://ncbi.nlm.nih.gov/pubmed/28163680 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fninf.2017.00002 |
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