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A Computational Framework for the Detection of Subcortical Brain Dysmaturation in Neonatal MRI Using 3D Convolutional Neural Networks
Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsupervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuroimaging datasets requires adequate sample size for...
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| Publicado no: | Neuroimage |
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| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6503677/ https://ncbi.nlm.nih.gov/pubmed/29793060 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2018.05.049 |
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