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DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy

We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstract feature representation and a multi-class classi...

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發表在:Neuroimage
Main Authors: Wachinger, Christian, Reuter, Martin, Klein, Tassilo
格式: Artigo
語言:Inglês
出版: 2017
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在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC5563492/
https://ncbi.nlm.nih.gov/pubmed/28223187
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2017.02.035
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