Deep MRI brain extraction: A 3D convolutional neural network for skull stripping
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- 作者：Jens Kleesieka ; b ; c ; d ; 1 ; kleesiek@uni-heidelberg.de" class="auth_mail" title="E-mail the corresponding author ; Gregor Urbana ; 1 ; Alexander Huberta ; Daniel Schwarza ; Klaus Maier-Heinb ; Martin Bendszusa ; Armin Billera ; d
- 关键词：GT ; ground truth ; T1w ; T1-weighted ; nT1w ; non-enhanced T1w ; ceT1w ; contrast-enhanced T1-weighted ; T2w ; T2-weigthed ; FLAIR ; fluid attenuated inversion recovery ; RF ; random forest ; CSF ; cerebrospinal fluid ; MFP ; max-fragment-pooling
- 刊名：NeuroImage
- 出版年：2016
- 出版时间：1 April 2016
- 年：2016
- 卷：129
- 期：Complete
- 页码：460-469
- 全文大小：1223 K
文摘
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Fast Deep Learning architecture for brain extraction in MRI images
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Trained appropriately, it handles multi-modal MRI data including contrast-enhanced scans.
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Matches at least state-of-the-art performance on publicly available data sets
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Superior performance for a multi-modal clinical data set of brain tumors