Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging

The advent of susceptibility-sensitive MRI techniques, such as susceptibility weighted imaging (SWI), has enabled accurate in vivo visualization and quantification of iron deposition within the human brain. Although previous approaches have been introduced to segment iron-rich brain regions, such as...

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Bibliographic Details
Main Authors:	Beliveau, V. (Author), Birkl, C. (Author), Nørgaard, M. (Author), Scherfler, C. (Author), Seppi, K. (Author)
Format:	Article
Language:	English
Published:	John Wiley and Sons Inc 2021
Subjects:	adult Adult aged Aged article brain Cerebellar Nuclei cerebellum nucleus controlled study convolutional neural network deep brain nuclei diagnostic imaging female Female human Humans image processing Image Processing, Computer-Assisted intrarater reliability Magnetic Resonance Imaging male Male middle aged Middle Aged Neural Networks, Computer neuroimaging Neuroimaging nuclear magnetic resonance imaging prediction procedures red nucleus Red Nucleus segmentation substantia nigra Substantia Nigra subthalamic nucleus Subthalamic Nucleus susceptibility weighted imaging young adult Young Adult
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View Fulltext in Publisher

Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging

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