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Automatic Spinal Cord Gray Matter Quantification: A Novel Approach.

Charidimos TsagkasA Horvath-HuckAnna AltermattS PezoldMatthias WeigelT HaasM AmannLudwig KapposTill SprengerOliver BieriPhilippe C CattinKatrin Parmar
Published in: AJNR. American journal of neuroradiology (2019)
Our novel approach including the averaged magnetization inversion recovery acquisitions sequence and a fully-automated postprocessing segmentation algorithm demonstrated an accurate and reproducible spinal cord GM and WM segmentation. This pipeline is promising for both the exploration of longitudinal structural GM changes and application in clinical settings in disorders affecting the spinal cord.
Keyphrases
  • spinal cord
  • deep learning
  • convolutional neural network
  • neuropathic pain
  • spinal cord injury
  • machine learning
  • high resolution
  • cross sectional
  • computed tomography
  • magnetic resonance imaging
  • magnetic resonance