Login / Signup

Quantitative identification and segmentation repeatability of thoracic spinal muscle morphology.

Anoosha Pai SHonglin ZhangJason R ShewchukBedoor Al OmranJohn StreetDavid WilsonMajid DoroudiStephen H M BrownThomas R Oxland
Published in: JOR spine (2020)
The guidelines proposed are important for reliable MRI-based measurements and allow meaningful comparisons of muscle morphometry in the thoracic spine across different studies globally. Good segmentation repeatability suggests we can further investigate the effect of posture and spinal curvature on muscle morphology in the thoracic spine.
Keyphrases
  • spinal cord
  • skeletal muscle
  • deep learning
  • convolutional neural network
  • spinal cord injury
  • magnetic resonance imaging
  • clinical practice
  • contrast enhanced
  • machine learning
  • magnetic resonance
  • case control