Magnetic resonance image segmentation of the compressed spinal cord in patients with degenerative cervical myelopathy using convolutional neural networks.
Kyohei NozawaSatoshi MakiTakeo FuruyaSho OkimatsuTakaki InoueAtsushi YundeMasataka MiuraYuki ShirataniYasuhiro ShigaKazuhide InageYawara EguchiSeiji OhtoriSumihisa OritaPublished in: Int. J. Comput. Assist. Radiol. Surg. (2023)
Keyphrases
- spinal cord
- magnetic resonance
- convolutional neural networks
- magnetic resonance images
- mr images
- image segmentation
- multiple sclerosis
- medical images
- brain image segmentation
- healthy volunteers
- medical imaging
- medical image analysis
- clinical studies
- clinical data
- deformable models
- medical data
- automatically segmenting
- structural analysis
- image registration
- mr imaging
- white matter
- clinically relevant
- brain images
- brain tissue
- image data
- mr brain images
- level set
- automatic segmentation
- segmentation algorithm
- manual segmentation
- brain mri
- mr brain
- image processing
- anatomical structures
- graph cuts
- magnetic resonance imaging
- mri data
- multiscale
- image analysis
- image slices
- computer vision
- brain tumors
- contrast enhanced
- disease progression
- energy function
- active contours
- markov random field
- computed tomography
- patient data
- computer aided diagnosis
- region growing
- gray level
- shape prior
- shape analysis
- clinical trials
- prostate cancer