Musclesense: a Trained, Artificial Neural Network for the Anatomical Segmentation of Lower Limb Magnetic Resonance Images in Neuromuscular Diseases.
Baris KanberJasper M. MorrowUros KlickovicStephen J. WastlingSachit ShahPietro FrattaAmy R. McDowellMatt G. HallChris A. ClarkFrancesco MuntoniMary M. ReillyMichael G. HannaDaniel C. AlexanderTarek A. YousryJohn S. ThorntonPublished in: Neuroinformatics (2021)
Keyphrases
- magnetic resonance images
- medical images
- brain structures
- brain mri
- artificial neural networks
- intra subject
- grey matter
- mr images
- medical imaging
- anatomical structures
- partial volume
- brain scans
- brain atlas
- magnetic resonance imaging
- brain tumors
- white matter
- multiple sclerosis lesions
- tissue segmentation
- medical image analysis
- image intensity
- mri scans
- bias field
- mri data
- brain tissue
- deformable models
- magnetic resonance
- inter subject
- spatial normalization
- accurate segmentation
- manual segmentation
- neural network
- ct images
- atlas based segmentation
- brain mr images
- corpus callosum
- computer vision
- three dimensional
- high resolution
- diffusion tensor
- fully automatic
- gray matter
- partial volume effects
- subject specific
- pattern recognition
- image segmentation
- region growing
- brain images
- level set
- edge detection
- diffusion weighted
- image processing
- intensity distribution