Segmentation of gliomas in magnetic resonance images using recurrent neural networks.
Stefan GrivalskyMartin TamajkaWanda BenesovaPublished in: TSP (2019)
Keyphrases
- magnetic resonance images
- recurrent neural networks
- brain tumors
- mri scans
- brain mri
- brain tissue
- medical images
- low grade gliomas
- partial volume
- tissue segmentation
- mr images
- medical imaging
- mri images
- brain scans
- multiple sclerosis lesions
- neural network
- white matter
- brain structures
- brain mr images
- intra subject
- magnetic resonance imaging
- recurrent networks
- echo state networks
- mri brain
- deformable registration
- high resolution
- artificial neural networks
- bias field
- feed forward
- mri data
- magnetic resonance
- partial volume effects
- image segmentation
- medical image analysis
- brain tumor segmentation
- gray matter
- nonlinear dynamic systems
- brain atlas
- image analysis
- diffusion tensor
- intensity distribution
- segmentation algorithm
- level set
- model based segmentation