A Deep Learning Algorithm for Synthesizing Magnetic Resonance Images from Spine Computed Tomography Images using Mixed Loss Functions.
Rizhong HuangMenghua ZhangKe HuangWeijie HuangPublished in: NCAA (2) (2023)
Keyphrases
- magnetic resonance images
- loss function
- computed tomography images
- learning algorithm
- mri scans
- learning models
- automatic segmentation
- partially labeled data
- boosting framework
- mr images
- boosting algorithms
- medical images
- mr imaging
- pairwise
- support vector
- loss minimization
- mri data
- magnetic resonance imaging
- medical imaging
- white matter
- learning to rank
- training data
- risk minimization
- diffusion tensor
- high resolution
- machine learning
- active learning
- reproducing kernel hilbert space
- generalization error
- unlabeled data
- brain tumors
- supervised learning
- magnetic resonance
- convex loss functions
- x ray
- image segmentation
- feature extraction
- diffusion weighted
- generalization ability
- computer vision
- pattern recognition