A Theoretical Framework for Self-Supervised MR Image Reconstruction Using Sub-Sampling via Variable Density Noisier2Noise.
Charles MillardMark ChiewPublished in: IEEE Trans. Computational Imaging (2023)
Keyphrases
- theoretical framework
- image reconstruction
- sampled data
- band limited
- sparsely sampled
- reconstructed image
- super resolution
- compressed sensing
- radon transform
- reconstruction method
- maximum a posteriori
- emission computed tomography
- image reconstruction algorithms
- medical images
- cardiac imaging
- computed tomography
- synthetic aperture radar
- random sampling
- tomographic reconstruction
- mr images
- inverse problems
- image data
- emission tomography
- wiener filtering
- reconstruction process
- high resolution
- noise level
- noise reduction
- image registration
- fundamental principles
- random projections
- brain images
- magnetic resonance
- magnetic resonance images
- sampling methods
- high quality