Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors

Mathematics

• Magnetic Resonance Image 100%
• Inhomogeneity 70%
• Segmentation 20%
• Langevin Dynamics 13%
• Super-resolution 13%
• Unsupervised Learning 13%
• Dynamic Algorithms 12%
• Image Denoising 12%
• Stochastic Gradient 11%
• Registration 11%
• Denoising 11%
• Prior Probability 11%
• Performance 10%
• Image Processing 9%
• Bayesian inference 9%
• Neural Networks 8%
• Decrease 7%
• Likelihood 7%
• Framework 4%

Engineering & Materials Science

• Magnetic resonance 63%
• Image denoising 23%
• Unsupervised learning 23%
• Convolutional neural networks 18%
• Image processing 15%