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Found 6 papers, 3 papers with code
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
Diffusion-weighted magnetic resonance imaging (DWI) is the only noninvasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain.
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
Diffusion-weighted magnetic resonance imaging (DWI) is the only non-invasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain.
Fitting IVIM with Variable Projection and Simplicial Optimization
Fitting multi-exponential models to Diffusion MRI (dMRI) data has always been challenging due to various underlying complexities.
ThetA -- fast and robust clustering via a distance parameter
Clustering is a fundamental problem in machine learning where distance-based approaches have dominated the field for many decades.
NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification
However, it is hard to estimate the impact of noise on downstream tasks based only on such qualitative assessments.
EVAC+: Multi-scale V-net with Deep Feature CRF Layers for Brain Extraction
Although multiple solutions have been proposed in the literature, we are still far from having truly robust methods.
