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Found 5 papers, 5 papers with code
Harmonization of diffusion MRI datasets with adaptive dictionary learning
Results show that the effect size of the four studied diffusion metrics is preserved while removing variability attributable to the scanner.
Automated characterization of noise distributions in diffusion MRI data
The proposed algorithms herein can estimate both parameters of the noise distribution, are robust to signal leakage artifacts and perform best when used on acquired noise maps.
Reducing variability in along-tract analysis with diffusion profile realignment
In this work, we propose to address the issue of possible misalignment, which might be present even after resampling, by realigning the representative streamline of each subject in this 1D space with a new method, coined diffusion profile realignment (DPR).
Automatic, fast and robust characterization of noise distributions for diffusion MRI
Knowledge of the noise distribution in magnitude diffusion MRI images is the centerpiece to quantify uncertainties arising from the acquisition process.
Non Local Spatial and Angular Matching : Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising
We then introduce a spatially and angular adaptive denoising technique, the Non Local Spatial and Angular Matching (NLSAM) algorithm.
