activity
20162019
most citedNon Local Spatial and Angular Matching : Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising

83 citations · 101 across the 2 of their papers we have counts for

collaborators

5 papers

eess.IV2019

Harmonization of diffusion MRI datasets with adaptive dictionary learning

Samuel St-Jean, Max A. Viergever, Alexander Leemans

Diffusion magnetic resonance imaging is a noninvasive imaging technique that can indirectly infer the microstructure of tissues and provide metrics which are subject to normal vari…

eess.IV2019

Automated characterization of noise distributions in diffusion MRI data

Samuel St-Jean, Alberto De Luca, Chantal M. W. Tax +2

Knowledge of the noise distribution in diffusion MRI is the centerpiece to quantify uncertainties arising from the acquisition process. Accurate estimation beyond textbook distribu…

q-bio.QM201918 cited

Reducing variability in along-tract analysis with diffusion profile realignment

Samuel St-Jean, Maxime Chamberland, Max A. Viergever +1

Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajecto…

cs.CV2018

Automatic, fast and robust characterization of noise distributions for diffusion MRI

Samuel St-Jean, Alberto De Luca, Max A. Viergever +1

Knowledge of the noise distribution in magnitude diffusion MRI images is the centerpiece to quantify uncertainties arising from the acquisition process. The use of parallel imaging…

cs.CV201683 cited

Non Local Spatial and Angular Matching : Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising

Samuel St-Jean, Pierrick Coupé, Maxime Descoteaux

Diffusion magnetic resonance imaging datasets suffer from low Signal-to-Noise Ratio, especially at high b-values. Acquiring data at high b-values contains relevant information and…