activity
20182021
most citedResolving orientation-specific diffusion-relaxation features via Monte-Carlo density-peak clustering in heterogeneous brain tissue

8 citations · 12 across the 3 of their papers we have counts for

collaborators

7 papers

physics.med-ph2021

aDWI-BIDS: an extension to the brain imaging data structure for advanced diffusion weighted imaging

James Gholam, Filip Szczepankiewicz, Chantal M. W. Tax +7

Diffusion weighted imaging techniques permit us to infer microstructural detail in biological tissue in vivo and noninvasively. Modern sequences are based on advanced diffusion enc…

q-bio.QM20204 cited

Tractometry-based Anomaly Detection for Single-subject White Matter Analysis

Maxime Chamberland, Sila Genc, Erika P. Raven +6

There is an urgent need for a paradigm shift from group-wise comparisons to individual diagnosis in diffusion MRI (dMRI) to enable the analysis of rare cases and clinically-heterog…

physics.med-ph20208 cited

Resolving orientation-specific diffusion-relaxation features via Monte-Carlo density-peak clustering in heterogeneous brain tissue

A. Reymbaut, J. P. de Almeida Martins, C. M. W. Tax +3

Characterizing the properties and orientations of sub-voxel fiber populations, although essential to study white-matter architecture, microstructure and connectivity, remains one o…

cs.LG2019

Multi-Stage Prediction Networks for Data Harmonization

Stefano B. Blumberg, Marco Palombo, Can Son Khoo +3

In this paper, we introduce multi-task learning (MTL) to data harmonization (DH); where we aim to harmonize images across different acquisition platforms and sites. This allows us…

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.QM2019

Scanner Invariant Representations for Diffusion MRI Harmonization

Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax +1

Purpose: In the present work we describe the correction of diffusion-weighted MRI for site and scanner biases using a novel method based on invariant representation. Theory and Met…