no code implementations • 5 Aug 2018 • Simon Koppers, Luke Bloy, Jeffrey I. Berman, Chantal M. W. Tax, J. Christopher Edgar, Dorit Merhof
For this purpose, a training database is required, which consist of the same subjects, scanned on different scanners.
no code implementations • 10 Apr 2019 • Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax, Paul M. Thompson
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.
1 code implementation • Magnetic resonance in medecine 2019 • Samuel St-Jean, Alberto De Luca, Chantal M. W. Tax, Max A. Viergever, Alexander Leemans
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.
no code implementations • 26 Jul 2019 • Stefano B. Blumberg, Marco Palombo, Can Son Khoo, Chantal M. W. Tax, Ryutaro Tanno, Daniel C. Alexander
Specifically, we introduce the Multi Stage Prediction (MSP) Network, a MTL framework that incorporates neural networks of potentially disparate architectures, trained for different individual acquisition platforms, into a larger architecture that is refined in unison.
no code implementations • MIDL 2019 • Maxime Chamberland, Sila Genc, Erika P. Raven, Greg D. Parker, Adam Cunningham, Joanne Doherty, Marianne van den Bree, Chantal M. W. Tax, Derek K. Jones
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-heterogeneous groups.