Search Results for author: Chantal M. W. Tax

Found 5 papers, 1 papers with code

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

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.

Anomaly Detection

Multi-Stage Prediction Networks for Data Harmonization

no code implementations26 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.

Multi-Task Learning

Automated characterization of noise distributions in diffusion MRI data

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.


Scanner Invariant Representations for Diffusion MRI Harmonization

no code implementations10 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.

Fairness Image Reconstruction

Spherical Harmonic Residual Network for Diffusion Signal Harmonization

no code implementations5 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.

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