11 citations · 15 across the 4 of their papers we have counts for
6 papers
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-space quantitative diffusion MRI measures using a stretched-exponential representation
Tomasz Pieciak, Maryam Afzali, Fabian Bogusz +2
Diffusion magnetic resonance imaging (dMRI) is a relatively modern technique used to study tissue microstructure in a non-invasive way. Non-Gaussian diffusion representation is rel…
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…
Deep learning-based parameter mapping for joint relaxation and diffusion tensor MR Fingerprinting
Carolin M. Pirkl, Pedro A. Gómez, Ilona Lipp +13
Magnetic Resonance Fingerprinting (MRF) enables the simultaneous quantification of multiple properties of biological tissues. It relies on a pseudo-random acquisition and the match…
Double Diffusion Encoding Prevents Degeneracy in Parameter Estimation of Biophysical Models in Diffusion MRI
Santiago Coelho, Jose M. Pozo, Sune N. Jespersen +2
Purpose: Biophysical tissue models are increasingly used in the interpretation of diffusion MRI (dMRI) data, with the potential to provide specific biomarkers of brain microstructu…
q-Space Novelty Detection with Variational Autoencoders
Aleksei Vasilev, Vladimir Golkov, Marc Meissner +5
In machine learning, novelty detection is the task of identifying novel unseen data. During training, only samples from the normal class are available. Test samples are classified…