[HTML][HTML] Learning to estimate the fiber orientation distribution function from diffusion-weighted MRI

D Karimi, L Vasung, C Jaimes, F Machado-Rivas… - NeuroImage, 2021 - Elsevier
Estimation of white matter fiber orientation distribution function (fODF) is the essential first
step for reliable brain tractography and connectivity analysis. Most of the existing fODF …

[HTML][HTML] Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results

L Ning, E Bonet-Carne, F Grussu, F Sepehrband… - Neuroimage, 2020 - Elsevier
Cross-scanner and cross-protocol variability of diffusion magnetic resonance imaging
(dMRI) data are known to be major obstacles in multi-site clinical studies since they limit the …

Diffusion mri with machine learning

D Karimi - arXiv preprint arXiv:2402.00019, 2024 - arxiv.org
Diffusion-weighted magnetic resonance imaging (dMRI) offers unique capabilities such as
noninvasive assessment of brain's micro-structure and structural connectivity. However …

[HTML][HTML] On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: Chronicles of the MEMENTO …

A De Luca, A Ianus, A Leemans, M Palombo… - NeuroImage, 2021 - Elsevier
Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural
organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal …

Contrastive semi-supervised harmonization of single-shell to multi-shell diffusion MRI

CB Hansen, KG Schilling, F Rheault, S Resnick… - Magnetic resonance …, 2022 - Elsevier
Abstract Diffusion weighted MRI (DW-MRI) harmonization is necessary for multi-site or multi-
acquisition studies. Current statistical methods address the need to harmonize from one site …

A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging

D Karimi, L Vasung, C Jaimes, F Machado-Rivas… - Medical image …, 2021 - Elsevier
Accurate modeling of diffusion-weighted magnetic resonance imaging measurements is
necessary for accurate brain connectivity analysis. Existing methods for estimating the …

Geometric deep learning for diffusion MRI signal reconstruction with continuous samplings (DISCUS)

C Ewert, D Kügler, R Stirnberg, A Koch… - Imaging …, 2024 - direct.mit.edu
Diffusion-weighted magnetic resonance imaging (dMRI) permits a detailed in-vivo analysis
of neuroanatomical microstructure, invaluable for clinical and population studies. However …

Uncertainty Reduction in Diffusion Magnetic Resonance Imaging Tractography

JP Grün - 2024 - bonndoc.ulb.uni-bonn.de
Diffusion Magnetic Resonance Imaging (dMRI) is currently the only non-invasive method
capable of mapping the geometry and microstructure of major white matter tracts in vivo …

Empirical and Data-Driven Harmonization of Diffusion Weighted MRI

CB Hansen - 2021 - search.proquest.com
Abstract Diffusion weighted MRI (DW-MRI) is known for mapping white matter fibers of the
brain and serves as the only available technique to probe tissue structure at a microscopic …

Integrating Histology and Microarchitecture Modeling with Deep Learning for Diffusion-Weighted Magnetic Resonance Imaging

V Nath - 2020 - ir.vanderbilt.edu
The human brain is one of the most complex organs to understand in terms of anatomy and
microstructural tissue properties of the brain's white matter. There is still a lack of …