77 citations · 104 across the 9 of their papers we have counts for
9 papers
Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology
Muhamed Barakovic, Marco Pizzolato, Chantal M. W. Tax +7
Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows no…
Microstructure estimation from diffusion-MRI: Compartmentalized models in permeable cellular tissue
Rémy Gardier, Juan Luis Villarreal Haro, Erick J Canales-Rodrıguez +4
Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, howev…
Slice estimation in diffusion MRI of neonatal and fetal brains in image and spherical harmonics domains using autoencoders
Hamza Kebiri, Gabriel Girard, Yasser Aleman-Gomez +4
Diffusion MRI (dMRI) of the developing brain can provide valuable insights into the white matter development. However, slice thickness in fetal dMRI is typically high (i.e., 3-5 mm…
Axial and radial axonal diffusivities from single encoding strongly diffusion-weighted MRI
Marco Pizzolato, Erick Jorge Canales-Rodríguez, Mariam Andersson +1
We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimatio…
Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI
Thomas Yu, Tom Hilbert, Gian Franco Piredda +8
Deep learning methods have become the state of the art for undersampled MR reconstruction. Particularly for cases where it is infeasible or impossible for ground truth, fully sampl…
Model-Informed Machine Learning for Multi-component T2 Relaxometry
Thomas Yu, Erick Jorge Canales Rodriguez, Marco Pizzolato +9
Recovering the T2 distribution from multi-echo T2 magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-st…
Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the substrate complexity and parameter choice on the reproducibility of results
Jonathan Rafael-Patino, David Romascano, Alonso Ramirez-Manzanares +3
Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodol…
Efficient sampling and robust 3D diffusion magnetic resonance imaging signal reconstruction
Alice P. Bates, Zubair Khalid, Jason D. McEwen +3
This paper presents novel single and multi-shell sampling schemes for diffusion MRI. In diffusion MRI, it is paramount that the number of samples is as small as possible in order t…
Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and spatial regularization
Erick J. Canales-Rodríguez, Alessandro Daducci, Stamatios N. Sotiropoulos +11
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assum…