Personne

Jonathan Rafael Patino Lopez

Publications associées (9)

Towards a high-density packing white matter substrate generator for Monte-Carlo simulations

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Gabriel Girard, Jonathan Rafael Patino Lopez, Juan Luis Villarreal Haro, Rémy Marc M Gardier

One main goal of Diffusion-Weighted Magnetic Resonance Imaging is to infer microscopic tissue properties from the measured signal. The use of Monte-Carlo Simulations for DW-MRI on realistic substrates will help the study of DWI-MRI signals in controlled en ...

2022

Simulation-based Microstructure Imaging: From Forward Signal Modeling to Machine Learning

Jonathan Rafael Patino Lopez

This thesis focuses on the signal modelling of Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) in the brain's white matter (WM). DW-MRI a non-invasive technique with enormous potential for the study of the brain's microstructure by measuring the dif ...

EPFL2021

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Diffusion-weighted MRI (DW-MRI) has recently seen a rising interest in planar, spherical and general B-tensor encodings. Some of these sequences have aided traditional linear encoding in the estimation of white matter microstructural features, generally by ...

Springer2021

DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Gabriel Girard, Marco Pizzolato, Jonathan Rafael Patino Lopez, Thomas Yu, Muhamed Barakovic

Diffusion MRI (DW-MRI) allows for the detailed exploration of the brain white matter microstructure, with applications in both research and the clinic. However, state-of-the-art methods for microstructure estimation suffer from known limitations, such as t ...

Springer Nature2020

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Spherical deconvolution methods are widely used to estimate the brain's white-matter fiber orientations from diffusion MRI data. In this study, eight spherical deconvolution algorithms were implemented and evaluated. These included two model selection tech ...

2019

Learning global brain microstructure maps using trainable sparse encoders

Jean-Philippe Thiran, Gabriel Girard, Jonathan Rafael Patino Lopez, Alessandro Daducci, Muhamed Barakovic

Diffusion-Weighted Magnetic Resonance Imaging is the only non-invasive technique available to infer the underlying brain tissue microstructure. Currently, one of the promising methods for microstructure imaging is signal modelling using convex formulation, ...

2019

HOTmix: characterizing hindered diffusion using a mixture of generalized higher order tensors

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Gabriel Girard, David Paul Roger Romascano, Marco Pizzolato, Jonathan Rafael Patino Lopez, Alessandro Daducci, Muhamed Barakovic, Gaëtan Olivier D Rensonnet, Tim Bjørn Dyrby

We present HOTmix, a new model to describe the diffusion MRI signal for molecules undergoing hindered diffusion. HOTmix is based on a mixture of generalized higher order tensors, explicitly incorporating the diffusion sequence’s time-dependent parameters. ...

2019

Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Gabriel Girard, Marco Pizzolato, Jonathan Rafael Patino Lopez, Thomas Yu

Probabilistic parameter estimation in model fitting runs the gamut from maximum likelihood or maximum a posteriori point estimates from optimization to Markov Chain Monte Carlo (MCMC) sampling. The latter, while more computationally intensive, generally pr ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

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In vivo quantitative estimation of axon diameter in the white matter could bring new tools to study the structural and functional architecture of the brain. Recently, the feasibility of axon diameter estimation with diffusion-weighted MRI (DW-MRI) has been ...

2018

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