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Erick Jorge Canales Rodriguez

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Publications associées (59)

Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the Substrate Complexity and Parameter Choice on the Reproducibility of Results

Jean-Philippe Thiran, David Paul Roger Romascano, Gabriel Girard, Jonathan Rafael Patino Lopez, Erick Jorge Canales Rodriguez, Alonso Ramirez Manzanares

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, methodological pitfalls in the design of the biomimicking geometrical configurations ...

2020

Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA

Jean-Philippe Thiran, Reto Meuli, Tobias Kober, Alessandro Daducci, Tom Hilbert, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato

Purpose Although several MRI methods have been explored to achievein vivomyelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the ...

Wiley2021

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

Jean-Philippe Thiran, Cristina Granziera, Alessandro Daducci, Muhamed Barakovic, Erick Jorge Canales Rodriguez

At the typical spatial resolution of MRI in the human brain, approximately 60–90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. Whil ...

2020

An overlapping pattern of cerebral cortical thinning is associated with both positive symptoms and aggression in schizophrenia via the ENIGMA consortium

Erick Jorge Canales Rodriguez, Wenhao Jiang

Background Positive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a ...

2020

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Elda Fischi Gomez, Cristina Granziera, Tom Hilbert, Muhamed Barakovic, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

Increased power by harmonizing structural MRI site differences with the ComBat batch method in ENIGMA

Erick Jorge Canales Rodriguez, Wenhao Jiang

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this intr ...

2020

DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

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

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

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

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

Sparse wars: A survey and comparative study of spherical deconvolution algorithms for diffusion MRI

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

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

Discoidin domain receptor 1 gene variants are associated with decreased white matter fractional anisotropy and decreased processing speed in schizophrenia

Erick Jorge Canales Rodriguez

DDR1 has been linked to schizophrenia (SZ) and myelination. Here, we tested whether DDR1 variants in people at risk for SZ influence white matter (WM) structural variations and cognitive processing speed (PS). First, following a case-control design (Study ...

2019

Multimodal microstructure imaging: joint T2-relaxometry and diffusometry to estimate myelin, intracellular, extracellular, and cerebrospinal fluid properties

Jean-Philippe Thiran, Alessandro Daducci, Erick Jorge Canales Rodriguez, Marco Pizzolato

We propose a multimodal joint estimation that aims at exploiting the complementary information of diffusion and multi-echo spin echo data to disentangle the contributions and properties of the main tissue microstructure compartments. We recovered T2, diffu ...

ISMRM2018

Multimodal microstructure imaging: combining relaxometry and diffusometry to estimate myelin, intracellular, extracellular, and cerebrospinal fluid properties

Jean-Philippe Thiran, Alessandro Daducci, Erick Jorge Canales Rodriguez, Marco Pizzolato

please visit https://infoscience.epfl.ch/record/264843 ...

2018

Fast and robust estimation of NODDI parameters using non-Gaussian noise models and spatial regularization

Jean-Philippe Thiran, Alessandro Daducci, Erick Jorge Canales Rodriguez

In this study, we developed a robust inversion algorithm to estimate the Neurite Orientation Dispersion and Density Imaging (NODDI) model. It is based on the Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework. However, in contrast ...

2018

Unified multi-modal characterization of microstructural parameters of brain tissue using diffusion MRI and multi-echo T2 data

Jean-Philippe Thiran, Nicolas Kunz, Alessandro Daducci, Erick Jorge Canales Rodriguez, Marco Pizzolato

In this study, a unified framework to estimate different microstructure indices from diffusion MRI and multi-echo T2 (MET2) data was proposed.The new methodology takes into account the common and complementary information provided by both modalities. While ...

2018

Reducing acquisition time for axon diameter mapping using global optimization in the spatial-angular-microstructure space

Jean-Philippe Thiran, Yves Wiaux, David Paul Roger Romascano, Alessandro Daducci, Anna Auria Rasclosa, Erick Jorge Canales Rodriguez, Tim Bjørn Dyrby

State-of-the-art microstructure imaging methods usually fit biophysical models to the diffusion MRI data on a voxel-by-voxel basis using non-linear procedures that require both long acquisitions and processing time. We recently introduced AMICO, a framewor ...

2016

Reducing acquisition time for microstructure imaging with spatially-regularized global optimization

Jean-Philippe Thiran, Yves Wiaux, David Paul Roger Romascano, Alessandro Daducci, Anna Auria Rasclosa, Erick Jorge Canales Rodriguez, Tim Bjørn Dyrby

Microstructure imaging with diffusion MRI (dMRI) is usually based on fitting models to the data using voxelwise nonlinear procedures that (i) are time consuming and (ii) need long acquisitions. Recently, we introduced the AMICO framework to accelerate the ...

2016

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data

Jean-Philippe Thiran, Alessandro Daducci, Hui Zhang, Erick Jorge Canales Rodriguez, Tim Bjørn Dyrby

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of bi ...

Elsevier2015

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Jean-Philippe Thiran, Yves Wiaux, Alessandro Daducci, Anna Auria Rasclosa, Erick Jorge Canales Rodriguez, Tim Bjørn Dyrby

Mapping the local microstructure properties of the tissue in the brain is crucial to understand any pathological condition from a biological perspective. In recent years, microstructure-imaging techniques aimed at extracting such precious information by us ...

2015

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI

Gloria Menegaz, Jean-Philippe Thiran, Mathews Jacob, Yves Wiaux, Alessandro Daducci, Ying-Chia Lin, Maxime Descoteaux, Erick Jorge Canales Rodriguez, Alonso Ramirez Manzanares

Validation is arguably the bottleneck in the diffusion MRI community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction chal ...

Institute of Electrical and Electronics Engineers2014

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