Jonathan Rafael Patiño Lopez

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Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, however, is that most of the proposed models are based on the assumption of negli ...

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 ...

Purpose Non-invasive axon diameter distribution (ADD) mapping using diffusion MRI is an ill-posed problem. Current ADD mapping methods require knowledge of axon orientation before performing the acquisition. Instead, ActiveAx uses a 3D sampling scheme to e ...

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 ...

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized by diffuse and focal areas of tissue loss. Conventional MRI techniques such as T1-weighted and T2-weighted scans are generally used in the diagnosis and prognosis of the ...

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 ...

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 ...

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 ...

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segm ...

Axonal conduction velocity, which ensures efficient function of the brain network, is related to axon diameter. Noninvasive, in vivo axon diameter estimates can be made with diffusion magnetic resonance imaging, but the technique requires three-dimensional ...

Aquaporins provide a unique approach for imaging genetic activity in deep tissues by increasing the rate of cellular water diffusion, which generates a magnetic resonance contrast. However, distinguishing aquaporin signals from the tissue background is cha ...

The methodological development in the mapping of the brain structural connectome from diffusion-weighted mag-netic resonance imaging (DW-MRI) has raised many hopes in the neuroscientific community. Indeed, the knowledge of the connections between different ...

Purpose Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging ( ...

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 ...

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI da ...

Jonathan Rafael Patiño Lopez

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Microstructure estimation from diffusion-MRI: Compartmentalized models in permeable cellular tissue

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

ActiveAx(ADD): Toward non-parametric and orientationally invariant axon diameter distribution mapping using PGSE

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

Multi-Compartment Diffusion Mri, T2 Relaxometry And Myelin Water Imaging As Neuroimaging Descriptors For Anomalous Tissue Detection

A Signal Peak Separation Index for axisymmetric B-tensor encoding

DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

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

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

Axon morphology is modulated by the local environment and impacts the noninvasive investigation of its structure-function relationship

Molecular Imaging with Aquaporin-Based Reporter Genes: Quantitative Considerations from Monte Carlo Diffusion Simulations

The diffusion-simulated connectivity (DiSCo) dataset

Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres

Assessing feasibility and reproducibility of a bundle-specific framework on in vivo axon diameter estimates at 300mT/m

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Voxel size matters: big voxels are required to generate realistic extra-axonal dMRI signals from Monte Carlo simulations

Non-parametric axon diameter distribution mapping with PGSE: reconstruction of uni- and multimodal distributions

Realistic 3D Fiber Crossing Phantom Models for Monte Carlo Diffusion Simulations