Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI

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Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

Background: Mapping diffusion MRI tractography streamlines to the cortical surface facilitates the integration of white matter features onto gray matter, especially for connectivity analysis. ...

Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

In the central nervous system of primates, several pathways are characterized by different spectra of axon diameters. In vivo methods, based on diffusion-weighted magnetic resonance imaging, can provide axon diameter index estimates non-invasively. However ...

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...

Today, Magnetic Resonance Imaging (MRI) is a well-established medical imaging modality thanks to its excellent soft tissue contrast. Conventional MR image contrasts can be weighted towards one or more physical properties that discriminate different tissues ...

Encephalopathy is a neurological complication of COVID-19. The objective of this exploratory study is to investigate the link between systemic inflammation and brain microstructural changes (measured by diffusion-weighted imaging) in patients with COVID-19 ...

The anisotropy of brain white matter microstructure manifests itself in orientational-dependence of various MRI contrasts, and can result in significant quantification biases if ignored. Understanding the origins of this orientation-dependence could enhanc ...

Background: Tractography uses diffusion magnetic resonance imaging to noninvasively infer the macroscopic pathways of white matter fibers and it is the only available technique to probe in vivo the structural connectivity of the brain. However, despite thi ...

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 ...

Stroke patients vary considerably in terms of outcomes: some patients present ‘natural’ recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual ...

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI

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Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

Cortical Surfaces Integration with Tractography for Structural Connectivity Analysis

Object Priors for Volumetric Image Segmentation

Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts

Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

Quantitative Microstructural Imaging for Clinical Use

C-reactive protein and white matter microstructural changes in COVID-19 patients with encephalopathy

Measuring compartmental T-2-orientational dependence in human brain white matter using a tiltable RF coil and diffusion-T-2 correlation MRI

Hierarchical Microstructure Informed Tractography

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

The structural connectome and motor recovery after stroke: predicting natural recovery