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Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations

Related publications (31)

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study

Patric Hagmann, Dimitri Nestor Alice Van De Ville, Maria Giulia Preti

Objective: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). ...

ELSEVIER IRELAND LTD2023

Widespread intra-axonal signal fraction abnormalities in bipolar disorder from multicompartment diffusion MRI: Sensitivity to diagnosis, association with clinical features and pharmacologic treatment

Erick Jorge Canales Rodriguez

Despite diffusion tensor imaging (DTI) evidence for widespread fractional anisotropy (FA) reductions in the brain white matter of patients with bipolar disorder, questions remain regarding the specificity and sensitivity of FA abnormalities as opposed to o ...

Wiley2023

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Victor Panaretos, Neda Mohammadi Jouzdani

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

Elsevier2024

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Bénédicte Marie Maréchal, Ricardo Alberto Corredor Jerez

Background: Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and ...

Springernature2023

Brain's Dynamic Functional Organization with Simultaneous EEG-fMRI Networks

João Pedro Forjaco Jorge, Patricia Figueiredo

The brain's functional networks can be assessed using imaging techniques like functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Recent studies have suggested a link between the dynamic functional connectivity (dFC) captured by ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

André Döring

IntroductionDiffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessita ...

Frontiers Media Sa2023

Brain matters: unveiling the distinct contributions of region, age, and sex to glia diversity and CNS function

Nina-Lydia Kazakou, Gioele La Manno, Zahra Moslehi

The myelinated white matter tracts of the central nervous system (CNS) are essential for fast transmission of electrical impulses and are often differentially affected in human neurodegenerative diseases across CNS region, age and sex. We hypothesize that ...

BMC2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Prateek Bansal, Thomas Gasos

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Diff3DHPE: A Diffusion Model for 3D Human Pose Estimation

Tong Zhang

Accurately estimating 3D human pose (3D HPE) and joint locations using only 2D keypoints is challenging. The noise in the predictions produced by conventional 2D human pose estimators often impeded the accuracy. In this paper, we present a diffusion-based ...

Ieee Computer Soc2023

The inductive bias of deep learning: Connecting weights and functions

Guillermo Ortiz Jimenez

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

EPFL2023

A multi-scale probabilistic atlas of the human connectome

Meritxell Bach Cuadra, Patric Hagmann, Elena Najdenovska, Alessandra Griffa, Maxime Descoteaux

The human brain is a complex system that can be efficiently represented as a network of structural connectivity. Many imaging studies would benefit from such network information, which is not always available. In this work, we present a whole-brain multi-s ...

NATURE PORTFOLIO2022