activity
20172022
most citedTADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data

73 citations · 236 across the 13 of their papers we have counts for

collaborators
Showing physics.med-phShow all

6 papers · 1 filter

physics.med-ph2020

ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation

Ross Callaghan, Daniel C. Alexander, Marco Palombo +1

This paper presents Contextual Fibre Growth (ConFiG), an approach to generate white matter numerical phantoms by mimicking natural fibre genesis. ConFiG grows fibres one-by-one, fo…

physics.med-ph2019

Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination

Ioana Hill, Marco Palombo, Mathieu Santin +14

The intra-axonal water exchange time τi, a parameter associated with axonal permeability, could be an important biomarker for understanding demyelinating pathologies such as Multip…

physics.med-ph2019

SANDI: a compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

Marco Palombo, Andrada Ianus, Daniel Nunes +4

This work introduces a compartment-based model for apparent soma and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in…

physics.med-ph20191 cited

In utero diffusion MRI: challenges, advances, and applications

Daan Christiaens, Paddy J. Slator, Lucilio Cordero-Grande +6

In utero diffusion MRI provides unique opportunities to non-invasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as…

physics.med-ph2018

Combined Diffusion-Relaxometry MRI to Identify Dysfunction in the Human Placenta

Paddy J. Slator, Jana Hutter, Marco Palombo +7

Purpose: A combined diffusion-relaxometry MR acquisition and analysis pipeline for in-vivo human placenta, which allows for exploration of coupling between T2* and apparent diffusi…

physics.med-ph2018

A generative model of realistic brain cells with application to numerical simulation of diffusion-weighted MR signal

Marco Palombo, Daniel C. Alexander, Hui Zhang

In this work, we introduce a novel computational framework that we developed to use numerical simulations to investigate the complexity of brain tissue at a microscopic level with…