92 citations · 125 across the 7 of their papers we have counts for
7 papers
Multi-compartment diffusion MRI, T2 relaxometry and myelin water imaging as neuroimaging descriptors for anomalous tissue detection
Elda Fischi-Gomez, Jonathan Rafael-Patino, Marco Pizzolato +5
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 an…
T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions
Hélène Lajous, Tom Hilbert, Christopher W. Roy +12
Relaxometry studies in preterm and at-term newborns have provided insight into brain microstructure, thus opening new avenues for studying normal brain development and supporting d…
Model-Informed Machine Learning for Multi-component T2 Relaxometry
Thomas Yu, Erick Jorge Canales Rodriguez, Marco Pizzolato +9
Recovering the T2 distribution from multi-echo T2 magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-st…
SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled bSSFP signal profile
Giulia MC Rossi, Adele LC Mackowiak, Tom Hilbert +4
Purpose: To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction using asymmetries in the phase-cycled bSSFP…
Compressed Sensing with Signal Averaging for Improved Sensitivity and Motion Artifact Reduction in Fluorine-19 MRI
Emeline Darçot, Jérôme Yerly, Tom Hilbert +5
Fluorine-19 (19F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-no…
Magnetization Transfer in Magnetic Resonance Fingerprinting
Tom Hilbert, Ding Xia, Kai Tobias Block +5
Purpose: To study the effects of magnetization transfer (MT, in which a semisolid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF)…
Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis
Francesco La Rosa, Mário João Fartaria, Tobias Kober +4
In this work, we present a comparison of a shallow and a deep learning architecture for the automated segmentation of white matter lesions in MR images of multiple sclerosis patien…