[HTML][HTML] Multimodality neuroimaging brain-age in UK biobank: relationship to biomedical, lifestyle, and cognitive factors

JH Cole - Neurobiology of aging, 2020 - Elsevier
The brain-age paradigm is proving increasingly useful for exploring aging-related disease
and can predict important future health outcomes. Most brain-age research uses structural …

[HTML][HTML] hMRI–A toolbox for quantitative MRI in neuroscience and clinical research

K Tabelow, E Balteau, J Ashburner, MF Callaghan… - Neuroimage, 2019 - Elsevier
Neuroscience and clinical researchers are increasingly interested in quantitative magnetic
resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue …

Neural orientation distribution fields for estimation and uncertainty quantification in diffusion MRI

W Consagra, L Ning, Y Rathi - Medical Image Analysis, 2024 - Elsevier
Inferring brain connectivity and structure in-vivo requires accurate estimation of the
orientation distribution function (ODF), which encodes key local tissue properties. However …

[HTML][HTML] High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and …

S Feizollah, CL Tardif - Neuroimage, 2023 - Elsevier
Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and
microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low …

ACID: A Comprehensive Toolbox for Image Processing and Modeling of Brain, Spinal Cord, and Ex Vivo Diffusion MRI Data

G David, B Fricke, JM Oeschger, L Ruthotto, FJ Fritz… - bioRxiv, 2023 - biorxiv.org
Diffusion MRI (dMRI) has become a crucial imaging technique in the field of neuroscience,
with a growing number of clinical applications. Although most studies still focus on the brain …

Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features

S Sihag, G Mateos, CT McMillan, A Ribeiro - arXiv preprint arXiv …, 2023 - arxiv.org
Graph convolutional networks (GCN) leverage topology-driven graph convolutional
operations to combine information across the graph for inference tasks. In our recent work …

[图书][B] Magnetic resonance brain imaging

J Polzehl, K Tabelow - 2019 - Springer
Our interest in neuroimaging started some 20 years ago, initiated by talks given by Fred
Godtliebsen (UiT, Tromsø, Norway) and by Fridhjof Kruggel (Max-Planck-Institute of …

Axisymmetric diffusion kurtosis imaging with Rician bias correction: A simulation study

JM Oeschger, K Tabelow… - Magnetic Resonance in …, 2023 - Wiley Online Library
Purpose To compare the estimation accuracy of axisymmetric diffusion kurtosis imaging
(DKI) and standard DKI in combination with Rician bias correction (RBC). Methods …

Determination of optimized set of b-values for apparent diffusion coefficient mapping in liver diffusion-weighted MRI

O Pena-Nogales, D Hernando, S Aja-Fernandez… - Journal of Magnetic …, 2020 - Elsevier
In this manuscript we derive the Cramér-Rao Lower Bound (CRLB) of the monoexponential
diffusion-weighted signal model under a realistic noise assumption, and propose a …

[HTML][HTML] Effects of radiofrequency channel numbers on B1+ mapping using the Bloch-Siegert shift method

Y Ren, Y Gao, B Qiu, X Nan, J Han - NeuroImage, 2023 - Elsevier
Purpose This paper aims to investigate the impact of the channel numbers on the
performance of B 1+ mapping, by using the Bloch-Siegert shift (BSS) method. B 1+ mapping …