MRI of healthy brain aging: A review

ME MacDonald, GB Pike - NMR in Biomedicine, 2021 - Wiley Online Library
We present a review of the characterization of healthy brain aging using MRI with an
emphasis on morphology, lesions, and quantitative MR parameters. A scope review found …

Tractography methods and findings in brain tumors and traumatic brain injury

FC Yeh, A Irimia, DC de Almeida Bastos, AJ Golby - Neuroimage, 2021 - Elsevier
White matter fiber tracking using diffusion magnetic resonance imaging (dMRI) provides a
noninvasive approach to map brain connections, but improving anatomical accuracy has …

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

JH Cole, RPK Poudel, D Tsagkrasoulis, MWA Caan… - NeuroImage, 2017 - Elsevier
Abstract Machine learning analysis of neuroimaging data can accurately predict
chronological age in healthy people. Deviations from healthy brain ageing have been …

Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment

C Yin, P Imms, M Cheng, A Amgalan… - Proceedings of the …, 2023 - National Acad Sciences
The gap between chronological age (CA) and biological brain age, as estimated from
magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging …

Differences between chronological and brain age are related to education and self-reported physical activity

J Steffener, C Habeck, D O'Shea, Q Razlighi… - Neurobiology of …, 2016 - Elsevier
This study investigated the relationship between education and physical activity and the
difference between a physiological prediction of age and chronological age (CA). Cortical …

Graph transformer geometric learning of brain networks using multimodal MR images for brain age estimation

H Cai, Y Gao, M Liu - IEEE Transactions on Medical Imaging, 2022 - ieeexplore.ieee.org
Brain age is considered as an important biomarker for detecting aging-related diseases
such as Alzheimer's Disease (AD). Magnetic resonance imaging (MRI) have been widely …

From a deep learning model back to the brain—Identifying regional predictors and their relation to aging

G Levakov, G Rosenthal, I Shelef… - Human brain …, 2020 - Wiley Online Library
Abstract We present a Deep Learning framework for the prediction of chronological age from
structural magnetic resonance imaging scans. Previous findings associate increased brain …

A review of neuroimaging-driven brain age estimation for identification of brain disorders and health conditions

S Mishra, I Beheshti, P Khanna - IEEE Reviews in Biomedical …, 2021 - ieeexplore.ieee.org
Background: Neuroimage analysis has made it possible to perform various anatomical
analyses of the brain regions and helps detect different brain conditions/disorders. Recently …

Pitfalls in brain age analyses

ER Butler, A Chen, R Ramadan, TT Le, K Ruparel… - 2021 - Wiley Online Library
Over the past decade, there has been an abundance of research on the difference between
age and age predicted using brain features, which is commonly referred to as the “brain age …

Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis

R Boyle, L Jollans, LM Rueda-Delgado, R Rizzo… - Brain imaging and …, 2021 - Springer
Brain-predicted age difference scores are calculated by subtracting chronological age from
'brain'age, which is estimated using neuroimaging data. Positive scores reflect accelerated …