[HTML][HTML] Predicting chronological age from structural neuroimaging: The predictive analytics competition 2019
Though aging is ubiquitous, the rate at which age-associated biological changes in the brain
occur differs substantially between individuals. Building on this, the so-called brain-age …
occur differs substantially between individuals. Building on this, the so-called brain-age …
Anatomical context improves deep learning on the brain age estimation task
Deep learning has shown remarkable improvements in the analysis of medical images
without the need for engineered features. In this work, we hypothesize that deep learning is …
without the need for engineered features. In this work, we hypothesize that deep learning is …
Predicting brain-age from raw T 1-weighted Magnetic Resonance Imaging data using 3D Convolutional Neural Networks
Age prediction based on Magnetic Resonance Imaging (MRI) data of the brain is a
biomarker to quantify the progress of brain diseases and aging. Current approaches rely on …
biomarker to quantify the progress of brain diseases and aging. Current approaches rely on …
[PDF][PDF] Brain age estimation using multiple regression analysis in brain MR images
Evaluating the morphological changes in human brain and comparing it to normal data
allow the risks of brain deformation related diseases to be assessed and the prevention …
allow the risks of brain deformation related diseases to be assessed and the prevention …
[HTML][HTML] Brain age prediction using deep learning uncovers associated sequence variants
Abstract Machine learning algorithms can be trained to estimate age from brain structural
MRI. The difference between an individual's predicted and chronological age, predicted age …
MRI. The difference between an individual's predicted and chronological age, predicted age …
[HTML][HTML] Learning patterns of the ageing brain in MRI using deep convolutional networks
Both normal ageing and neurodegenerative diseases cause morphological changes to the
brain. Age-related brain changes are subtle, nonlinear, and spatially and temporally …
brain. Age-related brain changes are subtle, nonlinear, and spatially and temporally …
[HTML][HTML] Machine learning for brain age prediction: Introduction to methods and clinical applications
The rise of machine learning has unlocked new ways of analysing structural neuroimaging
data, including brain age prediction. In this state-of-the-art review, we provide an …
data, including brain age prediction. In this state-of-the-art review, we provide an …
[HTML][HTML] Predicting brain age of healthy adults based on structural MRI parcellation using convolutional neural networks
H Jiang, N Lu, K Chen, L Yao, K Li, J Zhang… - Frontiers in …, 2020 - frontiersin.org
Structural magnetic resonance imaging (MRI) studies have demonstrated that the brain
undergoes age-related neuroanatomical changes not only regionally but also on the …
undergoes age-related neuroanatomical changes not only regionally but also on the …
[PDF][PDF] A U-net model of local brain-age
We propose a new framework for estimating neuroimaging-derived “brain-age” at a local
level within the brain, using deep learning. The local approach, contrary to existing global …
level within the brain, using deep learning. The local approach, contrary to existing global …
[HTML][HTML] Local brain-age: a U-net model
We propose a new framework for estimating neuroimaging-derived “brain-age” at a local
level within the brain, using deep learning. The local approach, contrary to existing global …
level within the brain, using deep learning. The local approach, contrary to existing global …