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 …
[HTML][HTML] Accurate brain age prediction with lightweight deep neural networks
Deep learning has huge potential for accurate disease prediction with neuroimaging data,
but the prediction performance is often limited by training-dataset size and computing …
but the prediction performance is often limited by training-dataset size and computing …
Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN
Y Zhang, R Xie, I Beheshti, X Liu, G Zheng… - Computers in Biology …, 2024 - Elsevier
Currently, significant progress has been made in predicting brain age from structural
Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However …
Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However …
Patch-based brain age estimation from MR images
Brain age estimation from Magnetic Resonance Images (MRI) derives the difference
between a subject's biological brain age and their chronological age. This is a potential …
between a subject's biological brain age and their chronological age. This is a potential …
[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 …
Brain age prediction using combined deep convolutional neural network and multi-layer perceptron algorithms
Y Joo, E Namgung, H Jeong, I Kang, J Kim, S Oh… - Scientific Reports, 2023 - nature.com
The clinical applications of brain age prediction have expanded, particularly in anticipating
the onset and prognosis of various neurodegenerative diseases. In the current study, we …
the onset and prognosis of various neurodegenerative diseases. In the current study, we …
From a deep learning model back to the brain—Identifying regional predictors and their relation to aging
Abstract We present a Deep Learning framework for the prediction of chronological age from
structural magnetic resonance imaging scans. Previous findings associate increased brain …
structural magnetic resonance imaging scans. Previous findings associate increased brain …
[HTML][HTML] Deep neural networks learn general and clinically relevant representations of the ageing brain
The discrepancy between chronological age and the apparent age of the brain based on
neuroimaging data—the brain age delta—has emerged as a reliable marker of brain health …
neuroimaging data—the brain age delta—has emerged as a reliable marker of brain health …
Brain age estimation from MRI using cascade networks with ranking loss
Chronological age of healthy people is able to be predicted accurately using deep neural
networks from neuroimaging data, and the predicted brain age could serve as a biomarker …
networks from neuroimaging data, and the predicted brain age could serve as a biomarker …
A domain guided CNN architecture for predicting age from structural brain images
Given the wide success of convolutional neural networks (CNNs) applied to natural images,
researchers have begun to apply them to neuroimaging data. To date, however, exploration …
researchers have begun to apply them to neuroimaging data. To date, however, exploration …