Brain age estimation from MRI images using 2D-CNN instead of 3D-CNN
Human Brain Age has become a popular aging biomarker and is used to detect differences
among healthy individuals. Because of the specific changes in the human brain with aging, it …
among healthy individuals. Because of the specific changes in the human brain with aging, it …
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 …
Brain age gap estimation using attention-based ResNet method for Alzheimer's disease detection
A Aghaei, M Ebrahimi Moghaddam… - Brain Informatics, 2024 - Springer
This study investigates the correlation between brain age and chronological age in healthy
individuals using brain MRI images, aiming to identify potential biomarkers for …
individuals using brain MRI images, aiming to identify potential biomarkers for …
A skewed loss function for correcting predictive bias in brain age prediction
In neuroimaging, the difference between predicted brain age and chronological age, known
as brain age delta, has shown its potential as a biomarker related to various pathological …
as brain age delta, has shown its potential as a biomarker related to various pathological …
P2‐402: BRAIN AGE PREDICTION FROM MINIMALLY PREPROCESSED MRI SCANS USING 3D DEEP RESIDUAL NEURAL NETWORKS
Abdulmajid Murad, Goo-Rak Kwon, Jae-Young Pyun, Chosun University, Gwangju, South
Korea. Contact e-mail: jypyun@ chosun. ac. kr Background: Normal brain aging can be …
Korea. Contact e-mail: jypyun@ chosun. ac. kr Background: Normal brain aging can be …
Multimodal brain age prediction with feature selection and comparison
Brain age, an estimated biological age from anatomical and/or functional brain imaging
data, and its deviation from the chronological age (brain age gap) have shown the potential …
data, and its deviation from the chronological age (brain age gap) have shown the potential …
Accurate brain age prediction model for healthy children and adolescents using 3d-cnn and dimensional attention
G Hu, Q Zhang, Z Yang, B Li - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
The brain age, estimated from the brain MRI data, is found to be a promising biomarker for
human brain development and neuroanatomical aging processes. A well-performed brain …
human brain development and neuroanatomical aging processes. A well-performed brain …
[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 …
Structural networks for brain age prediction
O Pina, I Cumplido-Mayoral… - … on Medical Imaging …, 2022 - proceedings.mlr.press
Biological networks have gained considerable attention within the Deep Learning
community because of the promising framework of Graph Neural Networks (GNN), neural …
community because of the promising framework of Graph Neural Networks (GNN), neural …
Predicting brain age using structural neuroimaging and deep learning
Y Varatharajah, S Baradwaj, A Kiraly, D Ardila, R Iyer… - BioRxiv, 2018 - biorxiv.org
Early detection of age-related diseases will greatly benefit from a model of the underlying
biological aging process. In this paper, we develop a brain-age predictor by using structural …
biological aging process. In this paper, we develop a brain-age predictor by using structural …