Otfpf: Optimal transport-based feature pyramid fusion network for brain age estimation with 3d overlapped convnext
Chronological age of healthy brain is able to be predicted using deep neural networks from
T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could …
T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could …
OTFPF: Optimal transport based feature pyramid fusion network for brain age estimation
Deep neural networks have shown promise in predicting the chronological age of a healthy
brain using T1-weighted magnetic resonance images (T1 MRIs). This predicted brain age …
brain using T1-weighted magnetic resonance images (T1 MRIs). This predicted brain age …
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 …
SFCNeXt: a simple fully convolutional network for effective brain age estimation with small sample size
Deep neural networks (DNN) have been designed to predict the chronological age of a
healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted …
healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted …
Brain age estimation from MRI using a two-stage cascade network with ranking loss
As age increases, human brains will be aged, and people tend to experience cognitive
decline with a higher risk of neuro-degenerative disease and dementia. Recently, it was …
decline with a higher risk of neuro-degenerative disease and dementia. Recently, it was …
Global-local transformer for brain age estimation
Deep learning can provide rapid brain age estimation based on brain magnetic resonance
imaging (MRI). However, most studies use one neural network to extract the global …
imaging (MRI). However, most studies use one neural network to extract the global …
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 …
Brain age estimation using LSTM on children's brain MRI
Brain age prediction based on children's brain MRI is an important biomarker for brain
health and brain development analysis. In this paper, we consider the 3D brain MRI volume …
health and brain development analysis. In this paper, we consider the 3D brain MRI volume …
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 …
such as Alzheimer's Disease (AD). Magnetic resonance imaging (MRI) have been widely …
Age estimation from MR images via 3D convolutional neural network and densely connect
The estimation of brain age from magnetic resonance (MR) images is useful for computer-
aided diagnosis (CAD) in neurodegenerative diseases. Some deep learning methods has …
aided diagnosis (CAD) in neurodegenerative diseases. Some deep learning methods has …