A review of medical image data augmentation techniques for deep learning applications
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
Deep learning for brain age estimation: A systematic review
Abstract Over the years, Machine Learning models have been successfully employed on
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …
Association of white matter volume with brain age classification using deep learning network and region wise analysis
Structural magnetic resonance imaging (sMRI) has been used to examine age-related
neuroanatomical changes in the human brain. In the present work, a pre-trained deep …
neuroanatomical changes in the human brain. In the present work, a pre-trained deep …
Constructing brain functional network by adversarial temporal-spatial aligned transformer for early AD analysis
Q Zuo, L Lu, L Wang, J Zuo, T Ouyang - Frontiers in neuroscience, 2022 - frontiersin.org
Introduction The brain functional network can describe the spontaneous activity of nerve
cells and reveal the subtle abnormal changes associated with brain disease. It has been …
cells and reveal the subtle abnormal changes associated with brain disease. It has been …
Linking brain age gap to mental and physical health in the Berlin aging study II
From a biological perspective, humans differ in the speed they age, and this may manifest in
both mental and physical health disparities. The discrepancy between an individual's …
both mental and physical health disparities. The discrepancy between an individual's …
Deep learning to predict neonatal and infant brain age from myelination on brain MRI scans
Background Assessment of appropriate brain myelination on T1-and T2-weighted MRI
scans is based on gestationally corrected age (GCA) and requires subjective visual …
scans is based on gestationally corrected age (GCA) and requires subjective visual …
[HTML][HTML] Mapping neurodevelopment with sleep macro-and micro-architecture across multiple pediatric populations
Profiles of sleep duration and timing and corresponding electroencephalographic activity
reflect brain changes that support cognitive and behavioral maturation and may provide …
reflect brain changes that support cognitive and behavioral maturation and may provide …
Hemisphere-separated cross-connectome aggregating learning via VAE-GAN for brain structural connectivity synthesis
Q Zuo, H Tian, R Li, J Guo, J Hu, L Tang, Y Di… - IEEE …, 2023 - ieeexplore.ieee.org
The brain network is an effective tool and has been widely used in the field of brain
neurodegenerative disease analysis. Due to the high cost of accessing medical image data …
neurodegenerative disease analysis. Due to the high cost of accessing medical image data …
Cervical cell image classification-based knowledge distillation
W Gao, C Xu, G Li, Y Zhang, N Bai, M Li - Biomimetics, 2022 - mdpi.com
Current deep-learning-based cervical cell classification methods suffer from parameter
redundancy and poor model generalization performance, which creates challenges for the …
redundancy and poor model generalization performance, which creates challenges for the …
A novel scaled-gamma-tanh (SGT) activation function in 3D CNN applied for MRI classification
Activation functions in the neural network are responsible for 'firing'the nodes in it. In a deep
neural network they 'activate'the features to reduce feature redundancy and learn the …
neural network they 'activate'the features to reduce feature redundancy and learn the …