Human-to-monkey transfer learning identifies the frontal white matter as a key determinant for predicting monkey brain age
The application of artificial intelligence (AI) to summarize a whole-brain magnetic resonance
image (MRI) into an effective “brain age” metric can provide a holistic, individualized, and …
image (MRI) into an effective “brain age” metric can provide a holistic, individualized, and …
Brain Age Estimation with a Greedy Dual-Stream Model for Limited Datasets
Brain age estimation involves predicting an individual's biological age from their brain
images. This process offers valuable insights into the aging process and the progression of …
images. This process offers valuable insights into the aging process and the progression of …
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 …
Multi-task Collaborative Pre-training and Adaptive Token Selection: A Unified Framework for Brain Representation Learning
Structural magnetic resonance imaging (sMRI) reveals the structural organization of the
brain. Learning general brain representations from sMRI is an enduring topic in …
brain. Learning general brain representations from sMRI is an enduring topic in …
Regional choroidal thickness estimation from color fundus images based on convolutional neural networks
Y Rong, Q Chen, Z Jiang, Z Fan, H Chen - Heliyon, 2024 - cell.com
Purpose This study aims to estimate the regional choroidal thickness from color fundus
images from convolutional neural networks in different network structures and task learning …
images from convolutional neural networks in different network structures and task learning …
Brain Ages Derived from Different MRI Modalities are Associated with Distinct Biological Phenotypes
AC Roibu, S Adaszewski, T Schindler… - 2023 10th IEEE …, 2023 - ieeexplore.ieee.org
Brain ageing is a highly variable, spatially and temporally heterogeneous process, marked
by numerous structural and functional changes. These can cause discrepancies between …
by numerous structural and functional changes. These can cause discrepancies between …
An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs
This study investigates the application of ordinal regression methods for categorizing
disease severity in chest radiographs. We propose a framework that divides the ordinal …
disease severity in chest radiographs. We propose a framework that divides the ordinal …
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 …
Vector Quantized Multi-modal Guidance for Alzheimer's Disease Diagnosis Based on Feature Imputation
Abstract Magnetic Resonance Imaging (MRI) and positron emission tomography (PET) are
the most used imaging modalities for Alzheimer's disease (AD) diagnosis in clinics. Although …
the most used imaging modalities for Alzheimer's disease (AD) diagnosis in clinics. Although …
Brain Age Estimation Using Structural MRI: A Clustered Federated Learning Approach
SS Cheshmi, A Mahyar, A Soroush… - … Conference on Omni …, 2023 - ieeexplore.ieee.org
Estimating brain age based on structural Magnetic Resonance Imaging (MRI) is one of the
most challenging and prominent areas of research in recent medical imaging and …
most challenging and prominent areas of research in recent medical imaging and …