Brain Age Prediction Using a Brain Multi-atlas-based Ensemble Deep Regression Method
Abstract
This ME thesis investigates brain age prediction from resting-state functional MRI using a multi-atlas ensemble deep regression framework based on graph convolutional networks. The study compares population-based and individual-based graph representations, evaluates multiple brain atlases, and explores ensemble strategies for combining predictions. Using Human Connectome Project data, the work examines how functional connectivity and graph-based deep learning can be leveraged for accurate brain age estimation.
Fields of Study & Subjects
Functional Brain Connectivity Studies
Advanced MRI Techniques and Applications
Advanced Neuroimaging Techniques and Applications
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 March 2026
- Language
- EN
- Document type
- Thesis