A Multitask Deep Learning Model for Voxel-Level Brain Age Estimation

Global brain age estimation has been used as an effective biomarker to study the correlation between brain aging and neurological disorders. However, it fails to provide spatial information on the brain aging process. Voxel-level brain age estimation can give insights into how different regions of the brain age in a diseased versus healthy brain. We propose a multitask deep-learning-based model that predicts voxel-level brain age with a Mean Absolute Error (MAE) of 5.30 years on our test set (n=50) and 6.92 years on an independent test set (n = 359). The results of our model outperformed a recently proposed voxel-level age prediction model. The source code and pre-trained models will be made publicly available to make our research reproducible.