mlsanityData to 14 Oct 2026

A voxel-level approach to brain age prediction: A method to assess regional brain aging

arXiv 2310.11385 ↗First posted 17 Oct 2023cs.CVcited by 3

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Abstract (arXiv)

Brain aging is a regional phenomenon, a facet that remains relatively under-explored within the realm of brain age prediction research using machine learning methods. Voxel-level predictions can provide localized brain age estimates that can provide granular insights into the regional aging processes. This is essential to understand the differences in aging trajectories in healthy versus diseased subjects. In this work, a deep learning-based multitask model is proposed for voxel-level brain age prediction from T1-weighted magnetic resonance images. The proposed model outperforms the models existing in the literature and yields valuable clinical insights when applied to both healthy and diseased populations. Regional analysis is performed on the voxel-level brain age predictions to understand aging trajectories of known anatomical regions in the brain and show that there exist disparities in regional aging trajectories of healthy subjects compared to ones with underlying neurological disorders such as Dementia and more specifically, Alzheimer's disease. Our code is available at https://github.com/nehagianchandani/Voxel-level-brain-age-prediction.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 12 of its 65 references that are in the map. First posted on arXiv 17 Oct 2023.

Builds on

12 of 65 references.

References · 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Deeply Supervised Multi-Task Autoencoder for Biological Brain Age estimation using three dimensional T1-weighted magnetic resonance imagingcited by 0
  2. 2025MRI-Based Brain Age Estimation with Supervised Contrastive Learning of Continuous Representationcited by 0
  3. 2026SurfAge-Net: A Hierarchical Surface-Based Network for Interpretable Fine-Grained Brain Age Predictioncited by 0