Open-source policy

We aim to always publish data and code from our projects when possible.

Source Code

Available at: https://github.com/rodrigomorenokth

Notable Repositories:

• Generalized Mean Intercept Length Tensor
• Vesselness using the Ring Pattern Detector
• Efficient Tensor Voting
• Classification of Trabeculae
• Distance Between Sets of Points

Other codebases are available upon request or will be published soon on GitHub.

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Datasets

Synthetic Healthy Brain Aging MRIs with Segmentation Masks

A collection of 6,448 synthetic aging brain T1 MRI scans with corresponding segmentation masks, designed to simulate longitudinal brain aging data.

Key Features:

• Synthetic data created using generative AI models
• Brain aging simulation from T1 MRI scans
• Corresponding segmentation masks for each scan
• Resolution: 160x160x192, 1x1x1 mm
• Size: 52.4GB

DOI: 10.23698/aida/synthetic/shbamri

Dataset Access: AIDA Data Hub

Citation: Jingru Fu, Antonios Tzortzakakis, José Barroso, Eric Westman, Daniel Ferreira, and Rodrigo Moreno (2023) Synthetic healthy brain aging MRIs with segmentation masks. doi:10.23698/aida/synthetic/shbamri

Related Publication: Fast 3D image generation for healthy brain aging using diffeomorphic registration. Fu, Jingru et al., 2022. doi: 10.1002/hbm.26165