🧠 BrainAgeNeXt: Advancing Brain Age Modeling

Upload a preprocessed T1w MRI scan (.nii.gz), enter the age and sex of the subject, and get the brain age prediction.

The following preprocessing steps are required.

  1. Skull-stripping using SynthStrip with the --no-csf flag for optimal results.
  2. N4 bias field correction using ANTs.
  3. Affine registration to the MNI 1mm isotropic template space.

BrainAgeNeXt has been trained and validated using over 11,000 T1w MRI acquired at 1.5, 3, and 7T. A 1mm isotropic resolution is preferred for the input image but not required. Our manuscript presents a detailed explanation of BrainAgeNeXt and its potential applications.

Note: this app allows to process only a single MRI at the time. Please visit our GitHub repository to install the code on your machine and run BrainAgeNeXt on large datasets )
Select Sex

Disclaimer: This is a research tool and is not intended for clinical use.

If you find this tool useful, please consider citing:

  1. La Rosa, F., Dos Santos Silva, J., Dereskewicz, E., Invernizzi, A., Cahan, N., Galasso, J., ... & Beck, E. S. (2025). BrainAgeNeXt: Advancing Brain Age Modeling for Individuals with Multiple Sclerosis. Imaging Neuroscience. DOI: 10.1162/imag_a_00487
  2. Roy, S., Koehler, G., Ulrich, C., Baumgartner, M., Petersen, J., Isensee, F., Jaeger, P.F. & Maier-Hein, K. (2023). MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).