DeepComBat¶

DeepComBat integrates ComBat with deep learning-based feature modeling.

The method uses neural networks to capture complex non-linear structure in the data while preserving the statistical harmonization principles of ComBat.

This hybrid approach allows the modeling of complex scanner effects and feature interactions that cannot be captured by linear models.

Paper

Hu, F., Lucas, A., Chen, A. A., Coleman, K., Horng, H., Ng, R. W., ... & Alzheimer's Disease Neuroimaging Initiative. (2024). Deepcombat: A statistically motivated, hyperparameter‐robust, deep learning approach to harmonization of neuroimaging data. Human brain mapping, 45(11), e26708. https://doi.org/10.1002/hbm.26708

Source code

• https://github.com/hufengling/DeepComBat

Implementation status¶

• To be implemented