Huanjie Li

This paper introduces a dual-projection based ICA denoising method to remove scanner/site effects in multi-site MRI data, showing improved performance over traditional ICA and GLM methods.

This paper introduces a deep learning framework to harmonize multisite neuroimaging data by removing site effects while preserving biological features, showing improved performance over traditional methods.

This paper introduces a tensor component analysis framework to identify shared brain networks across subjects during naturalistic stimuli, improving reproducibility and capturing individual differences.

This paper introduces a denoising method for multi-site multimodal MRI data to remove scanner and site variability, improving statistical analysis and data integration.