Featured Publications

Gardner M., Shinohara R. T., Bethlehem R. A. I., Romero-Garcia R., Warrier V., Dorfschmidt L., Lifespan Brain Chart Consortium, Shanmugan S., Thompson P., Seidlitz J., Alexander-Bloch A. F., Chen A. A. (Accepted). ComBatLS: A location- and scale-preserving method for multi-site image harmonization. Human Brain Mapping.

Moss, H. G., Chen, A. A., Jensen, J. H., & Benitez, A. (2025). Intra-voxel angular dispersion of fibers in corpus callosum decreases with healthy aging. Imaging Neuroscience, 3, imag_a_00463.

Chen, A. A., Clark, K., Dewey, B. E., DuVal, A., Pellegrini, N., Nair, G., Jalkh, Y., Khalil, S., Zurawski, J., Calabresi, P. A., Reich, D. S., Bakshi, R., Shou, H., & Shinohara, R. T. (2024). PARE: A framework for removal of confounding effects from any distance-based dimension reduction method. PLOS Computational Biology, 20(7), e1012241.

Chen, A. A., Weinstein, S. M., Adebimpe, A., Gur, R. C., Gur, R. E., Merikangas, K. R., Satterthwaite, T. D., Shinohara, R. T., & Shou, H. (2023). Similarity-based multimodal regression. Biostatistics, kxad033. https://doi.org/10.1093/biostatistics/kxad033

Hu, F., Chen, A. A., Horng, H., Bashyam, V., Davatzikos, C., Alexander-Bloch, A., Li, M., Shou, H., Satterthwaite, T. D., Yu, M., & Shinohara, R. T. (2023). Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization. NeuroImage, 274, 120125. https://doi.org/10.1016/j.neuroimage.2023.120125

Chen, A. A., Srinivasan, D., Pomponio, R., Fan, Y., Nasrallah, I. M., Resnick, S. M., Beason-Held, L. L., Davatzikos, C., Satterthwaite, T. D., Bassett, D. S., Shinohara, R. T., & Shou, H. (2022). Harmonizing functional connectivity reduces scanner effects in community detection. NeuroImage, 256, 119198. https://doi.org/10.1016/j.neuroimage.2022.119198

Chen, A. A., Luo, C., Chen, Y., Shinohara, R. T., & Shou, H. (2022). Privacy-preserving harmonization via distributed ComBat. NeuroImage, 248, 118822. https://doi.org/10.1016/j.neuroimage.2021.118822