Harmonizing MR Images Across 100+ Scanners: Multi-site Validation with Traveling Subjects and Real-world Protocols

Year: 2026

Type: preprint

Abstract: Reliable harmonization of heterogeneous magnetic resonance~(MR) image datasets, especially those acquired in pragmatic clinical trials, is critical to advance multi-center neuroimaging studies and translational machine learning in healthcare. We present an enhanced and rigorously validated version of the HACA3 harmonization algorithm, which we refer to as HACA3$^+$, incorporating key methodological enhancements: (1)~an improved artifact encoder to better isolate and mitigate image artifacts, (2)~background and foreground-sensitive attention mechanisms to increase harmonization specificity, and (3)~extensive training using data spanning 100+ scanners from 64 independent sites, providing a broader diversity of scanners than other harmonization methods. Our study focuses on four commonly acquired MR image contrasts (T1-weighted, T2-weighted, proton density, \& fluid-attenuated inversion recovery), reflecting realistic clinical protocols. We perform inter-site harmonization experiments using traveling subjects to assess the generalization and robustness of the harmonization model. We compare the results of the publicly available version of HACA3 and our implementation, HACA3$^+$. Downstream relevance is further established through whole brain segmentation and image imputation. Finally, we justify each enhancement through an ablation experiment. Pre-trained weights and code for HACA3$^+$ are made publicly available at https://github.com/shays15/haca3-plus.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2604.19474

Authors: Hays, Savannah P., Zuo, Lianrui, Chaudhary, Muhammad Faizyab Ali, Bartz, Kathleen M., Remedios, Samuel W., Zhang, Jinwei, Zhuo, Jiachen, Bilgel, Murat, Saidha, Shiv, Koch, Carolyn, Cassard, Sandra D., Mowry, Ellen M., Newsome, Scott D., Prince, Jerry L., Dewey, Blake E., Carass, Aaron

Institutions: Johns Hopkins University, Johns Hopkins University Applied Physics Laboratory, Vanderbilt University, Institute on Aging, National Institute on Aging, Johns Hopkins Medicine

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, U.S. Department of Health and Human Services, Patient-Centered Outcomes Research Institute, Johns Hopkins University, National Institutes of Health, McDonnell Center for Systems Neuroscience, National Institute on Aging, National Cancer Institute, Congressionally Directed Medical Research Programs

OpenAlex ID: W7155195993