Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
306-02-005 ISMRM Abstract

HARP: HARmonizing in-vivo diffusion MRI using Phantom-only training

Primary: Diffusion - Diffusion Reconstruction
Secondary: Acquisition & Reconstruction - Artifacts and Correction Strategies
306-02-005 · From Theory to Clinic: Advances in Diffusion MRI Modeling and Analysis · Monday, 11 May, 1:50 PM–3:40 PM · Auditorium 2
Keywords: Phantoms Diffusion MRI Domain adaptation Harmonization
Accepted
Hwihun Jeong1, Qiang Liu1,2, Kathryn E Keenan3, Elisabeth A Wilde4,5, Walter Schneider6, Sudhir K Pathak6, Anthony P Zuccolotto7, Lauren J O’Donnell8,9, Lipeng Ning1, Yogesh Rathi 1
1Department of Psychiatry, Brigham and Women's Hospital and Harvard Medical School, Boston, United States of America
2College of Engineering, Northeastern University, Boston, United States of America
3National Institute of Standards and Technology, Boulder, United States of America
4Department of Neurology, University of Utah School of Medicine, Salt Lake City, United States of America
5George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, United States of America
6University of Pittsburgh, Pittsburgh, United States of America
7Psychology Software Tools, Pittsburgh, United States of America
8Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, United States of America
9Harvard-MIT Health Sciences and Technology, Cambridge, United States of America
Presenting Author: Yogesh Rathi

Synopsis

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References

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2. Liu, Qiang, et al. “Effect of a consistent reconstruction algorithm on inter-scanner reproducibility in diffusion MRI.” Med Phys. (2025): e70096
3. Liu, Qiang, et al. "Reduced cross‐scanner variability using vendor‐agnostic sequences for single‐shell diffusion MRI." Magnetic Resonance in Medicine 92.1 (2024): 246-256.
4. Mirzaalian, Hengameh, et al. "Inter-site and inter-scanner diffusion MRI data harmonization." NeuroImage 135 (2016): 311-323.
5. Karayumak, Suheyla Cetin, et al. "Retrospective harmonization of multi-site diffusion MRI data acquired with different acquisition parameters." Neuroimage 184 (2019): 180-200.
6. De Luca, Alberto, et al. "Cross‐site harmonization of diffusion MRI data without matched training subjects." Magnetic Resonance in Medicine (2025).
7. Psychology Software Tools, Universal Phantom. https://pstnet.com/products/mri-diffusion-calibration-phantom/
8. CaliberMRI, Diffusion Phantom. https://qmri.com/product/diffusion-phantom/
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11. Lee, Jieun, et al. "Artificial neural network for myelin water imaging." Magnetic resonance in medicine 83.5 (2020): 1875-1883.
12. Zhang, Shengwei, and Konstantinos Arfanakis. "Evaluation of standardized and study-specific diffusion tensor imaging templates of the adult human brain: Template characteristics, spatial normalization accuracy, and detection of small inter-group FA differences." Neuroimage 172 (2018): 40-50.
13. Malcolm James G. and Shenton ME and RY. Two-Tensor Tractography Using a Constrained Filter. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, Berlin, Heidelberg, 2009; 894–902
14. Tournier, J-Donald, Fernando Calamante, and Alan Connelly. "Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution." Neuroimage 35.4 (2007): 1459-1472.
15. O'Donnell, Lauren J., and Carl-Fredrik Westin. "Automatic tractography segmentation using a high-dimensional white matter atlas." IEEE transactions on medical imaging 26.11 (2007): 1562-1575.
16. Schultz, Thomas. "Learning a reliable estimate of the number of fiber directions in diffusion MRI." International conference on medical image computing and computer-assisted intervention. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/306-02-005