651-02-015 / 651-02-015 ISMRM Abstract

Denoising structural connectivity matrices across a study population using random matrix theory

Primary: Diffusion - Tractography

Secondary: Analysis Methods - Data Processing

651-02-015 · Diffusion Modeling To Map Tissue Microstructure · Thursday, 14 May, 1:40 PM–3:16 PM · Power Pitch Theatre 1

Keywords: Structural Connectivity Tractography Denoising Network analysis Population cohort

Accepted

Bradley G Karat ¹, Sofia Nikolaidou², Zifei Ling^1,3, Jiangyang Zhang^1,3, Erika Raven^1,4, Jelle Veraart^1,3

¹Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, United States of America

²Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, United States of America

³Center for Advanced Imaging Innovation and Research (CAI²R), New York University Grossman School of Medicine, New York, United States of America

⁴Institute for Translational Neuroscience, NYU Grossman School of Medicine, New York, New York, United States of America

Presenting Author: Bradley G Karat

Synopsis

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References

1. Veraart J, Novikov DS, Christiaens D, Ades-Aron B, Sijbers J, Fieremans E. Denoising of diffusion MRI using random matrix theory. Neuroimage. 2016;142:394-406.

2. Veraart J, Fieremans E, Novikov DS. Diffusion MRI noise mapping using random matrix theory. Magn Reson Med. 2016;76(5):1582-1593.

3. Marčenko VA, Pastur LA. Distribution of eigenvalues for some sets of random matrices. Math USSR. 1967;1(4):457-483.

4. Behrens TE, Sporns O. Human connectomics. Curr Opin Neurobiol. 2012;22(1):144-153.

5. Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage. 2010;52(3):1059-1069.

6. Schilling KG, Daducci A, Maier-Hein K, et al. Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions. Magn Reson Imaging. 2019;57:194-209.

7. Smith RE, Tournier JD, Calamante F, Connelly A. SIFT: Spherical-deconvolution informed filtering of tractograms. Neuroimage. 2013;67:298-312.

8. Koller K, Rudrapatna U, Chamberland M, et al. MICRA: Microstructural image compilation with repeated acquisitions. Neuroimage. 2021;225:117406.

9. Smith RE, Tournier JD, Calamante F, Connelly A. Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information. Neuroimage. 2012;62(3):1924-1938.

10. Tournier JD, Smith R, Raffelt D, et al. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage. 2019;202:116137.

11. Landa B, Zhang TTCK, Kluger Y. Biwhitening reveals the rank of a count matrix. SIAM J Math Data Sci. 2022;4(4):1420-1446.

12. Stanley JS 3rd, Yang J, Li R, et al. Principled PCA separates signal from noise in omics count data. bioRxivorg. Published online February 7, 2025. doi:10.1101/2025.02.03.636129 [doi]

13. Warrington S, Torchi A, Mougin O, et al. A multi-site, multi-modal travelling-heads resource for brain MRI harmonisation. Sci Data. 2025;12(1):609.

14. Bookheimer SY, Salat DH, Terpstra M, et al. The Lifespan Human Connectome Project in Aging: An overview. Neuroimage. 2019;185:335-348.

15. Wu D, Ma T, Ceritoglu C, et al. Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI. Neuroimage. 2016;125:120-130.

16. Moeller S, Pisharady PK, Ramanna S, et al. NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. Neuroimage. 2021;226(117539):117539.

17. Does MD, Olesen JL, Harkins KD, et al. Evaluation of principal component analysis image denoising on multi-exponential MRI relaxometry. Magn Reson Med. 2019;81(6):3503-3514.

18. Kim ME, Gao C, Ramadass K, et al. White matter microstructure and macrostructure brain charts across the human lifespan. bioRxivorg. Published online May 9, 2025:2025.05.08.652953. doi:10.1101/2025.05.08.652953 [doi]

19. Zhou Z, Fischl B, Aganj I, Alzheimer’s Disease Neuroimaging Initiative. Harmonization of structural brain connectivity through distribution matching. Hum Brain Mapp. 2025;46(9):e70257.

20. Maier-Hein KH, Neher PF, Houde JC, et al. The challenge of mapping the human connectome based on diffusion tractography. Nat Commun. 2017;8(1):1349.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/651-02-015