668-03-007 ISMRM Abstract

Protocol generalisation for brain tissue microstructure estimation with geometric deep learning: a hypernetwork approach

Primary: Analysis Methods - Classification and Prediction

Secondary: Diffusion - Microstructure

668-03-007 · Quantitative MRI Software: Tools and Applications · Thursday, 14 May, 1:40 PM–2:35 PM · Digital Posters Row I

Keywords: Brain Diffusion-weighted MRI Neurite orientation dispersion and density imaging Geometric deep learning Acquisition protocol generalisation

Accepted

Andrea Brigliadori ¹, Gary Zhang¹, Leevi Kerkelä¹

¹Hawkes Institute and Department of Computer Science, University College London, London, United Kingdom

Presenting Author: Andrea Brigliadori

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References

1. Goodwin-Allcock T, McEwen J, Gray R, Nachev P, Zhang H. How can spherical CNNs benefit ML-based diffusion MRI parameter estimation? arXiv:2207.00572, 2022.

2. Cohen TS, Geiger M, Koehler J, Welling M. Spherical CNNs. arXiv:1801.10130, 2018.

3. Esteves C, Allen-Blanchette C, Makadia A, Daniilidis K. Learning SO(3) Equivariant Representations with Spherical CNNs. arXiv:1711.06721, 2017.

4. Kerkelä L, Seunarine K, Szczepankiewicz F, Clark CA. Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data. Frontiers in Neuroimaging, 3, 2024. doi:10.3389/fnimg.2024.1349415. [doi]

5. Ha, D., Dai, A., Le, Q. V. (2016). HyperNetworks. arXiv:1609.09106.

6. Rot S, Dragonu I, Triantafyllou C, Grech-Sollars M, Papadaki A, Mancini L, Wastling S, Steeden J, Thornton JS, Yousry T, Gandini Wheeler-Kingshott CAM, Thomas DL, Alexander DC, Zhang H. Real-time, inline quantitative MRI enabled by scanner-integrated machine learning: a proof of principle with NODDI. arXiv:2507.12632, 2025.

7. Cook PA, Bai Y, Nedjati-Gilani S, Seunarine KK, Hall MG, Parker GJ, Alexander DC. Camino: Open-Source Diffusion-MRI Reconstruction and Processing. Proc. ISMRM 14th Scientific Meeting, Seattle, WA, USA, 2006. http://cds.ismrm.org/protected/06MProceedings/PDFfiles/02759.pdf

8. NODDI Matlab Toolbox. RRID:SCR_006826. University College London, UK. http://cmic.cs.ucl.ac.uk/mig/index.php?n=Tutorial.NODDImatlab

9. Van Essen DC, Smith SM, Barch DM, Behrens TEJ, Yacoub E, Ugurbil K; WU-Minn HCP Consortium. The WU-Minn Human Connectome Project: An overview. NeuroImage, 80:62–79, 2013.

10. Sotiropoulos SN, Moeller S, Jbabdi S, Xu J, Andersson JL, Auerbach EJ, Yacoub E, Feinberg D, Setsompop K, Wald LL, Behrens TEJ, Ugurbil K, Lenglet C. Effects of Image Reconstruction on Fibre Orientation Mapping from Multichannel Diffusion MRI: Reducing the Noise Floor Using SENSE. Magn Reson Med, 70(6):1682–1689, 2013.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/668-03-007