Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
608-02-005 ISMRM Abstract

Using Large Language Models to Inform Tractography

Primary: Analysis Methods - Multi-Modal Learning with LLMs/VLMs
Secondary: Diffusion - Tractography
608-02-005 · Towards Multimodal Intelligence in MRI: Vision-Language Integration · Thursday, 14 May, 1:40 PM–3:30 PM · Meeting Room 1.60
Keywords: Tractography Large Language Models Connectome Anatomical Prior Integration
Accepted
Elinor Thompson1, Tiantian He1, Anna Schroder1, Ahmed Abdulaal1, Alec Sargood1, Sonja Soskic2, Henry F J Tregidgo1, Daniel C Alexander 1
1Hawkes Institute, Department of Computer Science, University College London, London, United Kingdom
2Hawkes Institute, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
Presenting Author: Daniel C Alexander

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Schilling, K. G. et al. Brain connections derived from diffusion MRI tractography can be highly anatomically accurate – if we know where white matter pathways start, where they end, and where they don’t go. Brain Struct. Funct. 225, 2387–2402 (2020). doi:10.1007/s00429-020-02129-z. [doi]
2. Vogel, J. W. et al. Spread of pathological tau proteins through communicating neurons in human Alzheimer’s disease. Nat. Commun. 11, 2612 (2020). doi:10.1038/s41467-020-15701-2 [doi]
3. Klein, A. & Tourville, J. 101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol. Front. Neurosci. 6, (2012). doi:10.3389/fnins.2012.00171 [doi]
4. Glasser, M. F. et al. A multi-modal parcellation of human cerebral cortex. Nature 536, 171–178 (2016). doi:10.1038/nature18933 [doi]
5. Zhang, F. et al. An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan. NeuroImage 179, 429–447 (2018). doi:10.1016/j.neuroimage.2018.06.027 [doi]
6. Lewis, P. et al. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. Preprint at https://doi.org/10.48550/arXiv.2005.11401 (2021). [doi]
7. Smith, R. E., Tournier, J.-D., Calamante, F. & Connelly, A. Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information. NeuroImage 62, 1924–1938 (2012). doi:10.1016/j.neuroimage.2012.06.005 [doi]
8. Schiavi, S. et al. A new method for accurate in vivo mapping of human brain connections using microstructural and anatomical information. Sci. Adv. 6, eaba8245 (2020). doi:10.1126/sciadv.aba8245 [doi]
9. Raj, A., Kuceyeski, A. & Weiner, M. A Network Diffusion Model of Disease Progression in Dementia. Neuron 73, 1204–1215 (2012). doi:10.1016/j.neuron.2011.12.040 [doi]
10. Thompson, E. et al. Demonstration of an open-source toolbox for network spreading models: regional amyloid burden promotes tau production in Alzheimer’s disease. Alzheimers Dement. 20, e093791 (2024). doi:10.1002/alz.093791 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/608-02-005