Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
470-02-084 ISMRM Abstract

Synthetic Stroke Lesion Generation Based on Mechanistic Principles and Label to Image Methodology

Primary: Analysis Methods - Image Synthesis and Translation
Secondary: Neuro - Stroke and Cerebrovascular Disorders
470-02-084 · Decoding Stroke with Imaging and AI: New Frontiers in Cerebrovascular Research · Tuesday, 12 May, 8:20 AM–9:15 AM · Traditional Posters | Exhibition Hall
Keywords: AI/ML Software Data Augmentation Lesion Evolution Patterns Synthetic contrasts Synthetic Data Generation
Accepted
Aksel Leknes 1, Ayo Zahra1, Ketil Oppedal2, Kathinka D Kurz3,4, Martin W Kurz5,6, Thomas W Lindner6,7,8, Soffien C Ajmi5,9, Muriel Bruchhage10,11
1Institute for Social Sciences, University of Stavanger, STAVANGER, Norway
2Department of Electrical Engineering and Computer Science, University of Stavanger, STAVANGER, Norway
3Radiology, Stavanger University Hospital, Stavanger, Norway
4Institute for Data science and Electrotechnology, University of Stavanger, STAVANGER, Norway
5Department of Neurology, Stavanger University Hospital, Stavanger, Norway
6Clinical Institute 1, University of Bergen, Bergen, Norway
7Department of Prehospital Medicine, Stavanger University Hospital, Stavanger, Norway
8The Centre for Emergency Medical Research and Development (RAKOS), Stavanger University Hospital, Stavanger, Norway
9Department of Quality and Health Technology, University of Stavanger, STAVANGER, Norway
10Institute of Psychology, University of Stavanger, STAVANGER, Norway
11Department of Radiology, Stavanger Medical Imaging Laboratory, Stavanger University Hospital, Stavanger, Norway
Presenting Author: Aksel Leknes

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. Feigin, V. L., Abate, M. D., Abate, Y. H., ElHafeez, S. A., Abd-Allah, F., Abdelalim, A., Abdelkader, A., Abdelmasseh, M., Abd-Elsalam, S., Abdi, P., Abdollahi, A., Abdoun, M., Abd-Rabu, R., Abdulah, D. M., Abdullahi, A., Abebe, M., Zuñiga, R. A. A., Abhilash, E. S., Abiodun, O. O., … Murray, C. J. L. (2024). Global, regional, and national burden of stroke and its risk factors, 1990–2021: A systematic analysis for the Global Burden of Disease Study 2021. The Lancet Neurology, 23(10), 973–1003. https://doi.org/10.1016/S1474-4422(24)00369-7 [doi]
2. Feigin, V. L., Brainin, M., Norrving, B., Martins, S. O., Pandian, J., Lindsay, P., F Grupper, M., & Rautalin, I. (2025). World Stroke Organization: Global Stroke Fact Sheet 2025. International Journal of Stroke, 20(2), 132–144. https://doi.org/10.1177/17474930241308142 [doi]
3. Maier, O., Menze, B. H., von der Gablentz, J., Ḧani, L., Heinrich, M. P., Liebrand, M., Winzeck, S., Basit, A., Bentley, P., Chen, L., Christiaens, D., Dutil, F., Egger, K., Feng, C., Glocker, B., Götz, M., Haeck, T., Halme, H.-L., Havaei, M., … Reyes, M. (2017). ISLES 2015—A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI. Medical Image Analysis, 35, 250–269. https://doi.org/10.1016/j.media.2016.07.009 [doi]
4. Liew, S.-L., Lo, B. P., Donnelly, M. R., Zavaliangos-Petropulu, A., Jeong, J. N., Barisano, G., Hutton, A., Simon, J. P., Juliano, J. M., Suri, A., Wang, Z., Abdullah, A., Kim, J., Ard, T., Banaj, N., Borich, M. R., Boyd, L. A., Brodtmann, A., Buetefisch, C. M., … Yu, C. (2022). A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms. Scientific Data, 9(1), 320. https://doi.org/10.1038/s41597-022-01401-7 [doi]
5. Billot, B., Greve, D. N., Puonti, O., Thielscher, A., Leemput, K. V., Fischl, B., Dalca, A. V., & Iglesias, J. E. (2023). SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining. Medical Image Analysis.
6. Laso, P., Cerri, S., Sorby-Adams, A., Guo, J., Mateen, F., Goebl, P., Wu, J., Liu, P., Li, H., Young, S. I., Billot, B., Puonti, O., Sze, G., Payabavash, S., DeHavenon, A., Sheth, K. N., Rosen, M. S., Kirsch, J., Strisciuglio, N., … Iglesias, J. E. (2024). Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI (No. arXiv:2312.05119). arXiv. https://doi.org/10.48550/arXiv.2312.05119 [doi]
7. Chalcroft, L., Pappas, I., Price, C. J., & Ashburner, J. (2024). Synthetic Data for Robust Stroke Segmentation (No. arXiv:2404.01946; Version 1). arXiv. https://doi.org/10.48550/arXiv.2404.01946 [doi]
8. Pérez-García, F., Sparks, R., & Ourselin, S. (2021). TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning. Computer Methods and Programs in Biomedicine, 208, 106236. https://doi.org/10.1016/j.cmpb.2021.106236 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/470-02-084