Chiara Mauri 1, Allison McKenzie2, Emma Yeon2, Cole Analoro2, Xiangrui Zeng1, Divya Varadarajan, Jonathan R Polimeni3,4,5, Yaël Balbastre6, Malte Hoffmann1, Bruce Fischl1
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America
2Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, United States of America
3Stanford University, Stanford, United States of America
4Richard M. Lucas Center for Imaging, Stanford University, Stanford, United States of America
5Department of Radiology, Stanford Medicine, Stanford, United States of America
6Department of Experimental Psychology, University College London, London, United Kingdom
Presenting Author: Chiara Mauri
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.
1. Ogawa, S., Lee, T.-M., Kay, A. R, et al. (1990), ‘Brain magnetic resonance imaging with contrast dependent on blood oxygenation.’, proceedings of the National Academy of Sciences 87(24), 9868–9872. PMID: 2124706 doi:10.1073/pnas.87.24.9868 [doi][pmid]
2. Rodrıguez, J. L., van der Kouwe, A. J., Oltmer, J., et al. (2024), ‘Entorhinal vessel density correlates with phosphorylated tau and tdp-43 pathology’, Alzheimer’s & Dementia 20(7), 4649. PMID: 38877668 doi:10.1002/alz.13896 [doi][pmid]
3. Wälchli, T., Bisschop, J., Carmeliet, et al. (2023), ‘Shaping the brain vasculature in development and disease in the single-cell era’, Nature Reviews Neuroscience 24(5), 271–298. PMID: 36941369 doi:10.1038/s41583-023-00684-y [doi][pmid]
4. Sweeney, M. D., Kisler, K., Montagne, A., et al. (2018), ‘The role of brain vasculature in neurodegenerative disorders’, Nature neuroscience 21(10), 1318–1331. PMID: 30250261 doi: 10.1038/s41593-018-0234-x [doi][pmid]
5. Zlokovic, B. V. (2008), ‘The blood-brain barrier in health and chronic neurodegenerative disorders’, Neuron 57(2), 178–201. PMID: 18215617 doi: 10.1016/j.neuron.2008.01.003 [doi][pmid]
6. Carmeliet, P. (2003), ‘Angiogenesis in health and disease’, Nature medicine 9(6), 653–660. doi: 10.1038/nm0603-653 [doi]
7. Carmeliet, P. and Jain, R. K. (2011), ‘Molecular mechanisms and clinical applications of angiogenesis’, Nature 473(7347), 298–307. PMID: 21593862 doi: 10.1038/nature10144 [doi][pmid]
8. Potente, M., Gerhardt, H. and Carmeliet, P. (2011), ‘Basic and therapeutic aspects of angiogenesis’, Cell 146(6), 873–887. PMID: 21925313 doi: 10.1016/j.cell.2011.08.039 [doi][pmid]
9. Quaegebeur, A., Lange, C. and Carmeliet, P. (2011), ‘The neurovascular link in health and disease: molecular mechanisms and therapeutic implications’, Neuron 71(3), 406–424. PMID: 21835339 doi: 10.1016/j.neuron.2011.07.013 [doi][pmid]
10. Ghobrial, M., Charish, J., Takada, S., et al. (2020), ‘The human brain vasculature shows a distinct expression pattern of sars-cov-2 entry factors’, BioRxiv pp. 2020–10. doi: 10.1101/2020.10.10.334664 [doi]
11. Dumas, A., Dierksen, G. A., Gurol, M. E., et al. (2012), ‘Functional magnetic resonance imaging detection of vascular reactivity in cerebral amyloid angiopathy’, Annals of neurology 72(1), 76–81. PMID: 22829269 doi: 10.1002/ana.23566 [doi][pmid]
12. Chollet, E., Balbastre, Y., Mauri, C., et al. (2024), ‘Neurovascular segmentation in sOCT with deep learning and synthetic training data’, arXiv preprint. doi: https://doi.org/10.48550/arXiv.2407.01419 [doi]
13. Mauri. C., et al. (2025), A method for automatic 3D vasculature segmentation in ex vivo MRI using synthetic data, 2025, ISMRM: 1054. https://archive.ismrm.org/2025/1054_PW16z7QCr.html
14. https://brain-development.org/ixi-dataset/
15. https://public.kitware.com/Wiki/TubeTK/Data
16. Bollmann, S., Mattern, H., Bernier, et al. (2022), ‘Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography’, Elife 11, e71186. PMCID: PMC9150892, PMID: 35486089 doi: 10.7554/eLife.71186 [doi][pmid]
18. Ronneberger, O., Fischer, P. and Brox, T. (2015), U-net: Convolutional networks for biomedical image segmentation, in ‘Medical image computing and computer-assisted intervention–MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18’, Springer, pp. 234–241.
19. Frangi, A. F., Niessen, W. J., Vincken, K. L., et al., “Multiscale vessel enhancement filtering,” in Medical Image Computing and Computer-Assisted Intervention—MICCAI ’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings 1, pp. 130–137, Springer, 1998. doi: 10.1007/bfb0056195 [doi]
20. Xu, Marshall, et al. "VesselBoost: A Python Toolbox for Small Blood Vessel Segmentation in Human Magnetic Resonance Angiography Data." Aperture Neuro 4 (2024). doi: 10.52294/001c.123217 [doi]