Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
468-03-014 ISMRM Abstract

Perfusion-Informed Deep Learning for Automated Pulmonary Vessel Segmentation

Primary: Body - Lung
Secondary: Analysis Methods - Segmentation and Detection
468-03-014 · Segmentation for Cardiac Applications · Tuesday, 12 May, 1:40 PM–2:35 PM · Digital Posters Row I
Keywords: Blood vessels Perfusion Segmentation Deep learning Lung MRI
Accepted
Pavlos Panos 1,2, Oliver Bieri1,2, Grzegorz Bauman1,2
1Department of Biomedical Engineering, University of Basel, Basel, Switzerland
2Department of Radiology, Division of Radiological Physics, University of Basel Hospital, Basel, Switzerland
Presenting Author: Pavlos Panos

Synopsis

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References

1. Hsia CCW, Bates JHT, Driehuys B, et al. Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report. Ann Am Thorac Soc. 20(2):161-195. doi:10.1513/AnnalsATS.202211-915ST [doi]
2. Wielpütz M, Kauczor HU. MRI of the lung: state of the art. Diagn Interv Radiol. 2012;18(4):344-353. doi:10.4261/1305-3825.DIR.5365-11.0 [doi]
3. Walker SC, Asadi AK, Hopkins SR, Buxton RB, Prisk GK. A statistical clustering approach to discriminating perfusion from conduit vessel signal contributions in a pulmonary ASL MR image. NMR Biomed. 2015;28(9):1117-1124. doi:10.1002/nbm.3358 [doi]
4. Ming Y, Luo S, Zhao L, et al. High Accuracy Pulmonary Vessel Segmentation for Contrast and Non-contrast CT Images and Clinical Evaluation. May 2025. doi:10.48550/arXiv.2503.16988 [doi]
5. Chu Y, Luo G, Zhou L, et al. Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences. Nat Commun. 2025;16(1):2262. doi:10.1038/s41467-025-56505-6 [doi]
6. Bauman G, Bieri O. Matrix pencil decomposition of time-resolved proton MRI for robust and improved assessment of pulmonary ventilation and perfusion. Magn Reson Med. 2017;77(1):336-342. doi:10.1002/mrm.26096 [doi]
7. Pusterla O, Willers C, Sandkühler R, et al. An automated pipeline for computation and analysis of functional ventilation and perfusion lung MRI with matrix pencil decomposition: TrueLung. June 2024. doi:10.48550/arXiv.2404.18275 [doi]
8. Ley S, Ley-Zaporozhan J. Pulmonary perfusion imaging using MRI: clinical application. Insights Imaging. 2011;3(1):61-71. doi:10.1007/s13244-011-0140-1 [doi]

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http://echo.ismrm.org/p/ISMRM2026/468-03-014