Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
331-02-008 / 331-02-008 ISMRM Abstract

Physics-Informed Neural Networks Improve Time-Encoded Pseudo-Continuous Arterial Spin Labeling Perfusion Quantification

Primary: Contrast Mechanisms - Arterial Spin Labelling
Secondary: Analysis Methods - Data Processing
331-02-008 · AI Frontiers in Image Analysis · Monday, 11 May, 1:50 PM–3:06 PM · Roof Terrace
331-02-008 · AI Frontiers in Image Analysis · Monday, 11 May, 1:50 PM–3:06 PM · Roof Terrace
Keywords: Data Analysis Neuroimaging Physics-informed Neural Networks Deep Learning-based quantification Hadamard encoding
Accepted
Alessandro Giupponi 1, Chiara Da Villa1, Giulio Ferrazzi2, Francesca Benedetta Pizzini3, Matthias van Osch4,5,6,7,8,9,10, Mattia Veronese11,12, Marco Castellaro1
1Department of Information Engineering, University of Padova, Padova, Italy
2Philips Healthcare, Milan, Italy
3Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
4NeuroScience Research Theme, Leiden University Medical Center, Leiden, Netherlands
5C.J. Gorter MRI Center, Leiden University Medical Center, Netherlands
6Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Netherlands
7C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
8Leiden University Medical Center, Leiden, Netherlands
9C.J. Gorter MRI Center, Department of Radiology, LUMC, Leiden, Netherlands
10Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
11department of information engineering, Padova, Italy
12Centre for Neuroimaging Sciences, King's College London, London, United Kingdom
Presenting Author: Alessandro Giupponi

Synopsis

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References

1. Woods JG, Achten E, Asllani I, et al. Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications. Magn Reson Med. 2024;92(2):469–495. doi:10.1002/mrm.30091. [doi]
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4. de Vries L, van Herten RLM, Hoving JW, et al. Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke. Med Image Anal. 2023;90:102971. doi:10.1016/j.media.2023.102971. [doi]
5. de Vries L, van Herten RLM, Hoving JW, et al. Accelerating physics-informed neural fields for fast CT perfusion analysis in acute ischemic stroke. In: Proc 7th Int Conf Med Imaging Deep Learn. PMLR; 2024:1606–1626. Available from: https://proceedings.mlr.press/v250/vries24a.html.
6. Teeuwisse WM, Schmid S, Ghariq E, Veer IM, van Osch MJP. Time-encoded pseudocontinuous arterial spin labeling: Basic properties and timing strategies for human applications. Magn Reson Med. 2014;72(6):1712–1722. doi:10.1002/mrm.25083. [doi]
7. Ye FQ, Mattay VS, Jezzard P, Frank JA, Weinberger DR, McLaughlin AC. Correction for vascular artifacts in cerebral blood flow values measured by arterial spin tagging techniques. Magn Reson Med. 1997;37(2):226–235. doi:10.1002/mrm.1910370215. [doi]
8. Avants BB, Epstein CL, Grossman M, Gee JC. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal. 2008;12(1):26–41. doi:10.1016/j.media.2007.06.004. [doi]
9. Sitzmann V, Martel J, Bergman A, Lindell D, Wetzstein G. Implicit neural representations with periodic activation functions. Adv Neural Inf Process Syst 2020;33:7462–7473.
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11. Chappell MA, Kirk TF, Craig MS, McConnell FAK, Zhao MY, MacIntosh BJ, Okell TW, Woolrich MW; BASIL: A toolbox for perfusion quantification using arterial spin labelling. Imaging Neuroscience 2023; 1 imag–1–00041. doi: https://doi.org/10.1162/imag_a_00041 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/331-02-008