Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
503-03-001 / 271-01-021 ISMRM Abstract

All-in-One DeepGrasp: A Unified Self-Supervised Model for Accelerated 4D Radial MRI Across Organs, Resolutions, and Dynamics

Primary: Acquisition & Reconstruction - Image Reconstruction: AI
Secondary: Acquisition & Reconstruction - Subsampling: Parallel imaging, compressed sensing and low-rank modeling
503-03-001 · AI: Emerging Techniques and Clinical Applications · Wednesday, 13 May, 4:00 PM–5:50 PM · Auditorium 1
271-01-021 · ISMRM AMPC Selected Posters · Sunday, 10 May, 7:00 AM–2:00 PM · Traditional Posters
Keywords: AI/ML Image Reconstruction Foundation model Dynamic MRI Reconstruction Subspace Modelling Accelerated MRI reconstruction
Accepted
Haoyang Pei1,2,3, Jingjia Chen 1,2, Yao Wang3, Hersh Chandarana1,2, Li Feng1,2
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, United States of America
2Center for Advanced Imaging Innovation and Research (CAI²R), New York University Grossman School of Medicine, New York, United States of America
3Department of Electrical and Computer Engineering, NYU Tandon School of Engineering, New York, United States of America
Presenting Author: Jingjia Chen

Synopsis

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References

1. Feng, Li, et al. "Golden‐angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden‐angle radial sampling for fast and flexible dynamic volumetric MRI." Magnetic resonance in medicine 72.3 (2014): 707-717. https://doi.org/10.1002/mrm.24980 [doi]
2. Feng, Li, et al. "XD‐GRASP: golden‐angle radial MRI with reconstruction of extra motion‐state dimensions using compressed sensing." Magnetic resonance in medicine 75.2 (2016): 775-788. https://doi.org/10.1002/mrm.25665 [doi]
3. Feng, Li, et al. "GRASP‐Pro: imProving GRASP DCE‐MRI through self‐calibrating subspace‐modeling and contrast phase automation." Magnetic resonance in medicine 83.1 (2020): 94-108. https://doi.org/10.1002/mrm.27903 [doi]
4. Feng, Li. "4D golden‐angle radial MRI at subsecond temporal resolution." NMR in Biomedicine 36.2 (2023): e4844. https://doi.org/10.1002/nbm.4844 [doi]
5. Feng, Li. "Live‐view 4D GRASP MRI: a framework for robust real‐time respiratory motion tracking with a sub‐second imaging latency." Magnetic Resonance in Medicine 90.3 (2023): 1053-1068. https://doi.org/10.1002/mrm.29700 [doi]
6. Pei, Haoyang, et al. "DeepGrasp4D: A General Framework for Highly-Accelerated Real-Time 4D Golden-Angle Radial MRI Using Deep Learning." Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition. Vol. 31. 2024.
7. Pei, Haoyang, et al. "Highly-Accelerated, Free-Breathing, Time-Resolved 4D Golden-Angle Radial MRI with Self-Supervised Learning." Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition. Vol. 2643. 2025.
8. Pei, Haoyang, and Li Feng. "Deep Learning-Optimized GRASP-Pro Reconstruction for Highly-Accelerated DCE-MRI." Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition. Vol. 1136. 2025.
9. Chen, Jingjia, et al. "DCE‐MRI of the liver with sub‐second temporal resolution using GRASP‐Pro with navi‐stack‐of‐stars sampling." NMR in Biomedicine: e5262. https://doi.org/10.1002/nbm.5262 [doi]
10. Sriram, Anuroop, et al. "End-to-end variational networks for accelerated MRI reconstruction." Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part II 23. Springer International Publishing, 2020. https://doi.org/10.1007/978-3-030-59713-9_7 [doi]
11. Yaman, Burhaneddin, et al. "Self‐supervised learning of physics‐guided reconstruction neural networks without fully sampled reference data." Magnetic resonance in medicine 84.6 (2020): 3172-3191. https://doi.org/10.1002/mrm.28378 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/503-03-001