ArticleProceedings. IEEE International Symposium on Biomedical Imaging2022
Data-Consistent non-Cartesian deep subspace learning for efficient dynamic MR image reconstruction.
Article in Proceedings. IEEE International Symposium on Biomedical Imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- MoCo + ROVir: Synergy Between Respiratory Motion Compensation and Cardiac Receive Region Focusing for Cardiac MRI.Magnetic resonance in medicine · 2026Article
- A 20-minute, free-running, whole-heart cardiac MRI to image myocardial injury following reperfused myocardial infarction: demonstration in a large animal model.Radiology advances · 2026Article
- All-in-One Cardiac MRI: Unified Non-Contrast-enhanced and Contrast-enhanced Imaging for a Continuous-Acquisition Examination.Radiology. Cardiothoracic imaging · 2025Article
- Accelerating 3D radial MPnRAGE using a self-supervised deep factor model.Magnetic resonance in medicine · 2025Article
- Repeatability-encouraging self-supervised learning reconstruction for quantitative MRI.Magnetic resonance in medicine · 2025Article
- Generalizable, sequence-invariant deep learning image reconstruction for subspace-constrained quantitative MRI.Magnetic resonance in medicine · 2025Article
- ACCELERATING QUANTITATIVE MRI USING SUBSPACE MULTISCALE ENERGY MODEL (SS-MUSE).Proceedings. IEEE International Symposium on Biomedical Imaging · 2025Article
- Rosette Trajectory MRI Reconstruction with Vision Transformers.Tomography (Ann Arbor, Mich.) · 2025Article
- Large-scale 3D non-Cartesian coronary MRI reconstruction using distributed memory-efficient physics-guided deep learning with limited training data.Magma (New York, N.Y.) · 2024Article
- Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS.Magnetic resonance in medicine · 2024Article
- Non-electrocardiogram-gated, free-breathing, off-resonance reduced, high-resolution, whole-heart myocardial TMagnetic resonance in medicine · 2024Article
- The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1).Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2024Review
- Emerging Trends in Fast MRI Using Deep-Learning Reconstruction on Undersampled k-Space Data: A Systematic Review.Bioengineering (Basel, Switzerland) · 2023Review
- Motion-compensated TFrontiers in cardiovascular medicine · 2023Review
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Authors and funding
5 authors.
Funding
Abstract
Non-Cartesian sampling with subspace-constrained image reconstruction is a popular approach to dynamic MRI, but slow iterative reconstruction limits its clinical application. Data-consistent (DC) deep learning can accelerate reconstruction with good image quality, but has not been formulated for non-Cartesian subspace imaging. In this study, we propose a DC non-Cartesian deep subspace learning framework for fast, accurate dynamic MR image reconstruction. Four novel DC formulations are developed and evaluated: two gradient decent approaches, a directly solved approach, and a conjugate gradient approach. We applied a U-Net model with and without DC layers to reconstruct T1-weighted images for cardiac MR Multitasking (an advanced multidimensional imaging method), comparing our results to the iteratively reconstructed reference. Experimental results show that the proposed framework significantly improves reconstruction accuracy over the U-Net model without DC, while significantly accelerating the reconstruction over conventional iterative reconstruction.
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