ArticleIEEE transactions on medical imaging2018
Navigator-Free EPI Ghost Correction With Structured Low-Rank Matrix Models: New Theory and Methods.
Article in IEEE transactions on medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Tune In or Take the Stage? A Randomized Controlled Trial Comparing After-School Music and Theatre Training with Neuroimaging Outcomes for Youth.medRxiv : the preprint server for health sciences · 2026Article
- Smooth optimization using global and local low-rank regularizers.SIAM journal on imaging sciences · 2026Article
- Navigator-free multi-shot diffusion MRI via non-local low-rank reconstruction.Magnetic resonance in medicine · 2025Article
- Fast and ultra-high shot diffusion MRI image reconstruction with self-adaptive Hankel subspace.Medical image analysis · 2025Article
- Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction.Magnetic resonance imaging · 2025Article
- Diffusion tensor brain imaging at 0.55T: A feasibility study.Magnetic resonance in medicine · 2024Article
- Eddy current-induced artifact correction in high b-value ex vivo human brain diffusion MRI with dynamic field monitoring.Magnetic resonance in medicine · 2024Article
- Reconstruction for 7T high-resolution whole-brain diffusion MRI using two-stage N/2 ghost correction and L1-SPIRiT without single-band reference.Magnetic resonance in medicine · 2023Article
- Automated Parameter Selection for Accelerated MRI Reconstruction via Low-Rank Modeling of Local k-Space Neighborhoods.Zeitschrift fur medizinische Physik · 2023Article
- Improving robustness of 3D multi-shot EPI by structured low-rank reconstruction of segmented CAIPI sampling for fMRI at 7T.NeuroImage · 2023Article
- High-fidelity, high-spatial-resolution diffusion magnetic resonance imaging of ex vivo whole human brain at ultra-high gradient strength with structured low-rank echo-planar imaging ghost correction.NMR in biomedicine · 2023Article
- Multi-band multi-shot diffusion MRI reconstruction with joint usage of structured low-rank constraints and explicit phase mapping.Magnetic resonance in medicine · 2023Article
- A miniature U-net forQuantitative imaging in medicine and surgery · 2022Article
- What's new and what's next in diffusion MRI preprocessing.NeuroImage · 2022Review
- Robust autocalibrated structured low-rank EPI ghost correction.Magnetic resonance in medicine · 2021Article
- Minimizing echo and repetition times in magnetic resonance imaging using a double half-echo k-space acquisition and low-rank reconstruction.NMR in biomedicine · 2021Article
- Autoregression and Structured Low-Rank Modeling of Sinogram Neighborhoods.IEEE transactions on computational imaging · 2021Article
- Improved MUSSELS reconstruction for high-resolution multi-shot diffusion weighted imaging.Magnetic resonance in medicine · 2020Article
- Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction.Magnetic resonance in medicine · 2019Article
- Wave-LORAKS: Combining wave encoding with structured low-rank matrix modeling for more highly accelerated 3D imaging.Magnetic resonance in medicine · 2019Article
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4 authors.
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Abstract
Structured low-rank matrix models have previously been introduced to enable calibrationless MR image reconstruction from sub-Nyquist data, and such ideas have recently been extended to enable navigator-free echo-planar imaging (EPI) ghost correction. This paper presents a novel theoretical analysis which shows that, because of uniform subsampling, the structured low-rank matrix optimization problems for EPI data will always have either undesirable or non-unique solutions in the absence of additional constraints. This theory leads us to recommend and investigate problem formulations for navigator-free EPI that incorporate side information from either image-domain or k-space domain parallel imaging methods. The importance of using nonconvex low-rank matrix regularization is also identified. We demonstrate using phantom and in vivo data that the proposed methods are able to eliminate ghost artifacts for several navigator-free EPI acquisition schemes, obtaining better performance in comparison with the state-of-the-art methods across a range of different scenarios. Results are shown for both single-channel acquisition and highly accelerated multi-channel acquisition.
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