Simulating single-coil MRI from the responses of multiple coils
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Abstract (arXiv)
We convert the information-rich measurements of parallel and phased-array MRI into noisier data that a corresponding single-coil scanner could have taken. Specifically, we replace the responses from multiple receivers with a linear combination that emulates the response from only a single, aggregate receiver, replete with the low signal-to-noise ratio and phase problems of any single one of the original receivers (combining several receivers is necessary, however, since the original receivers usually have limited spatial sensitivity). This enables experimentation in the simpler context of a single-coil scanner prior to development of algorithms for the full complexity of multiple receiver coils.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Nov 2018.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 2; 2024: 2; 2025: 1; 2026: 2.
11 papers.
- 2021Bayesian Uncertainty Estimation of Learned Variational MRI Reconstructioncited by 30
- 2023CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstructioncited by 21
- 2022Self-supervised Deep Unrolled Reconstruction Using Regularization by Denoisingcited by 8
- 2024Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learningcited by 8
- 2024Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Predictioncited by 7
- 2021Learned Half-Quadratic Splitting Network for MR Image Reconstructioncited by 5
- 2022PUERT: Probabilistic Under-sampling and Explicable Reconstruction Network for CS-MRIcited by 5
- 2023On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Diseasecited by 3
- 2025Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Datacited by 0
- 2026Anatomical Token Uncertainty for Transformer-Guided Active MRI Acquisitioncited by 0
- 2026Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction modelscited by 0
- 2026Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models2 May 2026
- 2026Anatomical Token Uncertainty for Transformer-Guided Active MRI Acquisition23 Mar 2026
- 2025Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data7 Oct 2025
- 2024Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction6 Jun 2024
- 2024Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning27 May 2024
- 2023CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction19 Sep 2023
- 2023On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Disease27 Jan 2023
- 2022Self-supervised Deep Unrolled Reconstruction Using Regularization by Denoising7 May 2022
- 2022PUERT: Probabilistic Under-sampling and Explicable Reconstruction Network for CS-MRI24 Apr 2022
- 2021Learned Half-Quadratic Splitting Network for MR Image Reconstruction17 Dec 2021
- 2021Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction12 Feb 2021