ArticleMagnetic resonance in medicine2021
High-dimensional fast convolutional framework (HICU) for calibrationless MRI.
Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Image space formalism of convolutional neural networks for k-space interpolation.Magnetic resonance in medicine · 2025Article
- Fast and ultra-high shot diffusion MRI image reconstruction with self-adaptive Hankel subspace.Medical image analysis · 2025Article
- New Theory and Faster Computations for Subspace-Based Sensitivity Map Estimation in Multichannel MRI.IEEE transactions on medical imaging · 2024Article
- A 2D-GRAPPA Algorithm with a Boomerang Kernel for 3D MRI Data Accelerated along Two Phase-Encoding Directions.Sensors (Basel, Switzerland) · 2022Article
- CALIBRATIONLESS MRI RECONSTRUCTION WITH A PLUG-IN DENOISER.Proceedings. IEEE International Symposium on Biomedical Imaging · 2021Article
- Autoregression and Structured Low-Rank Modeling of Sinogram Neighborhoods.IEEE transactions on computational imaging · 2021Article
Corrections and comments
- Erratum issuedErratum.2022
Authors and funding
3 authors.
Funding
Abstract
purposeTo present a computational procedure for accelerated, calibrationless magnetic resonance image (Cl-MRI) reconstruction that is fast, memory efficient, and scales to high-dimensional imaging. THEORY AND
methodsCl-MRI methods can enable high acceleration rates and flexible sampling patterns, but their clinical application is limited by computational complexity and large memory footprint. The proposed computational procedure, HIgh-dimensional fast convolutional framework (HICU), provides fast, memory-efficient recovery of unsampled k-space points. For demonstration, HICU is applied to 6 2D T2-weighted brain, 7 2D cardiac cine, 5 3D knee, and 1 multi-shot diffusion weighted imaging (MSDWI) datasets.
resultsThe 2D imaging results show that HICU can offer 1-2 orders of magnitude computation speedup compared to other Cl-MRI methods without sacrificing imaging quality. The 2D cine and 3D imaging results show that the computational acceleration techniques included in HICU yield computing time on par with SENSE-based compressed sensing methods with up to 3 dB improvement in signal-to-error ratio and better perceptual quality. The MSDWI results demonstrate the feasibility of HICU for a challenging multi-shot echo-planar imaging application.
conclusionsThe presented method, HICU, offers efficient computation and scalability as well as extendibility to a wide variety of MRI applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.