ArticleMagnetic resonance in medicine2021
Aliasing artifact reduction in spiral real-time 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. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- "Two-For-One": 4D Cardiac and Pulmonary MR Imaging From a Single Acquisition Using bSTAR.Magnetic resonance in medicine · 2026Trial
- Free-breathing 3D pulmonary ventilation mapping at 0.55 T using stack-of-spiral out-in bSSFP.Magnetic resonance in medicine · 2026Article
- Deep Learning Assisted Outer Volume Removal for Highly-Accelerated Real-Time Dynamic MRI.ArXiv · 2025Article
- Simultaneous multi-slice cardiac real-time MRI at 0.55T.Magnetic resonance in medicine · 2025Article
- Rapid slice-to-volume four-dimensional flow in pediatric congenital heart disease: a feasibility study.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025Article
- Real-time water/fat imaging at 0.55T with spiral out-in-out-in sampling.Magnetic resonance in medicine · 2024Article
- A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images.Scientific data · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo mitigate a common artifact in spiral real-time MRI, caused by aliasing of signal outside the desired FOV. This artifact frequently occurs in midsagittal speech real-time MRI.
methodsSimulations were performed to determine the likely origin of the artifact. Two methods to mitigate the artifact are proposed. The first approach, denoted as "large FOV" (LF), keeps an FOV that is large enough to include the artifact signal source during reconstruction. The second approach, denoted as "estimation-subtraction" (ES), estimates the artifact signal source before subtracting a synthetic signal representing that source in multicoil k-space raw data. Twenty-five midsagittal speech-production real-time MRI data sets were used to evaluate both of the proposed methods. Reconstructions without and with corrections were evaluated by two expert readers using a 5-level Likert scale assessing artifact severity. Reconstruction time was also compared.
resultsThe origin of the artifact was found to be a combination of gradient nonlinearity and imperfect anti-aliasing in spiral sampling. The LF and ES methods were both able to substantially reduce the artifact, with an averaged qualitative score improvement of 1.25 and 1.35 Likert levels for LF correction and ES correction, respectively. Average reconstruction time without correction, with LF correction, and with ES correction were 160.69 ± 1.56, 526.43 ± 5.17, and 171.47 ± 1.71 ms/frame.
conclusionBoth proposed methods were able to reduce the spiral aliasing artifacts, with the ES-reduction method being more effective and more time efficient.
Indexed as
Identifiers
What OpenQuestion holds
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.