ArticleMagnetic resonance in medicine2026
Cartesian MaxGIRF: Model-based EPI reconstruction incorporating gradient nonlinearity and concomitant field effects.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Cartesian MaxGIRF: Model-based EPI reconstruction incorporating gradient nonlinearity and concomitant field effects.Magnetic resonance in medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
purposeLower field strength scanners with large bore size or complex geometries, and scanners with stronger gradient systems experience increased gradient nonlinearity and concomitant fields, each of which causes distortions in EPI. Current correction approaches based on image-domain interpolation introduce undesirable spatial blurring. To avoid spatial blurring, we introduce a model-based EPI reconstruction framework, denoted Cartesian MaxGIRF ("Max"well field correction using "GIRF"-predicted gradients), that simultaneously compensates the effects of concomitant fields, gradient nonlinearity, and off-resonance during image reconstruction. THEORY AND
methodsPerformance of the proposed framework was compared against standard correction methods using phantom datasets at 0.55T: (1) 2D spin-echo EPI (SE-EPI) with reversed phase-encoding directions and (2) accelerated 2D SE-EPI with partial Fourier. Two unique EPI image artifacts induced by concomitant fields ("parabolic shift" and "slice-dependent Nyquist ghost") were demonstrated and mitigated by the proposed framework using long-ETL 3D GRE-EPI and high-resolution 3D GRE-EPI, respectively. Resolution improvements and artifact mitigations by the proposed framework were demonstrated using in-vivo human brain datasets: (1) accelerated 2D diffusion-weighted SE-EPI and (2) high-resolution 3D GRE-EPI at 0.55T.
resultsThe amount of the parabolic shift for each imaging case was theoretically analyzed. The proposed framework demonstrated the mitigation of both parabolic shifts and slice-dependent Nyquist ghosts and retained better image details than standard correction methods when mitigating geometric distortions for all scenarios.
conclusionThe Cartesian MaxGIRF framework simultaneously mitigates the effects of concomitant fields, gradient nonlinearity, and static off-resonance. This approach is particularly useful to mitigate artifacts induced by second-order concomitant fields present in both symmetric and asymmetric gradient systems.
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.