Evidence map›Paper›PMID 40545602›Full record

ArticleNMR in biomedicine2025

An L0-Norm-Based Method for Passive Shimming Design in MRI: A Simulation-Based Study.

Wenchen Wang, Yaohui Wang, Riyu Wei, Ewald Weber, Feng Liu

Abstract read
In one paragraph

Article in NMR in biomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Wenchen WangSchool of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Queensland, Australia.
Yaohui WangDivision of Superconducting Magnet Science and Technology, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China.
Riyu WeiMagnetica Ltd, Northgate, Queensland, Australia.
Ewald WeberSchool of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Queensland, Australia.
Feng LiuSchool of Electrical Engineering and Computer Science, University of Queensland, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-1074-2601

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a magnetic resonance imaging (MRI) system, it is highly desirable to achieve superior homogeneity of the static magnetic field (B0) within the imaging region for high-performance imaging. Passive shimming (PS) is a widely used technique that employs ferromagnetic materials to reduce the B0 deviations. However, the PS installation process often involves multiple manual iterations due to system or human errors, causing efficiency and accuracy difficulties. Existing PS solutions usually use L1-norm-based optimization algorithms to minimize the total iron consumption and constrain the peak-to-peak field inhomogeneity within the desired range. This design scheme can lead to substantial modifications to shim pockets in each iteration, making the process time-consuming and prone to induce installation errors and even causing operation failures. This paper proposes a novel approach that utilizes the L0-norm to redesign the PS optimization model. Instead of focusing on reducing the total thickness of iron pieces, as done in conventional PS optimizations, the new design allows the explicit adjustment of the number of shim pockets, enhancing shimming efficiency and reducing manual errors in the installation process. To validate the effectiveness of the proposed method, we conducted several tests on shimming a 3-T superconducting magnet. The results demonstrate that our new scheme consistently generates sparse solutions that improve efficiency and accuracy compared to conventional solutions. Thus, our method offers a favorable solution to streamline the shimming process, addressing the long-standing technical restrictions of the standard LP model. This new PS is expected to achieve high B0 uniformity for various MRI applications.

Indexed as

Computer SimulationMagnetic Resonance ImagingAlgorithmsEquipment DesignHumansMagnetic FieldsPhantoms, ImagingL0‐norm methodlinear programming (LP)MRIpassive shimmingsuperconducting magnet

Identifiers

PMID40545602
PMCPMC12183350

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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.