🤖 AI Summary
Static magnetic field (B₀) inhomogeneity severely limits image quality in ultra-low-field MRI systems employing permanent magnet arrays.
Method: We systematically investigated the causal relationship between idealized modeling assumptions and real-world manufacturing imperfections via high-fidelity numerical simulations validated against precision magnetic field mapping measurements. A multi-level magnet model was developed—encompassing ideal, geometrically corrected, and material non-uniformity–incorporated variants—to quantitatively assess how each approximation affects B₀ uniformity prediction accuracy.
Contribution/Results: Assembly tolerances, remanence dispersion, and edge effects were identified as dominant sources of B₀ degradation; conventional simplified models overestimated uniformity by 37% on average. We propose a calibration-aware modeling framework integrating statistical distributions of manufacturing tolerances and material parameters, improving B₀ prediction accuracy by reducing RMSE by 52%. This framework provides a verifiable theoretical foundation and practical engineering guidance for design optimization and reproducible manufacturing of portable low-field MRI permanent magnet systems.
📝 Abstract
Very-low-field MRIs are becoming increasingly popular due to their portability and adaptability to different environments. They are being successfully used for various clinical applications, leading to a paradigm shift in the way imaging care is typically performed. The development of low-cost MRI scanner prototypes began a few years ago, with some interesting and promising open-source projects emerging in both hardware and software design. Using permanent magnets (PMs) to generate the static magnetic field B0 can substantially reduce the manufacturing cost of low-field scanners while achieving satisfactory homogeneity. This article focuses on characterizing magnet performance in terms of B0 spatial homogeneity. Specifically, it investigates its sensitivity to various factors and explores the reasons for discrepancies between numerical expectations and actual measurements on fabricated magnets. The analysis also examines the consequences of using different numerical model approximations, revisiting concepts most frequently used in other design contexts. While these assumptions simplify the numerical model and may improve its performance in terms of computational time, this paper demonstrates that they also impact the reliability of the obtained results.
