Abstract
In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B(0)) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B(0) uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using Linear Programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming. This work aims to improve the efficacy of passive shimming by optimally balancing field quality, iron usage, and harmonics, leading to a smoother field profile. This study introduces a hybrid algorithm that combines a Pattern Search Algorithm with Sequential Quadratic Programming (PSA-SQP) to enhance shimming performance. Additionally, a regularization method is employed to effectively reduce the use of iron pieces. The magnetic field improved from 462 ppm to 6.7 ppm, utilizing merely 0.8 kg of iron in a 400 mm Diameter of Spherical Volume (DSV) of a 7T MRI magnet. Compared to traditional LP optimization techniques, this method notably enhanced magnetic field uniformity by 98.5% and reduced the iron weight requirement by 91.7%, showcasing impressive performance. The proposed new passive shimming algorithm is more effective in improving magnetic field uniformity for MRI applications.