A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm
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. Traditio...
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| Vydáno v: | Scientific reports Ročník 15; číslo 1; s. 28419 - 10 |
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| 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. |
|---|---|
| AbstractList | In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B0 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. 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. In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B ) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B 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. In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B0 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.In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B0 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. Abstract In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B0 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. In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B0 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. |
| ArticleNumber | 28419 |
| Author | Xia, Ling Fan, Yifeng Zhu, Minhua Liu, Feng Zhao, Jie |
| Author_xml | – sequence: 1 givenname: Jie surname: Zhao fullname: Zhao, Jie organization: School of Medical Imaging, Hangzhou Medical College – sequence: 2 givenname: Minhua surname: Zhu fullname: Zhu, Minhua organization: School of Medical Imaging, Hangzhou Medical College – sequence: 3 givenname: Ling surname: Xia fullname: Xia, Ling organization: Key Laboratory of Biomedical Engineering, Ministry of Education, Zhejiang University – sequence: 4 givenname: Yifeng surname: Fan fullname: Fan, Yifeng email: fanyifeng@hmc.edu.cn organization: School of Medical Imaging, Hangzhou Medical College – sequence: 5 givenname: Feng surname: Liu fullname: Liu, Feng organization: School of Information Technology and Electrical Engineering, The University of Queensland |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40760142$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1109/20.119968 10.1109/TASC.2017.2732285 10.1002/mp.16538 10.1109/TMAG.2007.916267 10.1109/TMAG.2005.845080 10.1109/TASC.2011.2112358 10.1201/9780203758731-1 10.1007/s10948-019-05241-2 10.1109/ASEMD.2015.7453633 10.1016/j.jmr.2015.05.004 10.1016/j.neucom.2015.07.025 10.1007/s11431-013-5169-6 10.1016/j.asoc.2012.12.025 10.1002/mrm.1910010107 10.1016/j.pnsc.2009.04.007 10.1016/j.jmr.2015.11.019 10.1002/mp.17403 |
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| Keywords | Pattern search algorithm Passive shimming Magnetic resonance imaging Sequential quadratic programming Hybrid optimization |
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| Snippet | In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B
0
) is essential for producing detailed images of human anatomy. Passive... In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B ) is essential for producing detailed images of human anatomy. Passive... In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive... Abstract In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy.... |
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| SubjectTerms | 639/166 639/705 639/766 Algorithms Humanities and Social Sciences Hybrid optimization Integer programming Iron Linear programming Magnetic fields Magnetic resonance imaging multidisciplinary NMR Nuclear magnetic resonance Optimization algorithms Passive shimming Pattern search algorithm Regularization methods Science Science (multidisciplinary) Sequential quadratic programming |
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| Title | A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm |
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