Design of Gradient Coil for Magnetic Resonance Imaging Applying Particle-Swarm Optimization

Designing a gradient coil for magnetic resonance imaging (MRI) is an electromagnetic inverse problem often formulated as a constrained optimization, which has been successfully solved by inverse boundary element methods. The constant search for new coil features and improved performance has highligh...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2011-12, Vol.47 (12), p.4761-4768
Main Authors: Cobos Sanchez, Clemente, Fernandez Pantoja, Mario, Gomez Martin, Rafael
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Boundary element methods
Coils
Cross-disciplinary physics: materials science
rheology
Exact sciences and technology
Magnetic resonance imaging
Magnetism
Materials science
Optimization methods
Other topics in materials science
Particle swarm optimization
Physics
Studies
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Summary:Designing a gradient coil for magnetic resonance imaging (MRI) is an electromagnetic inverse problem often formulated as a constrained optimization, which has been successfully solved by inverse boundary element methods. The constant search for new coil features and improved performance has highlighted the need of employing more versatile optimization techniques capable of dealing with the new requirements. In this paper, the solution of linear and nonlinear optimization problems using particle-swarm optimization (PSO) algorithms is presented. Examples of coil designed using this heuristic method are shown, including a comparison to solutions provided by conventional optimization approaches. Numerical experiments reveal that the application of PSO for the solution of inverse boundary element problems for coil design is a computationally efficient algorithm that is capable of handling nonlinear problems and that offers fast convergence, especially for those symmetric coil geometries where the computational effort can be drastically reduced by using suitable dimensionality-reduction techniques.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2011.2159510