Shim Coil Optimization via Reduced Parameter Space
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for homogenizing static magnetic fields in magnetic resonance apparatuses face challenges with high computational effort and hardware limitations, particularly when dealing with a large number of shim coils, leading to inefficient current settings and potential overheating issues.
Innovation Solution
A method using a filter method with a reduced parameter space, where two control parameters influence the norm of shim currents and a spatial weighting function, allowing for efficient optimization while considering hardware limitations without significant increased computation effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the number of shim coils is increased to improve magnetic field homogeneity, then the magnetic field homogeneity is improved, but the computational effort and complexity of current setting increases enormously
Solution Approach 1:
The patent transforms the high-dimensional current setting problem into a low-dimensional parameter optimization problem by expressing shim coil currents as functions of a small number of parameters (2-10 parameters instead of N currents). This parameterization dramatically reduces the complexity of finding optimal settings while maintaining the ability to achieve high magnetic field homogeneity with multiple shim coils.
2Manufacturing precision
If incremental improvement methods are used to optimize current settings, then the magnetic field homogeneity is improved, but the number of process steps increases enormously with increasing degrees of freedom
Solution Approach 1:
The patent changes the dimensionality of the optimization problem by moving from optimizing N current parameters directly to optimizing only 2-10 underlying parameters that control the current settings. This dimensional reduction transforms an intractable high-dimensional optimization into a manageable low-dimensional problem, dramatically reducing the number of process steps required.
3Manufacturing precision
If more shim coils are used to achieve better field homogeneity, then the magnetic field homogeneity is improved, but power consumption increases leading to overheating issues
Solution Approach 1:
The patent enables control over power consumption by parameterizing the current settings in terms of a small number of parameters. This allows the optimization process to simultaneously consider both field homogeneity quality and power consumption constraints, finding parameter values that achieve the desired homogeneity while keeping currents (and thus power consumption) within acceptable limits to avoid overheating.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the computational effort and effectively finds optimal shim current settings that minimize power consumption and adhere to hardware constraints, achieving better magnetic field homogeneity while avoiding excessive heating and hardware limitations.
Implementation Method 1
a magnetic resonance apparatus having a number N shim coils, wherein the method comprises the following steps: (a) Mapping the magnetic field distribution B0(r) of the static magnetic field
Data Source
AI summary
A method for homogenizing the static magnetic field with a distribution B0(r) in the active volume of a magnetic resonance apparatus having a number N of shim coils defines a target field distribution B0T(r) using a filter method in which a norm of the shim currents is influenced by means of filter factors. An optimization procedure works in a parameter space having M control parameters, wherein 2≦M<N. One of the control parameters is used as a weighting parameter for modification of a spatial weighting function and another control parameter is used to control the filter factors. Using this method the hardware limitations can be taken into account when determining the target field distribution, without a significant increase in the computational effort to determine the target field distribution during optimization.


