MRI Permanent Magnet Design Using Neural Networks for Field Homogeneity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing MRI devices using superconducting magnets are costly, bulky, and require liquid helium, limiting their portability and accessibility, while permanent magnets suffer from low magnetic field homogeneity, hindering their imaging quality and widespread use.
Innovation Solution
A method and system utilizing a deep neural network to design a permanent magnet by simulating a target magnetic field map, constructing a parametric model, and determining a three-dimensional spatial structure and material distribution to enhance field intensity and homogeneity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If superconducting magnets are used to provide high magnetic field intensity and homogeneity, then imaging quality is improved, but device cost, size, and complexity increase significantly
Solution Approach 1:
The patent replaces expensive superconducting magnets with affordable permanent magnets made of neodymium iron boron. Although permanent magnets have lower magnetic field intensity individually, the patent uses arrays of multiple permanent magnets to achieve the required magnetic field strength for MRI, thereby reducing overall device cost and complexity while maintaining imaging quality
Solution Approach 2:
The patent divides the magnetic field generation system into multiple permanent magnet blocks arranged in specific patterns. Instead of using a single large superconducting magnet, the system employs arrays of smaller permanent magnets that can be strategically positioned to create the necessary magnetic field homogeneity and intensity for high-quality imaging
2Ease of operation
If permanent magnets are used to reduce cost and improve portability, then device mobility is improved, but magnetic field homogeneity deteriorates
Solution Approach 1:
The patent segments the magnetic field generation into multiple permanent magnet blocks arranged in specific three-dimensional patterns. By carefully positioning and orienting these segmented magnets, the system achieves magnetic field homogeneity comparable to superconducting magnets while maintaining the portability and lower cost advantages of permanent magnet technology
Solution Approach 2:
The patent applies different magnetic block arrangements and orientations in different regions of the magnet array to optimize local magnetic field characteristics. This local quality approach allows each region to contribute optimally to the overall magnetic field homogeneity while maintaining system portability
3Productivity
If genetic algorithm is used to optimize magnet design, then some optimization is achieved, but the algorithm cannot effectively explore the relationship between magnetic field and magnetic block arrangement
Solution Approach 1:
The patent employs a feedback mechanism where the magnetic field generated by a permanent magnet array is simulated, and the results are used to adjust and optimize the arrangement of magnetic blocks. This iterative feedback process enables the system to effectively explore and optimize the complex relationship between magnetic block configuration and magnetic field characteristics
Solution Approach 2:
The patent replaces traditional mechanical optimization methods with computational simulations and artificial intelligence algorithms. By using computer-based magnetic field simulations and machine learning models, the system can efficiently explore the complex relationship between magnetic block arrangement and magnetic field properties, achieving superior optimization compared to conventional methods
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
Improves magnetic field intensity and homogeneity of permanent magnets, enabling better imaging quality and facilitating the development of portable MRI devices suitable for remote and emergency medical applications.
Implementation Method 1
obtaining a target magnetic field map of a target magnetic block set, where the target magnetic field map is obtained by simulating an actual magnet constructed from the target magnetic block set
Data Source
AI summary
Disclosed is a method and system for designing a magnetic resonance imaging permanent magnet, a device, and a medium. The method includes: obtaining a target magnetic field map of a target magnetic block set, and the target magnetic block set is a set of target magnetic blocks corresponding to a number of target magnetic blocks determined based on a total mass of a set magnet; inputting the target magnetic field map into a parametric model to obtain a parameterized matrix, where the parameterized matrix includes a candidate spatial position number of each target magnetic block, spatial position coordinates of a center of each target magnetic block, an angle of each target magnetic block, and material distribution of each magnetic block, and the parametric model is constructed based on a deep neural network; and determining a three-dimensional spatial structure and material distribution of a permanent magnet based on the parameterized matrix.