Optimal Phase Surface RF Pulse Design for Magnetic Resonance
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Solution Overview
Problem
Current methods for designing RF pulses in magnetic resonance experiments rely on pre-determined shapes and idealized assumptions, which are inadequate for large flip angles and spin echo pulses, leading to hardware limitations and reduced performance.
Innovation Solution
A bottom-up approach using a computer system to generate RF pulses without pre-determined shapes, tailored to user-specific problems, by iteratively updating an initial RF pulse profile based on input parameters and utilizing a neural network trained on optimal phase surface data to select desired RF pulse profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pre-determined RF pulse shapes are used, then the design process is simplified, but the performance is reduced for large flip angles and spin echo pulses
Solution Approach 1:
The patent changes the fundamental parameters of RF pulse design from fixed pre-determined shapes to dynamically optimized parameters. The system iteratively adjusts pulse amplitude, duration, and phase parameters based on desired experimental conditions, transforming the design process from static template selection to dynamic parameter optimization, thereby achieving both ease of use and high performance
Solution Approach 2:
The patent introduces dynamics into RF pulse design by enabling real-time adjustment and optimization of pulse parameters based on user-specific experimental requirements. The system evolves from static pre-determined shapes to dynamic, adaptable pulse designs that can be customized for different flip angles, bandwidth requirements, and experimental scenarios, improving both reliability and ease of manufacture
2Device complexity
If idealized assumptions are made in RF pulse design, then the design process becomes simpler, but hardware limitations are not accounted for
Solution Approach 1:
The patent implements feedback mechanisms that allow the system to learn from actual hardware performance and adjust pulse designs accordingly. By iteratively optimizing pulse parameters based on real experimental conditions and hardware capabilities, the system ensures hardware compatibility while maintaining simple design processes, resolving the contradiction between design simplicity and hardware reliability
Solution Approach 2:
The patent performs preliminary optimization of RF pulse parameters before actual experimentation, taking into account anticipated hardware limitations. The system pre-calculates and optimizes pulse designs based on expected hardware performance characteristics, ensuring that the pulses are compatible with actual hardware capabilities while keeping the design process simple
3Ease of operation
If standard RF pulse designs are used, then the implementation is easier, but bandwidth and signal-to-noise ratio are not optimized
Solution Approach 1:
The patent makes RF pulse implementation dynamic by enabling real-time optimization of bandwidth and signal-to-noise ratio parameters. The system automatically adjusts pulse characteristics based on desired experimental outcomes, transforming static standard pulses into dynamic, optimized pulses that maintain ease of operation while significantly improving measurement precision
Solution Approach 2:
The patent optimizes bandwidth and signal-to-noise ratio by dynamically changing pulse parameters such as amplitude, duration, and phase. The system iteratively adjusts these parameters to achieve optimal performance for each specific experimental condition, maintaining ease of operation through automated optimization while improving measurement precision
Data Source
AI summary
The present disclosure provides a method for producing a radio frequency (RF) pulse for use in magnetic resonance. The steps of the method include providing a computer system and a set of RF input parameters. The computer system then generates an optimal phase surface by iteratively updating an initial RF pulse profile based at least in part on the set of RF input parameters. The optimal phase surface contains a set of iteratively generated RF pulse profiles with various characteristics, such as bandwidths or selectivity. The steps of the method further include selecting an RF pulse profile with the computer system based on a search on the optimal phase surface, which can be implemented with the help of an index file. The search can be performed using an artificial intelligence algorithm, and can retrieve the shortest pulse profile that satisfies user input parameters or requirements.