MRI Control Device Optimizing Gradient and Shim Subsystems
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Solution Overview
Problem
Current imaging systems, such as magnetic resonance systems, require complex and time-consuming optimization of control sequences for different active volumes, necessitating detailed knowledge of subsystems and manual adjustments, which can lead to suboptimal image quality and increased risk of misinterpretation.
Innovation Solution
The method involves providing active volume position data to automatically generate control signals for subsystems, allowing for local optimization of functional sub-sequences without manual calculation, using a control device that can process sequence control data and active volume information to dynamically adjust technical subsystems for improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual optimization of control sequences is performed by operators with detailed subsystem knowledge, then image quality can be improved, but the process becomes time-consuming and complex
Solution Approach 1:
The control device automatically generates optimized control signals for subsystems based on active volume position data without requiring manual operator intervention. The system performs self-optimization by processing sequence control data and active volume information to dynamically adjust technical subsystems, eliminating the need for time-consuming manual optimization while maintaining or improving image quality
Solution Approach 2:
The system pre-provides active volume position data to the control device before measurement sequence execution. This preliminary provision of spatial information enables the control device to pre-calculate and generate optimized control signals for all subsystems in advance, reducing optimization time during actual operation while ensuring high image quality
2Manufacturing precision
If detailed manual adjustments of subsystems are made for different active volumes, then local optimization is achieved, but operator effort and complexity increase
Solution Approach 1:
The control device automatically performs local optimization for different active volumes by processing sequence control data and active volume position data. The system generates specific control signals for gradient and shim subsystems tailored to each active volume without requiring manual operator adjustments, achieving local optimization while minimizing operator effort to simply providing the necessary position data
Solution Approach 2:
The measurement sequence is divided into functional sub-sequences, each associated with a specific active volume. The control device processes each sub-sequence independently with its corresponding active volume position data, enabling localized optimization for each segment without requiring comprehensive manual adjustment of the entire system, thereby reducing overall operator effort
3Measurement precision
If comprehensive control of multiple subsystems is implemented, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The control device serves multiple functions by simultaneously managing sequence control data processing, active volume position data integration, and generation of control signals for multiple subsystems (gradient, shim, radio-frequency). This multi-functional approach consolidates control complexity into a single device while maintaining high measurement accuracy through coordinated subsystem optimization
Solution Approach 2:
The control device merges the processing of sequence control data and active volume position data into a unified control signal generation process. By combining these functions and coordinating multiple subsystems through a single control unit, the system manages complexity centrally while achieving comprehensive measurement accuracy through integrated subsystem control
Data Source
AI summary
In an imaging system having a number of subsystems and a control device that controls the subsystems in a coordinated manner to implement a measurement sequence and an operating method therefor, sequence control data that define different functional sub-sequences of the measurement sequence are transmitted to the control device. Different active volumes are associated with the functional sub-sequences. In addition to the sequence control data, active volume position data are provided to the control device that define bearing and extent of the active volumes associated with the different functional sub-sequences. Control signals to implement the measurement sequence for the different subsystems are generated automatically by the control device based on the sequence control data and the active volume position data so that the individual functional sub-sequences are locally optimized at least with regard to a sub-region of their associated active volume.