Magnetic Resonance Acquisition Assistance With Real-Time Quality Feedback
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Solution Overview
Problem
Magnetic resonance data acquisition is hindered by factors such as B0 magnetic field inhomogeneity, gradient field strength, local coil quality, patient movement, and operator experience, leading to suboptimal image quality and inefficiencies in diagnostic imaging.
Innovation Solution
An assistance system with analysis modules that evaluate magnetic resonance data and additional measurement information in real-time, providing assistance information to users via a user interface to address issues like image quality, patient movement, and hardware defects, offering suggestions for corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If measurement programs are executed with default settings and standard acquisition protocols, then the examination process is simple and quick to initiate, but the image quality and diagnostic accuracy are suboptimal due to lack of adaptive optimization
Solution Approach 1:
The system performs preliminary actions by automatically acquiring patient-specific anatomical data and physiological parameters before the main measurement program executes. This preliminary characterization enables subsequent adaptive optimization of imaging parameters without requiring complex manual configuration during the examination, thus improving image quality while keeping the examination process simple to initiate.
Solution Approach 2:
The assistance system enables self-service by automatically analyzing acquired data, determining optimal measurement parameters, and adapting the imaging protocol without requiring expert intervention. The system serves itself by autonomously optimizing image quality based on real-time data analysis, eliminating the need for highly experienced operators to manually tune complex parameters.
2Manufacturing precision
If experienced medical personnel manually optimize measurement parameters based on extensive experience, then image quality and diagnostic accuracy improve, but the examination time and operational complexity increase
Solution Approach 1:
The system implements continuous feedback loops where measurement data is acquired, analyzed in real-time, and used to dynamically adjust imaging parameters. This automated feedback mechanism replicates the decision-making process of experienced operators but executes it much faster, improving image quality without extending examination time, as the parameter optimization occurs automatically during the acquisition process rather than requiring manual iteration.
Solution Approach 2:
The patent replaces the mechanical system of manual parameter adjustment by experienced operators with an automated computational system. Instead of relying on human cognitive processing and manual intervention, the system uses algorithmic analysis and automatic parameter optimization, which processes data much faster than human operators can manually adjust settings, thereby maintaining high image quality while reducing examination time.
3Reliability
If robust measurement sequences are used to compensate for patient movement and hardware defects, then reliability of image acquisition improves, but adaptability to individual patient conditions and hardware configurations is reduced
Solution Approach 1:
The system applies local quality by tailoring measurement parameters and acquisition strategies to specific local conditions detected in the patient's anatomy and hardware configuration. Rather than using uniform robust sequences for all cases, the system analyzes patient-specific features and hardware characteristics, then adapts parameters locally to optimize both reliability and adaptability for each individual examination scenario.
Solution Approach 2:
The measurement sequences transition from static, pre-defined robust protocols to dynamic, adaptive sequences that adjust in real-time based on acquired data. The system continuously monitors patient condition and hardware performance, dynamically modifying acquisition parameters to maintain reliability while adapting to individual patient conditions and specific hardware configurations, thus achieving both robustness and versatility.
Data Source
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AI summary
The invention is based on a computer-implemented method for supporting and/or assisting a user by means of an assistance system when executing a measurement program during magnetic resonance data acquisition, comprising the steps of: - selecting a measurement program for acquiring magnetic resonance data, - executing the selected measurement program and providing the magnetic resonance data and/or image data reconstructed from the magnetic resonance data, - acquiring further measurement information, wherein the further measurement information is acquired before executing the selected measurement program or during executing the selected measurement program, and providing the further measurement information, - determining at least one piece of evaluation information by means of at least one analysis module of the assistance system depending on the magnetic resonance data and/or image data and/or the further measurement information,and providing the at least one piece of evaluation information, - generating assistance information, wherein the assistance information is generated as a function of the at least one piece of evaluation information by means of the at least one analysis module, and providing the assistance information and - outputting the assistance information to a user.,