Automated MR Image Quality Inspection and Parameter Adjustment
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Solution Overview
Problem
Manual quality inspection of MR images in magnetic resonance scanners is prone to errors, leading to repeated examinations, increased patient risk, and costs due to the time-consuming nature of evaluating image quality, which can result in suboptimal image quality and unnecessary re-scans.
Innovation Solution
An automated method for generating MR images that includes performing quality inspections and adjusting parameters or procedures to improve image quality, reducing the need for manual intervention and shortening patient wait times by automatically modifying settings such as signal-to-noise ratios, movement detection, and protocol selection based on predefined thresholds and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual quality inspection is performed by trained operators, then image quality assessment can be conducted, but the process is time-consuming and prone to errors leading to repeated examinations
Solution Approach 1:
The system performs automatic self-inspection of MR image quality using computerized algorithms that evaluate images against predefined quality criteria, eliminating the need for manual operator assessment and enabling immediate quality determination without patient waiting time
Solution Approach 2:
The patent replaces the manual mechanical inspection process with an automated computerized evaluation system that uses algorithms to assess image quality metrics, substituting human operators with an automated digital assessment mechanism
2Reliability
If manual quality inspection is performed, then image quality can be evaluated, but incorrect results may occur requiring repeated examinations
Solution Approach 1:
The system implements automatic feedback loops where quality inspection results immediately trigger appropriate actions - either proceeding to the next examination or automatically initiating corrective measures such as parameter adjustments or re-scan protocols, ensuring high reliability without reducing throughput
Solution Approach 2:
The patent performs preliminary automatic quality assessment immediately after image acquisition to identify potential quality issues before they require manual review, enabling early intervention and preventing the need for repeated examinations
3Object-affected harmful factors
If repeated examinations are performed due to low image quality, then patient safety risks increase, but automated quality inspection and correction is needed
Solution Approach 1:
The system implements beforehand cushioning by performing preliminary quality checks and automatically applying corrective actions before low-quality images are finalized or repeated scans are initiated, preventing patient exposure to unnecessary repeated radiation or contrast agent administration
Solution Approach 2:
The patent introduces an automated quality control intermediary system that acts as a mediator between image acquisition and clinical decision-making, using computerized algorithms to assess quality and trigger appropriate responses without requiring complex manual intervention protocols
4Manufacturing precision
If automated quality inspection and parameter adjustment is implemented, then image quality improves and re-scans are reduced, but system complexity increases
Solution Approach 1:
The system automatically adjusts acquisition parameters such as signal-to-noise ratio thresholds, movement detection settings, and protocol selection based on real-time quality assessment, dynamically optimizing image quality through parameter modification without requiring complex hardware changes
Solution Approach 2:
The patent implements dynamic adaptation where the quality inspection system continuously monitors image quality metrics and automatically modifies acquisition parameters or protocols in real-time, creating a flexible responsive system that adapts to varying imaging conditions
Data Source
AI summary
An embodiment of the invention relates to the generation of MR images of a volume section within an examination object by way of a magnetic resonance scanner. In at least one embodiment, the following steps are performed: generating at least one of the MR images; automatically performing a number of quality inspections on the at least one MR image; and, should one of these quality inspections fail, an action is automatically performed in order to improve a quality when generating more of the MR images.