Medical Imaging Control Device with Automated IQA Algorithms
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Solution Overview
Problem
Current medical imaging systems face challenges in ensuring consistent image quality due to the need for expert technicians, variability in scanner settings, and the risk of inadequate image quality leading to patient recalls, misdiagnosis, and inefficiencies in scanning processes.
Innovation Solution
An automated control device with an Image Quality Assessment (IQA) unit that uses algorithms to evaluate image quality during or after image capture, allowing for automatic control of the imaging system, including adjustments to recording parameters and patient instructions, to ensure minimum diagnostic image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual image quality check is performed by technician, then image quality assessment is possible, but reliability depends on technician's expertise and experience
Solution Approach 1:
The imaging system performs automatic self-assessment of image quality using embedded algorithms that evaluate image data without requiring external expert intervention. The system independently determines quality metrics and makes decisions about whether images meet diagnostic standards.
Solution Approach 2:
The patent replaces the manual mechanical process of expert technician review with automated computational algorithms. These algorithms process image data and quality metrics automatically, substituting human expertise with machine-based assessment systems.
2Measurement precision
If experienced technicians perform manual quality assurance, then accurate assessment is achieved, but training time and practical experience are required
Solution Approach 1:
The system pre-loads and executes quality assessment algorithms during the imaging process itself, rather than requiring post-acquisition manual review. Quality metrics are calculated in advance as images are acquired, eliminating the need for separate expert review steps.
Solution Approach 2:
Complex computational algorithms replace the years of training and experience that technicians would otherwise need to acquire. The automated system instantly performs quality assessments that would otherwise require extensive human expertise and time investment.
3Ease of operation
If automated IQA algorithms are implemented, then expert technician requirement is reduced, but integration into imaging system is required
Solution Approach 1:
The quality assessment algorithms are merged with the existing imaging system architecture, sharing common hardware resources such as processors, memory, and data buses. The IQA functionality is integrated into the same computational environment that already processes imaging data.
Solution Approach 2:
The imaging system's existing hardware components are designed to serve multiple functions - the same processor that reconstructs images also executes quality assessment algorithms, and the same memory that stores image data also holds quality metrics. This multi-functionality reduces the need for separate dedicated hardware.
4Reliability
If manual image quality checking is performed, then quality feedback is provided, but patient recalls and rescanning occur due to inadequate quality assessment
Solution Approach 1:
The system implements continuous feedback loops where quality metrics are calculated during image acquisition and immediately fed back to control the imaging process. If quality thresholds are not met, the system automatically triggers alerts or protocol adjustments in real-time, preventing inadequate images from being finalized.
Solution Approach 2:
Quality assessment is performed preliminarily during the imaging acquisition process itself, rather than as a separate post-processing step. This allows the system to identify quality issues immediately and take corrective action before the imaging session is completed, avoiding patient recalls.
Data Source
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AI summary
The invention relates to a control device (13) for controlling a medical imaging system (1), wherein the control device (13) comprises an IQA unit (20) which contains a number of IQA algorithms (21, 21a) and is designed to generate a quality measure (S, R) after or during the application of a control protocol (P) for the acquisition of this image data (B) by the medical imaging system (1), wherein the quality measure (S, R) evaluates the quality of the image data (B), and wherein the control device (13) is designed to automatically control the medical imaging system (1) based on the quality measure (S, R). The invention further relates to a method for controlling a medical imaging system and to a corresponding medical imaging system.