Mobile X-Ray Misalignment Detection for Image Quality Assurance
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Solution Overview
Problem
Mobile chest X-Ray imaging in ICU and ED settings often suffers from poor image quality due to sub-optimal patient positioning and equipment configuration, leading to projection errors and distortions that can result in erroneous measurements and potential life-threatening adverse events.
Innovation Solution
A computer-implemented method using Deep Learning techniques, including image classification and landmark detection, to automatically identify misalignments and distortions in X-Ray images, prompting a user interface to alert medical personnel of quality issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mobile X-Ray imaging is used in ICU and ED settings, then accessibility and speed of imaging are improved, but image quality deteriorates due to sub-optimal positioning and equipment configuration
Solution Approach 1:
The system automatically detects misalignment in X-Ray images and provides real-time feedback to the operator through visual indicators, enabling correction of positioning errors while maintaining mobile imaging advantages
Solution Approach 2:
The patent replaces manual assessment of image quality with automated computer-based detection systems that use image processing algorithms to objectively evaluate alignment and provide quantitative feedback
2Measurement precision
If manual assessment of X-Ray image quality is performed, then detection of misalignment is possible, but time consumption and subjectivity increase
Solution Approach 1:
The system performs self-assessment of image quality through automated algorithms that independently evaluate alignment without requiring manual intervention, thereby eliminating subjectivity and reducing time consumption
Solution Approach 2:
Manual visual assessment is replaced with automated computer-based detection systems that process images rapidly and provide objective, consistent evaluations of misalignment
3Manufacturing precision
If ideal positioning of patient and equipment is enforced, then image quality is improved, but ease of operation deteriorates due to difficult patient conditions and room constraints
Solution Approach 1:
The system provides real-time feedback on positioning quality, enabling operators to make informed adjustments within the constraints of patient condition and room layout, rather than requiring perfect positioning from the outset
Solution Approach 2:
The system detects and quantifies misalignment parameters, allowing operators to understand the degree and type of positioning error and make targeted corrections rather than attempting to achieve ideal positioning under difficult conditions
Data Source
AI summary
The invention provides a computer-implemented method for X-Ray image quality assurance. The method comprises acquiring X-Ray image data of a subject using a mobile X-Ray imaging system, the X-Ray image data comprising at least one X-Ray image, based on the X-Ray image data, performing an automatic image-based detection of imaging errors indicative of a misalignment of the X-Ray imaging system relative to the subject, and in response to detecting an imaging error indicative of a misalignment, prompting a display device to display a user interface comprising an indicator indicating a presence of the misalignment and/or an indicator indicating a type of the misalignment and/or an indicator indicating a degree of the misalignment.