Medical Imaging Preview Analysis for Immediate Quality Feedback
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Solution Overview
Problem
Existing medical imaging systems lack real-time image quality feedback capabilities, making it difficult to address quality concerns during the imaging procedure while the patient is present, and extensive modifications to the imaging device controller are costly and not modality-agnostic.
Innovation Solution
A system that taps into the imaging device controller's video feed to extract low-resolution preview images, using machine learning components to analyze these images for quality issues, and provides immediate feedback without modifying the controller.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the imaging device controller is modified to perform real-time image quality assessment, then immediate feedback capability is improved, but device complexity and recertification cost increase
Solution Approach 1:
The patent introduces an intermediary system consisting of a video capture device and image analysis software that monitors the controller display without modifying the controller itself. This intermediary approach enables real-time image quality assessment while avoiding direct integration into the imaging device controller, thus maintaining system simplicity and avoiding recertification requirements.
2Measurement precision
If retrospective quality assessment is performed on images uploaded to PACS, then quality review capability is improved, but feedback timeliness deteriorates as patients leave the imaging area
Solution Approach 1:
The system performs preliminary image quality assessment by capturing and analyzing preview images from the controller display in real-time during the imaging procedure. This preliminary action enables quality evaluation before the patient leaves the imaging area, allowing immediate feedback and potential re-imaging while the patient is still present, thus eliminating the time loss associated with retrospective PACS-based review.
3Measurement precision
If a modality-specific quality assessment system is implemented, then assessment accuracy for specific modalities is improved, but system adaptability to multiple modalities deteriorates
Solution Approach 1:
The patent implements a universal image quality assessment system that monitors the controller display through video capture and applies ML-based analysis applicable across multiple imaging modalities. The system extracts preview images from the display and performs quality assessment using modality-agnostic image analysis techniques, enabling broad adaptability while maintaining sufficient assessment accuracy across different imaging types through generalizable computer vision algorithms.
Data Source
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AI summary
An apparatus (1) for providing image quality feedback during a medical imaging examination includes at least one electronic processor (20) programmed to: receive a live video feed (17) of a display (6) of an imaging device controller (4) of an imaging device (2) performing the medical imaging examination; extract a preview image (12) from the live video feed; perform an image analysis (38) on the extracted preview image to determine whether the extracted preview image satisfies an alert criterion; and output an alert (30) when the extracted preview image satisfies the alert criterion as determined by the image analysis.