Superposition Image Discrepancy Detection in Fluoroscopy
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Solution Overview
Problem
The accuracy and quality of superposition images in fluoroscopy-guided interventions are compromised due to patient movement and anatomical deformation caused by surgical instruments, making manual correction time-consuming and error-prone, especially for untrained viewers.
Innovation Solution
A method for automatically checking the quality of superposition images by determining the discrepancy between reference and current positions of anatomical structures in real-time, using a computing unit to generate and display a measure of discrepancy, facilitating quasi-real-time correction and improved image alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual correction of superposition image discrepancies is performed, then correction capability is provided, but time consumption and error rate increase
Solution Approach 1:
The patent replaces the manual visual inspection and correction process with an automated computer-based system that uses image processing algorithms to detect discrepancies between fluoroscopic images and reference images, automatically calculate correction parameters, and generate corrected superposition images without human intervention
Solution Approach 2:
The system performs self-correction by automatically detecting alignment errors between the current fluoroscopic image and the reference image, computing the necessary transformation parameters, and generating the corrected superposition image independently, eliminating the need for manual correction by medical personnel
2Manufacturing precision
If superposition images are used to guide interventions, then positioning precision is improved, but image quality deteriorates due to patient movement and anatomical deformation
Solution Approach 1:
The patent implements a dynamic correction system that continuously detects and compensates for changes in patient position and anatomical deformation during the intervention by repeatedly comparing current fluoroscopic images with reference images and automatically updating the superposition alignment in real-time
Solution Approach 2:
The system establishes a feedback loop where the automated discrepancy detection continuously monitors alignment errors between fluoroscopic and reference images, and the computed correction parameters are fed back to generate improved superposition images, enabling continuous optimization of image quality throughout the procedure
3Productivity
If automated discrepancy detection is implemented, then evaluation speed is improved, but system complexity increases
Solution Approach 1:
The patent replaces complex manual visual assessment with automated computer-based image processing algorithms that efficiently compare fluoroscopic images with reference images, extract anatomical landmarks, calculate discrepancy parameters, and generate correction information without requiring sophisticated manual analysis by medical personnel
Data Source
AI summary
A method and computing unit are for automatically checking a superposition image of a body region of interest of an examination object. The method and computing unit include determining at least one reference position of an object in a reference image; determining a current position of the object; generating the superposition image by superimposing the current fluoroscopic image and the reference image; determining at least one parameter characterizing a measure of discrepancy; and displaying the measure of discrepancy determined. Further, in at least one embodiment, the various aspects of the method or performed by at least one processor of the computing unit, are performed in quasi real time.