Coronary Lumen Contour Editing Using Multi-Frame Segmentation Uncertainty
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Solution Overview
Problem
Existing methods for segmenting coronary artery lumens in cardiac images are imprecise and unreliable due to uncertainties in imaging artifacts and single-frame analysis, making precise contour editing challenging, especially in interventional settings like PCI.
Innovation Solution
A method that processes multiple cardiac images from different time points of a cardiac cycle to determine local segmentation uncertainties, allowing for precise adjustment and editing of lumen segmentation contours using a computing device with a processor and memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard contour editing tools are used for manual annotation, then the segmentation can be precisely adjusted, but the editing process becomes time-consuming and complex
Solution Approach 1:
The system automatically determines the contour of the coronary artery lumen by processing multiple cardiac images through a computing device, eliminating the need for manual contour drawing by operators. The automated method performs segmentation without human intervention, thus resolving the contradiction between precision and time consumption.
Solution Approach 2:
The patent replaces manual mechanical editing operations with an automated computing-based image processing system. The computing device automatically analyzes multiple cardiac images to determine the lumen contour, substituting the mechanical interaction of manual contour drawing with automated computational analysis.
2Productivity
If single-frame analysis is used for lumen segmentation, then the processing is simple and fast, but the segmentation accuracy is reduced due to imaging artifacts and inability to capture lumen variations
Solution Approach 1:
The patent merges information from multiple cardiac images captured at different time points of the cardiac cycle into a unified lumen contour determination. By combining data from multiple frames, the system captures the full range of lumen diameter variations and overcomes limitations of single-frame analysis, improving segmentation accuracy while maintaining processing efficiency through automated multi-frame analysis.
3Productivity
If fully automated segmentation is used, then the processing time is reduced, but the reliability is lowered due to algorithm inaccuracies and imaging artifacts
Solution Approach 1:
The patent combines information from multiple cardiac images to determine the lumen contour, merging data that captures different phases of the cardiac cycle. This multi-frame approach improves reliability by providing a more comprehensive view of the lumen geometry, reducing the impact of artifacts present in any single frame, while maintaining automated processing efficiency.
Data Source
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AI summary
Techniques for adjusting or editing respective segments of a contour of a given lumen segmentation of a portion of coronary arteries are described. The respective segments of the contour are adjusted by processing multiple cardiac images. Each of the multiple cardiac images depicts a portion of coronary arteries, i.e., the same portion of coronary arteries, within an anatomical region of interest. Respective magnitudes of one or more local segmentation uncertainties are determined based on the multiple cardiac images. Each of the one or more local segmentation uncertainties is associated with a respective segment of the contour of the given lumen segmentation. The respective segments of the contour are adjusted edited or manipulated based on the respective magnitudes of the one or more local segmentation uncertainties.