Vessel Segment Shape Extraction from Thresholded CT Boundaries
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for vessel segmentation in CT imaging are cumbersome and prone to inaccuracies due to user-dependent manual extraction and challenges with simulated dye injection, particularly when dealing with structures like blood vessels.
Innovation Solution
A method for automatic vessel segmentation using threshold-based classification and clustering to identify vessel boundaries, allowing for real-time feedback and reduced computational complexity through segment-by-segment rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual vessel extraction is performed by user, then accuracy of vessel extraction may be improved, but time spent by user increases and depends on user experience
Solution Approach 1:
The patent segments the vessel extraction process into discrete steps: identifying seed points within the vessel, growing regions from these seeds based on intensity thresholds, and iteratively refining the segmentation. This breaks down the complex manual extraction task into automated, manageable components that reduce user time investment while maintaining accuracy.
Solution Approach 2:
The patent implements feedback mechanisms where the system provides real-time visual feedback during the region growing process, allowing users to monitor and control segmentation progress. This interactive feedback loop enables users to achieve accurate results with minimal manual input compared to traditional fully manual extraction.
2Illumination intensity
If simulated dye injection function is used to highlight target tissue, then visualization of target tissue is improved, but leakage occurs due to vicinity of nearby structures such as bone
Solution Approach 1:
The patent dynamically adjusts intensity thresholds and region growing parameters to prevent leakage into nearby structures. By modifying the threshold values and growth criteria based on local image characteristics, the system maintains bright, clear vessel visualization while preventing false segmentation into adjacent bone or soft tissue structures.
Solution Approach 2:
The patent replaces the simulated dye injection mechanism with a region-based segmentation approach using intensity thresholds and connectivity analysis. This substitution eliminates the leakage problem inherent in dye-based methods by using mathematical criteria for region boundaries rather than diffusion-based visualization that spills into adjacent structures.
3Speed
If entire subject is re-rendered to provide feedback, then real-time feedback is improved, but computational resources increase
Solution Approach 1:
The patent segments the rendering process to update only the specific regions containing vessels that have been segmented, rather than re-rendering the entire subject volume. This localized rendering approach provides real-time visual feedback on segmentation progress while dramatically reducing computational resource requirements compared to full-volume re-rendering.
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
In an embodiment, a method (100) is described. The method comprises estimating (102) a pair of threshold values for being compared to radiographic imaging values to classify a region derived from radiographic imaging data of a subject based on whether or not a part of the region comprises a radiographic imaging value indicative of presence of a vessel. The method further comprises identifying (104), within a cross-section of the region, a boundary of the vessel based on a set of radiographic imaging values classified according to the pair of threshold values. The method further comprises determining (106) a segment shape of the vessel that connects the identified boundary of the vessel with another boundary of the vessel identified in a cross section of a further region adjacent to the region.