Colon Rendering Segmentation for Residual Material Highlighting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In medical imaging, particularly in colon rendering, residual materials like stool or fluids can be difficult to distinguish from colonic tissue due to similar radiation attenuation values, leading to confusion and increased workload for clinicians as they may obscure or mimic polyps, especially in bowel preparations where these materials can be highlighted or obscured.
Innovation Solution
A method and apparatus for rendering the interior of the colon using volumetric data from CT scans, which identifies and highlights regions suspected of containing residual stool by segmenting and dilating the data set to differentiate between residual materials and polyps, using techniques like thresholding and dilation to ensure accurate visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contrast media is administered to highlight residual materials, then residual materials become more visible, but they can still obscure or mimic polyps leading to diagnostic confusion
Solution Approach 1:
The patent segments the colon lumen into multiple cross-sectional slices and processes each slice independently to identify and highlight residual materials. By dividing the volumetric data into discrete segments, the system can apply specific highlighting algorithms to distinguish residual materials from polyps in each segment, reducing diagnostic confusion while maintaining visibility.
Solution Approach 2:
The patent applies different visual properties (transparency, color, texture) to different regions of the rendered colon based on local characteristics. Residual materials are highlighted with specific visual properties that differ from polyps and normal tissue, allowing clinicians to distinguish between them while maintaining the overall three-dimensional context.
2Object-affected harmful factors
If residual materials are highlighted with different visual properties, then they can be distinguished from polyps, but the rendering complexity increases
Solution Approach 1:
The patent applies highlighting only to specific regions where residual materials are detected, rather than uniformly highlighting the entire colon. The system uses threshold-based detection to identify regions with high probability of containing residual materials and applies visual differentiation selectively to those regions, reducing overall rendering complexity.
Solution Approach 2:
The patent creates a separate rendered representation of the colon with highlighted residual materials while maintaining the original rendering for comparison. This allows clinicians to view both the standard rendering and the highlighted version, reducing the need for complex real-time switching between different rendering modes.
3Measurement precision
If multiple cross-sectional slices are processed to identify residual materials, then identification accuracy improves, but processing time increases
Solution Approach 1:
The patent performs preliminary processing of the volumetric data by pre-segmenting the colon into cross-sectional slices and pre-identifying potential residual material regions before final rendering. This preliminary segmentation and identification phase allows the system to prepare highlight masks in advance, reducing processing time during actual rendering while maintaining high identification accuracy.
Solution Approach 2:
The patent implements dynamic processing where the level of slice-by-slice analysis can be adjusted based on clinical needs. The system can process all slices for maximum accuracy or selectively process only suspicious regions identified by preliminary scanning, allowing flexible trade-off between processing time and identification accuracy based on the specific clinical scenario.
Data Source
Figure 1a~1b
Figure 2
AI summary
A rendering method uses volumetric data (202) indicative of the interior of an object to render a surface (102). Locations in the volumetric data (202) having a first parameter are identified. Regions on the rendered surface (102) which are located in proximity to the identified locations are highlighted, for example by using different visuals.