Segmentation Highlighter for Real-Time Medical Imaging
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Solution Overview
Problem
Current 3D visualization techniques for segmenting and highlighting regions of interest in imaging data are time-consuming and require significant manual editing, often losing anatomical context and being computationally expensive, especially when dealing with structures near bones or small vessels.
Innovation Solution
A method that concurrently segments and highlights regions of interest using a computing device with a segmentor, highlighter, and highlight remover, allowing for real-time visualization and interaction, with highlighting rules determining color and texture, and enabling intuitive editing and measurement during the segmentation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the entire dataset is processed using existing segmentation techniques, then complete segmentation coverage is achieved, but computational cost and processing time increase significantly
Solution Approach 1:
The patent divides the imaging dataset into multiple sub-regions or sub-volumes that can be processed independently and in parallel. This allows the segmentation algorithm to work on smaller data chunks simultaneously, reducing the computational burden on single processing units while maintaining complete coverage of the entire dataset through aggregation of results.
Solution Approach 2:
The patent implements progressive or incremental segmentation where results are generated and visualized before complete processing of the entire dataset. This allows users to see partial results early in the process and potentially intervene or adjust parameters, effectively reducing the perceived processing time and allowing for staged computation rather than requiring complete processing before any output.
2Extent of automation
If automatic segmentation algorithms are embedded into clinical application software workflow, then specific segmentation goals are achieved, but flexibility and adaptability for different visualization needs are reduced
Solution Approach 1:
The patent creates a segmentation system that serves multiple functions: it can perform automated segmentation for clinical workflows, generate visualizations directly from segmentation results, allow manual editing and refinement, and support various output formats and visualization styles. This multi-functional approach allows the same system to adapt to different clinical needs and user preferences without requiring separate specialized tools.
Solution Approach 2:
The patent implements a dynamic workflow where the segmentation process can be adjusted, paused, and modified at multiple stages. Users can switch between automated and manual modes, adjust segmentation parameters dynamically, and modify visualization settings based on evolving clinical needs, making the system adaptable rather than rigidly fixed to a single workflow path.
3Manufacturing precision
If additional seed points and editing tools are used for reusing segmentations, then visualization accuracy is improved, but user time and operational complexity increase
Solution Approach 1:
The patent performs preliminary processing and preparation of segmentation results before they are needed for visualization. This includes pre-computing multiple possible visualization representations, pre-organizing segmentation data into reusable formats, and pre-validating segmentation quality. By doing this work in advance, the system reduces the amount of manual editing and adjustment users need to perform later, thereby improving ease of operation while maintaining accuracy.
4Shape
If bone is removed and vessels are segmented for 3D visualization, then vascular structure clarity is improved, but anatomical context is lost
Solution Approach 1:
The patent applies different processing qualities to different regions of the imaging data. Vessel regions are processed with high clarity and detail for accurate visualization, while surrounding anatomical structures are processed with appropriate but potentially lower detail. This local differentiation allows vessels to stand out clearly while maintaining the broader anatomical context in the background, resolving the contradiction between vessel clarity and contextual preservation.
Data Source
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AI summary
A method includes segmenting a region of interest in imaging data in a visual presentation of the imaging data and visually highlighting, concurrently with the segmenting, the region of interest while the region of interest is being segmented, wherein the visual highlighting includes coloring the region of interest while the region of interest is being segmented. A computer readable storage medium encoded with computer readable instructions, which, when executed by a processer, causes the processor to:segment a region of interest in imaging data in a visual presentation of the imaging data and visually highlight, concurrently with the segmenting, the region of interest while the region of interest is being segmented, wherein the visual highlighting includes coloring the region of interest while the region of interest is being segmented.