Semi-Automatic Tumor Segmentation with Interactive Feedback
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Solution Overview
Problem
Current tools for quantitative analysis in medical imaging lack the speed, precision, and consistency required for wider clinical use, making manual delineation of tumor boundaries time-consuming and prone to variable results.
Innovation Solution
A system and method for volumetric segmentation in medical images that combines automated segmentation with a real-time user interface, allowing radiologists to interactively confirm candidate structures and refine segmentation results, thereby enhancing efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual delineation is used to define tumor boundaries, then complete control and precision are achieved, but the process becomes time-consuming and produces variable results
Solution Approach 1:
The system performs preliminary automated segmentation to generate initial tumor boundaries before user review. This preliminary action provides a starting point that reduces the time needed for manual delineation while maintaining precision, as users only need to adjust the automated results rather than draw boundaries from scratch.
Solution Approach 2:
The system implements feedback by displaying the automated segmentation results to the user for review and adjustment. Users can interact with the system to correct boundaries, and the system incorporates these corrections to produce final segmentation. This feedback loop ensures precision while reducing time compared to purely manual methods.
2Productivity
If fully automated segmentation methods are used, then speed is improved, but precision and consistency are insufficient for clinical use
Solution Approach 1:
The system performs preliminary automated segmentation to generate initial tumor boundaries before user review. This preliminary action provides a starting point that reduces the time needed for manual delineation while maintaining precision, as users only need to adjust the automated results rather than draw boundaries from scratch.
Solution Approach 2:
The system implements feedback by displaying the automated segmentation results to the user for review and adjustment. Users can interact with the system to correct boundaries, and the system incorporates these corrections to produce final segmentation. This feedback loop ensures precision while reducing time compared to purely manual methods.
3Ease of operation
If manual delineation is performed by different users, then complete control is achieved, but variable results are produced due to variable performance
Solution Approach 1:
The system performs preliminary automated segmentation to generate initial tumor boundaries before user review. This preliminary action provides a starting point that reduces the time needed for manual delineation while maintaining precision, as users only need to adjust the automated results rather than draw boundaries from scratch.
Solution Approach 2:
The system implements feedback by displaying the automated segmentation results to the user for review and adjustment. Users can interact with the system to correct boundaries, and the system incorporates these corrections to produce final segmentation. This feedback loop ensures precision while reducing time compared to purely manual methods.
Data Source
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AI summary
A method for volumetric segmentation in a plurality of planar medical images includes, receiving, at an electronic processor, the plurality of planar medical images. A boundary of a candidate structure in the plurality of medical images is generated using a segmentation model. A first planar medical image from the plurality of planar medical images is displayed on a display. A user input is received using a user interface indicating a region in the first planar medical image. A first planar contour of the candidate structure is generated. The region is compared to the boundary. Responsive to the region being at least partially within the boundary, the first planar medical image is re-displayed on the display showing the first planar contour of the structure, and a finding record for the candidate structure including the boundary is generated.