Medical Image Segmentation via Motion-Adaptive Control Points
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Solution Overview
Problem
Current image segmentation methods in medical imaging are inefficient and unreliable due to limitations in utilizing user-initiated motions, particularly in 3D image delineation, which requires high accuracy and is time-consuming, especially for structures that require precise mouse movements and manual contouring.
Innovation Solution
A device and method that translate user-initiated motion into a first contour, register motion parameters such as speed and acceleration, and distribute image control points with decreasing density to enhance segmentation accuracy, using active contour, model-based segmentation, and graph cut algorithms to determine a second contour for improved image segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual contouring is used for 3D image delineation, then segmentation accuracy is improved, but time consumption increases significantly
Solution Approach 1:
The patent segments the contouring process into two distinct stages: an automatic segmentation phase that generates an initial contour rapidly, and an interactive refinement phase where users adjust only the necessary parts. This segmentation of the workflow allows the system to achieve both speed (from automatic processing) and accuracy (from interactive refinement), resolving the contradiction between time consumption and segmentation accuracy.
Solution Approach 2:
The system performs preliminary automatic segmentation to create an initial contour before user intervention. This preliminary action handles the bulk of the contouring work automatically, reducing the time users would otherwise spend on manual contouring while maintaining the opportunity for high accuracy through subsequent refinement.
2Productivity
If automatic processing is used for image segmentation, then processing speed is improved, but reliability decreases due to image acquisition errors and ambiguities
Solution Approach 1:
The patent implements a feedback mechanism where the system automatically processes the image to generate an initial contour, then allows users to review and correct this contour based on their expertise. The user's corrections feed back into the final segmentation result, ensuring reliability while maintaining the speed benefits of automatic processing.
Solution Approach 2:
The system applies different quality levels to different parts of the segmentation process: automatic processing is used for the overall contour generation (providing speed), while interactive correction is applied locally to regions where automatic processing may have failed or produced inaccurate results (ensuring reliability).
3Reliability
If interactive segmentation with user input is used, then segmentation reliability is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal segmentation system that can handle multiple segmentation tasks and image types through a single integrated framework. The system combines automatic processing capabilities with interactive correction tools in one unified interface, reducing the complexity that would otherwise arise from needing separate systems for different segmentation approaches.
Data Source
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AI summary
The present invention relates to a device for segmenting an image (12) of a subject (14), comprising a data interface (16) for receiving an image (12) of said subject (14), said image (12) depicting a structure of said subject (14), a translation unit (20) for translating a user-initiated motion (22) of an image positioner means (24) into a first contour surrounding said structure, a motion parameter registering unit (26) for registering a motion parameter of said user-initiated motion (22) to said first contour, said motion parameter comprising a speed and/or an acceleration of said image positioner means (24), an image control point unit (28) for distributing a plurality of image control points on said first contour with a density decreasing with said motion parameter, and a segmentation unit (30) for segmenting said image by determining a second contour within said first contour based on said plurality of image control points (28), said segmentation unit (30) being configured to use one or more segmentation functions.