Active Contour Image Segmentation for Medical Tumor Delineation
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Solution Overview
Problem
Manual image segmentation in medical imaging, such as tumor delineation for radiation therapy, is laborious, error-prone, and inconsistent due to reliance on manual processes and parameter tuning, leading to variability in results.
Innovation Solution
An automated or semi-automated two-pass image segmentation technique generates multiple contours of an object, with a secondary algorithm evaluating and ranking them based on fitness metrics to reduce variability and user interaction for selecting the final segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual contouring is performed by a physician, then the segmentation can be customized to specific medical judgment, but the process is laborious and introduces error and inconsistency
Solution Approach 1:
The system enables automated self-service segmentation where the computer automatically generates contours without requiring manual physician intervention. The active contour algorithm autonomously identifies and delineates tumor boundaries, eliminating human labor while maintaining consistent results through algorithmic precision rather than human variability.
Solution Approach 2:
The patent replaces the manual mechanical process of physician contouring with an automated computational system. The active contour algorithm uses image processing and mathematical optimization to substitute human manual tracing, thereby eliminating labor-intensive operations while improving consistency through deterministic computational methods.
2Productivity
If automated segmentation algorithms are used, then productivity increases, but the results require extensive parameter tuning and trial-and-error
Solution Approach 1:
The system performs self-configuration by automatically determining optimal segmentation parameters without user intervention. The active contour algorithm adapts to image characteristics autonomously, eliminating the need for users to manually tune parameters or perform trial-and-error adjustments, thus maintaining high productivity while reducing operational complexity.
Solution Approach 2:
The patent implements adaptive parameter adjustment where the algorithm automatically modifies segmentation parameters based on image-specific characteristics. Rather than requiring fixed manual configuration, the system dynamically optimizes parameters during execution, thereby maintaining computational efficiency while eliminating complex user-side parameter tuning.
3Measurement precision
If multiple potential solutions are generated, then the accuracy of segmentation improves through evaluation and selection, but the complexity of the system increases
Solution Approach 1:
The patent divides the segmentation process into distinct phases: generation of multiple candidate contours followed by evaluation and selection. This segmentation of the computational process allows the system to explore multiple potential solutions independently, then systematically evaluate them using fitness metrics, thereby improving accuracy through comprehensive search while managing complexity through structured processing stages.
Solution Approach 2:
The system implements feedback mechanisms where candidate contours are evaluated against fitness metrics that measure segmentation quality. This feedback loop allows the algorithm to assess multiple solutions, compare them against established criteria, and select the optimal contour, thereby improving measurement precision through systematic evaluation while maintaining manageable complexity through quantitative assessment.
Data Source
AI summary
An image segmentation system is discloses that provides one or more possible contours of a feature of an image, in parallel, that respectively correspond to different interpretations of the image. First, a relatively large set of possible contours are generated in accordance with an image segmentation algorithm. Subsequently, this set of possible contours is reduced to a few candidates reflecting representative solutions corresponding to one or more desired applications.