3D Image Segmentation Using Level Set Functions and Curvature Analysis
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Solution Overview
Problem
Current methods for evaluating the volume and geometry of irregularly shaped objects in 3D images are labor-intensive and time-consuming, failing to provide accurate results for medical and other applications that require quick and precise geometrical information.
Innovation Solution
A system and method using level set functions and a modified illusory surface algorithm that allows for minimal human interaction to segment and calculate the volume and geometry of irregular 3D objects from medical images, employing an amplification factor to distinguish between target and surrounding structures based on Gaussian curvature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual segmentation methods are used to evaluate volume and geometry of irregular 3D objects, then measurement precision can be achieved, but productivity is severely reduced due to labor-intensive processes
Solution Approach 1:
The system performs automatic segmentation and geometrical calculation without requiring manual intervention. The algorithm independently identifies target objects, segments them from surrounding structures, and computes volumetric and geometric parameters automatically, eliminating the need for human operators to perform these tasks manually.
Solution Approach 2:
The patent replaces manual mechanical segmentation operations with an automated computational algorithm. The system uses image processing and mathematical models to perform segmentation and geometric analysis that would otherwise require manual measurement and calculation, significantly improving processing speed while maintaining accuracy.
2Productivity
If automated methods are used to quickly evaluate 3D volume, then productivity is improved, but measurement precision deteriorates due to inability to handle irregular shapes accurately
Solution Approach 1:
The system transforms the segmentation problem into a level set evolution process, changing the mathematical parameters and representation method. By using level set functions and evolving surfaces based on curvature properties, the algorithm can accurately represent and measure irregular shapes that traditional automated methods cannot handle, thereby maintaining measurement precision while achieving automation.
Solution Approach 2:
The patent introduces level set functions as an intermediary mathematical tool between the raw image data and the final geometric measurements. This intermediary representation allows the system to handle complex irregular boundaries accurately during the automated segmentation process, bridging the gap between speed and precision.
3Measurement precision
If complex automated algorithms are implemented to handle irregular shapes, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex problem into distinct computational stages: image preprocessing, level set initialization, surface evolution based on curvature, and final geometric parameter extraction. By dividing the overall task into manageable segments, the system achieves high measurement precision for irregular shapes while keeping each individual computational step relatively simple and well-defined.
Data Source
AI summary
A method and apparatus for volumetric image analysis and processing is described. Using the method and apparatus, it is possible to obtain geometrical information from multi-dimensional (3D or more) images. As long as an object can be reconstructed as a 3D object, regardless of the source of the images, the method and apparatus can be used to segment the target (in 3D) from the rest of the structure and to obtain the target's geometric information, such as volume and curvature.