Image Segmentation Using Line-Based Seed Regions
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Solution Overview
Problem
Existing image segmentation methods for anatomical structures are inefficient and error-prone due to the need for accurate placement of seed points, which can be unintuitive and cumbersome, leading to suboptimal results.
Innovation Solution
A system and method that allow users to indicate a line in the image close to where segments are to be cut, defining regions on either side of the line, enabling more accurate and intuitive seed point placement, similar to an actual cutting operation, using processor-driven algorithms for segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users mark areas on each separate structure with a brush-like tool to define seed points, then segmentation can be performed, but the process becomes inefficient and error-prone
Solution Approach 1:
The patent replaces the manual brush-like tool operation with an automated line-based segmentation approach. Instead of requiring users to manually paint or mark areas, the system uses graph cut algorithms that automatically determine segmentation based on drawn lines, substituting mechanical interaction with computational processing.
Solution Approach 2:
The system enables self-service segmentation by automatically generating seed points and performing graph cut operations based on user-drawn lines. The algorithm autonomously identifies anatomical structures and performs segmentation without requiring manual seed point placement, allowing the system to serve itself in the segmentation process.
2Measurement precision
If users manually place seed points using brush-like tools, then segmentation can be achieved, but accuracy depends on user skill and intuition
Solution Approach 1:
The patent replaces manual seed point placement with automated graph cut algorithms that compute optimal segmentation boundaries. The system substitutes human intuition and skill with computational algorithms that automatically determine accurate segmentation based on image data and user-drawn guide lines.
3Productivity
If traditional brush-like tool methods are used for seed point definition, then segmentation is possible, but the process is cumbersome and time-consuming
Solution Approach 1:
The patent replaces time-consuming manual brush operations with automated graph cut algorithms. The system performs segmentation computations automatically based on simple line inputs, dramatically reducing the time required compared to manual seed point placement methods.
Solution Approach 2:
The system performs self-service by automatically executing graph cut algorithms and generating segmentation results without requiring manual intervention for seed point placement. This automation eliminates the time-consuming manual processes while maintaining user control through line-based input.
Data Source
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AI summary
There are provided systems and methods for segmenting an image comprising one or more anatomical structures into segments. A system (100) comprises a memory (106) comprising instruction data representing a set of instructions and a processor (102) configured to communicate with the memory (106) and to execute the set of instructions. The set of instructions, when executed by the processor (102), cause the processor (102) to receive a first user input indicating a line in the image, define two regions in the image, one on either side of the indicated line, each region abutting the indicated line on its respective side and, for each of the two regions, determine a segment corresponding to an anatomical structure comprised in the region, using the region as a seed for determining the segment.