Spinal Canal Center Line Extraction With Robust Optimal Path Finding
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Solution Overview
Problem
Existing methods for extracting the spinal canal center line in medical imaging are prone to segmentation errors, leading to unrealistic image distortions and complications in diagnosing spinal fractures.
Innovation Solution
A method and apparatus that utilize three-dimensional voxel-wise spinal canal segmentation, inverse density array generation, and dynamic programming-based optimal path finding to generate a spinal canal center line that is not sensitive to segmentation errors, employing a coarse-to-fine strategy to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional C-arm fluoroscopy systems with fixed geometry are used, then the system structure is simple, but the flexibility and adaptability for different surgical approaches are limited
Solution Approach 1:
The C-arm fluoroscopy system is designed with dynamic, movable components including the C-arm assembly that can rotate around the patient, the image intensifier that can move relative to the x-ray source, and the position indication system that tracks these movements in real-time. This dynamic configuration allows the system to adapt to different surgical approaches and patient anatomies while maintaining a relatively simple overall structure through modular design
2Measurement precision
If complex path finding algorithms are used to extract spinal center lines, then the path finding accuracy is improved, but the computational time and processing complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-defining constraint parameters for the spinal center line path, including anatomical constraints (vertebral body boundaries, intervertebral disc spaces), geometric constraints (curve smoothness, angle limits), and physiological constraints (natural spinal curvature). These pre-established constraints guide the path finding algorithm to converge faster on accurate solutions without requiring exhaustive computational search of all possible paths
3Measurement precision
If real-time position indication is provided during surgery, then the surgical guidance accuracy is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The system introduces a position indication system that acts as an intermediary between the physical C-arm fluoroscopy apparatus and the surgical interpretation system. This intermediary component includes detectors that track the positions of x-ray source and image intensifier, a computer that calculates spatial relationships and generates position indicators, and display mechanisms that present this information to surgeons. This intermediary layer simplifies the overall system by centralizing the complex calculations and providing intuitive visual feedback
Data Source
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AI summary
Method and apparatus for finding an optimal spinal canal path center line are disclosed. Imaging scans such as a Computer Tomography (CT) scan are used to diagnosis rib and spine fractures. The spine image is usually reformatted in a straightened CPR (curved planar reformat). A dynamic programming-based techniques to find an optimal path from a spinal canal segmentation is disclosed. The disclosed method and apparatus overcomes spinal canal segmentation errors resulting in spinal canal gaps and unrealistic image distortions. The disclosed techniques are not sensitive to segmentation errors even is the presence of high segmentation noise. The disclosed techniques generate a binary three-dimensional image corresponding to the scanned spine image, perform density estimation to create a three- dimensional having the same size as the original binary three-dimensional, perform dynamic programming based optimal spinal canal path finding with a coarse to fine optimal path finding strategy to accelerate the optimal spinal canal path finding.