CT Scan Positioning Optimization for Regional Image Quality
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Solution Overview
Problem
Current CT scan methods often result in suboptimal image quality due to varying object positions, leading to artifacts like beam hardening, especially when scanning metallic or large components, as the positioning typically optimizes for either specific or average image quality across the volume, failing to achieve high quality in all regions.
Innovation Solution
A method that iteratively assesses and optimizes the positioning of objects during CT scans by evaluating local image quality across different positions, allowing for the selection of the best positioning for individual regional areas and merging scans based on quality values to create an optimized CT reconstruction with reduced artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single positioning is used for CT scanning, then the scanning process is simple and fast, but the image quality cannot be optimized for all regional areas simultaneously
Solution Approach 1:
The patent divides the object into multiple regional areas and performs separate positioning optimization for each region. Instead of treating the entire object as a single unit, the method segments the volume into zones with different quality requirements and optimizes trajectories independently for each segment, allowing regional image quality optimization without requiring a complete redesign of the scanning process.
Solution Approach 2:
The patent implements local quality optimization by determining different optimal positioning parameters for different regional areas of the object. Each region receives a customized trajectory and positioning configuration tailored to its specific imaging requirements, particularly optimizing for high-density components in metal parts while maintaining acceptable quality in other areas.
2Manufacturing precision
If multiple positionings are used to optimize image quality for different regions, then image quality improves, but the scanning time and process complexity increase
Solution Approach 1:
The patent merges multiple region-specific trajectories into a single integrated scanning process. By combining the optimized trajectories for different regional areas into one continuous motion path, the system achieves regional optimization benefits while avoiding the time penalty of executing separate scans for each region. The merged trajectory ensures the radiation source visits each region at its optimal positioning angle.
Solution Approach 2:
The patent employs dynamic trajectory adjustment where the scanning path is continuously optimized based on real-time positioning data and regional quality requirements. The system dynamically modifies the trajectory to pass through different regions at optimally calculated angles, rather than using static pre-defined paths, thereby reducing total scanning time while maintaining regional quality optimization.
3Manufacturing precision
If expert positioning is used to optimize for specific measures, then that specific area achieves good quality, but other areas suffer from suboptimal image quality and artifacts
Solution Approach 1:
The patent systematically varies key positioning parameters including rotation angles, tilt angles, and radial positions to determine optimal configurations for each regional area. By changing these parameters according to specific regional requirements—particularly adjusting angles to minimize beam hardening effects in metal regions—the method reduces artifacts in previously problematic areas while maintaining or improving quality in optimized regions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly improves image quality by identifying and optimizing positions for each regional area, reducing artifacts and enhancing the overall quality of CT reconstructions, particularly for high-density components like metal, thereby expanding the applications of CT scans.
Implementation Method 1
In a CT scan, several radiographs (so-called projections) are usually taken from different positions along a so-called CT trajectory
Data Source
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AI summary
Method for finding at least one second positioning of an object with respect to a CT scan of the object or for data fusion of CT reconstructions for at least one first and second positioning.