CT Image Generation With Region-Specific Weighting
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Solution Overview
Problem
Existing CT imaging systems suffer from artifacts and uneven CT number uniformity, which degrade image quality.
Innovation Solution
A system utilizing a parallel hardware architecture with multiple processing threads generates multiple images from projection data using different weighting functions, combining them to reduce artifacts and improve CT number uniformity through back-projection and masking operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single weighting function is used for back-projection, then the processing is simple and fast, but the CT image has artifacts and poor CT number uniformity
Solution Approach 1:
The patent divides the weighting function into multiple segments (first weighting function and second weighting function) that operate on different regions of the image. The first weighting function processes a first region while the second weighting function processes a second region, allowing each segment to be optimized for its specific region's characteristics. This segmentation enables improved CT number uniformity in different regions without requiring a completely complex unified processing system.
Solution Approach 2:
The patent applies different weighting functions to different regions of the CT image based on their specific characteristics. The first weighting function is designed for the first region while the second weighting function is designed for the second region, ensuring that each region receives processing tailored to its local quality requirements. This local quality approach improves overall CT number uniformity without uniformly increasing complexity across the entire system.
2Manufacturing precision
If multiple weighting functions are used for back-projection, then CT number uniformity improves, but processing time and computational load increase
Solution Approach 1:
By segmenting the image into distinct regions and applying appropriate weighting functions to each, the patent avoids the need for complex global processing. Each segmented region can be processed independently and efficiently, reducing overall processing time while maintaining improved CT number uniformity through region-specific optimization.
Solution Approach 2:
The patent applies weighting functions selectively to specific regions rather than uniformly to the entire image. This partial action approach focuses computational resources only where needed to improve CT number uniformity, avoiding unnecessary processing in regions that already have acceptable quality, thereby reducing overall processing time.
3Productivity
If parallel processing is used, then processing speed increases, but system complexity increases
Solution Approach 1:
The patent segments the back-projection process into multiple parallel processing streams, each handling different regions with different weighting functions. This segmentation enables independent parallel execution of processing tasks, increasing overall processing speed while keeping each individual processing thread relatively simple and manageable.
Data Source
AI summary
The present disclosure relates to systems and methods for image generation. The methods may include obtaining projection data generated by a scanner; generating, based on a first weighting function, a first image by back-projecting the projection data, the first image having a first region corresponding to a first part of the object; generating, based on a second weighting function, a second image by back-projecting the projection data, the second image having a second region corresponding to the first part of the object, the second region of the second image presenting a better CT number uniformity than the first region of the first image; and generating a third image based on the first image and the second image.