Adaptive Metal Template Expansion for CT Artifact Reduction
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Solution Overview
Problem
Existing CT image reconstruction techniques fail to effectively reduce metal artifacts, particularly in cases where metal implants occupy a large proportion of the image, leading to distorted images and halo effects, which hinder accurate diagnosis.
Innovation Solution
A method and apparatus that determine the proportion of metal pixels in a CT image, generating an expanded metal template for images with high metal content and applying weighting techniques for images with low metal content to produce a metal-free, artifact-reduced image, thereby improving image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If existing MAR techniques are used to reduce metal artifacts, then artifact reduction is achieved, but the algorithm complexity increases and results vary with metal properties
Solution Approach 1:
The patent changes the parameter of metal template expansion level based on the proportion of metal pixels in the image. For images with high metal content (greater than first threshold), a higher expansion level is applied, while for images with low metal content (less than second threshold), a lower expansion level is used. This adaptive parameter adjustment resolves the contradiction by optimizing artifact reduction effectiveness while avoiding unnecessary computational complexity for different metal content scenarios.
2Object-affected harmful factors
If MAR technique is applied to artificial knee joint with large metal volume, then artifact reduction is attempted, but metal artifacts are not significantly reduced and affect diagnosis
Solution Approach 1:
The patent applies local quality by differentiating the metal template expansion treatment based on the local metal content in different regions of the image. By calculating the proportion of metal pixels and applying different expansion levels (2D or 3D expansion) to different regions according to their metal content, the method achieves effective artifact reduction in high-metal regions while preserving diagnostic information, thereby resolving the contradiction between artifact reduction and diagnostic accuracy.
3Object-affected harmful factors
If MAR technique is applied to artificial metal tibia with small metal proportion, then artifact reduction is achieved, but halo effect occurs and metal image is lost
Solution Approach 1:
The patent applies dynamics by making the metal template expansion level adaptive and variable based on the metal pixel proportion in the image. For images with small metal proportion like artificial metal tibia, the system dynamically selects a lower expansion level, preventing over-expansion that causes halo effects and information loss. This dynamic adjustment resolves the contradiction by matching the treatment intensity to the actual metal content, reducing artifacts without creating new problems.
4Ease of operation
If uniform metal template expansion is applied to all images, then processing simplicity is maintained, but image quality varies and diagnostic reliability decreases
Solution Approach 1:
The patent maintains processing simplicity through an automated workflow that calculates metal pixel proportion and automatically selects the appropriate expansion level (2D or 3D) based on predetermined thresholds. This parameter-based automation resolves the contradiction by eliminating the need for manual intervention while ensuring that each image receives the appropriate treatment level, thereby maintaining both ease of operation and diagnostic reliability.
Data Source
AI summary
The present invention provides a method and apparatus for reducing artifacts in CT image reconstruction. The method comprises obtaining an original reconstructed image and an original sinogram and determining a proportion of metal pixels in the original reconstructed image. If the proportion is greater than a first threshold value, then generating an expanded metal template based on the original reconstructed image, generating a metal-free, metal artifact reduced (MAR) image based on the expanded metal template and the original sinogram, and generating a final image based on the expanded metal template and the metal-free, MAR image. However, if the proportion of metal pixels is less than a second threshold value, then generating an expanded metal template based on the original reconstructed image, generating a metal-free, metal artifact reduced image based on a treatment, and generating a final image based on the expanded metal template and the metal-free, MAR image.