Metal Artifact Reduction in CT Image Reconstruction
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Solution Overview
Problem
Metal implants in CT scans cause streak-like artifacts in reconstructed images, degrading image quality, and existing metal artifact reduction methods fail to fully eliminate these artifacts, leading to issues like black halos, blurring, and residual streaks.
Innovation Solution
A medical image processing method involving multivalued processing of raw images to determine a predicted projection value based on the contribution of each tissue along a ray path, using a correspondence between ray absorption amounts to minimize metal artifacts and improve image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If metal implants are present in the body during CT scanning, then the CT scan can be performed, but metal artifacts (streak-like or shadow artifacts) appear in the reconstructed image, degrading image quality
Solution Approach 1:
The patent segments the projection data into two categories: complete projection data (rays not passing through metal implants) and incomplete projection data (rays passing through metal implants). By separating and differently processing these data types, the method eliminates metal artifacts while preserving valid anatomical information.
Solution Approach 2:
The patent extracts and identifies incomplete projection data that corresponds to rays passing through metal implants using a metal detection algorithm. These problematic data points are then removed or replaced through interpolation, effectively taking out the harmful metal artifact sources from the reconstruction process.
2Reliability
If existing metal artifact reduction methods are used, then some artifact reduction is achieved, but residual artifacts (black halos, blurring, residual streaks) remain, failing to fully eliminate the problem
Solution Approach 1:
The patent employs an iterative reconstruction process where the reconstructed image is continuously refined. In each iteration, the algorithm compares the current reconstruction with the measured projection data, identifies remaining artifacts, and adjusts the projection data accordingly. This feedback loop continues until artifacts are minimized, ensuring thorough artifact removal without leaving residual streaks or blurring.
Solution Approach 2:
The patent replaces traditional mechanical artifact reduction methods with an advanced computational approach using machine learning algorithms and iterative optimization. This substitution enables more precise identification and correction of metal artifacts, achieving superior artifact reduction compared to conventional methods while preserving image details.
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
The method effectively removes metal artifacts, resulting in significantly improved image quality by minimizing the impact of metal implants in reconstructed CT images.
Implementation Method 1
In the process of computed tomography (CT), a detector is used to acquire data of X-rays passing through a subject to be examined
Implementation Method 2
according to a correspondence between a degree of contribution, relating to a ray absorption amount, of each tissue on a ray path
Data Source
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AI summary
Provided in embodiments of the present application are a medical image processing method and apparatus and a medical device. The medical image processing method includes: acquiring raw projection data obtained after a subject to be examined is scanned, and performing reconstruction to obtain a raw medical image; performing multivalued processing on the raw medical image to obtain a multivalued image; according to a correspondence between a degree of contribution, relating to a ray absorption amount, of each tissue on a ray path that does not pass through a specific material site in the multivalued image and a raw projection value corresponding to the ray path in the raw projection data, determining a predicted projection value of a path corresponding to the specific material site in the raw projection data; and obtaining a first medical image according to the predicted projection value and the raw projection data.