MRI Artifact Reduction via Iterative Coil Correction
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Solution Overview
Problem
Magnetic resonance imaging (MRI) methods using multi-channel parallel imaging technology still suffer from significant artifacts in images due to uneven received signals, despite improvements in image quality through composition processing.
Innovation Solution
A novel MRI method and system that performs image composition processing on raw images from a predetermined artifact coil and a non-artifact coil, and then corrects the artifact coil images by multiplying the composite image with the space sensitivity of the artifact coil, iteratively refining the composite image to reduce artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-channel parallel imaging technology is used to improve signal-to-noise ratio and imaging speed, then image quality is improved, but artifacts become more obvious due to uneven received signals
Solution Approach 1:
The patent extracts and identifies the artifact coil from the multi-channel coil array by comparing signal characteristics. Once identified, the artifact coil's contribution is separated and corrected through iterative processing, removing the harmful artifacts while preserving the useful signal information from other coils
Solution Approach 2:
The patent implements iterative feedback processing where the composite image is repeatedly refined by identifying artifact coils, correcting their contributions, and re-composing the image. Each iteration uses the previous result as feedback to further reduce artifacts, progressively improving image quality
2Reliability
If image composition processing is applied to combine signals from multiple coils, then signal-to-noise ratio is improved, but artifacts persist due to uneven signal reception
Solution Approach 1:
The patent implements iterative feedback processing where the composite image is repeatedly refined by identifying artifact coils, correcting their contributions, and re-composing the image. Each iteration uses the previous result as feedback to further reduce artifacts, progressively improving image quality
Solution Approach 2:
The patent changes the processing parameters by applying different weighting factors to different coils based on their artifact characteristics. Artifact coils are assigned reduced weights that are iteratively adjusted, while non-artifact coils maintain higher weights, optimizing the composite image quality
Data Source
AI summary
The present invention provides a magnetic resonance imaging method and system, the method comprising performing the following steps at least once: a composition step: performing image composition processing on raw images received by a receiving coil that is pre-determined as an artifact coil and a receiving coil that is pre-determined as a non-artifact coil to obtain a composite image; and a correction step: obtaining a product of the above composite image and space sensitivity of the above artifact coil to replace the raw image received by the above artifact coil, and performing the above composition step again.