MRI Phase Correction Using Main Virtual Channel Selection
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Solution Overview
Problem
Current phase correction methods for multi-segment MR imaging suffer from phase errors and artifacts due to low-quality phase correction data, especially in parallel imaging, leading to degraded image quality.
Innovation Solution
A phase correction method using a channel compression algorithm to determine a main virtual channel from each slice, applying phase correction data from this channel to reduce phase errors and artifacts by avoiding additional phase differences between channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phase correction data from each coil channel is used to correct corresponding image data, then phase correction is performed for all channels, but low-quality phase correction data introduces additional phase differences between channels resulting in artifacts
Solution Approach 1:
The patent extracts only the most reliable phase correction data (from the channel with maximum signal strength) and uses it to correct all channels, rather than using all channel data. This extraction approach eliminates the harmful effect of low-quality phase correction data while maintaining the benefit of comprehensive phase correction.
Solution Approach 2:
The patent applies different quality criteria to different channels and selects phase correction data based on local signal strength characteristics. By evaluating each channel's signal quality individually and selecting the optimal channel, the method ensures high-quality phase correction without introducing artifacts from poor-quality data.
2Productivity
If segmented acquisition with multiple excitations is used, then complete k-space data is obtained, but phase errors accumulate between segments causing artifacts
Solution Approach 1:
The patent performs preliminary phase correction using the most reliable channel data before combining segmented k-space data. This preliminary action corrects phase errors in advance, allowing the segmented acquisition to maintain high productivity while achieving accurate phase information in the final image.
Data Source
AI summary
Techniques are described for performing a phase correction for magnetic resonance imaging. The techniques include: for each slice of a target site: using a channel compression algorithm to determine each virtual channel of the slice using a channel compression matrix; determining a main virtual channel of the slice from each virtual channel; using phase correction data of the main virtual channel of the slice of the target site to perform phase correction on multi-segment image data of each virtual channel of the slice of the target site. This results in a reduction in phase errors in multi-segment MR image data.