MRI Signal Processing for Accurate Water-Fat Tissue Separation
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Solution Overview
Problem
Existing MRI image processing methods fail to accurately separate water and fat tissues due to low Signal Noise Ratio (SNR), leading to reduced image accuracy and principal value rotation issues.
Innovation Solution
A magnetic resonance imaging apparatus that prioritizes processing pixels with high signal strength and small phase differences, using a phase unwrapping process to avoid low SNR regions and reduce principal value rotation, thereby improving image accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phase unwrapping is performed using regional expansion method, then processing can be completed, but principal value rotation occurs due to large phase differences between adjacent pixels
Solution Approach 1:
The patent changes the processing parameter from phase difference magnitude to signal strength (SNR) as the criterion for determining processing order. By prioritizing pixels with high signal strength, the method ensures reliable phase measurements before propagating to adjacent pixels, thereby preventing principal value rotation while maintaining processing completion.
2Productivity
If phase unwrapping is performed without considering SNR, then processing speed is maintained, but accuracy of tissue image is lowered due to principal value rotation from low SNR
Solution Approach 1:
The patent performs preliminary sorting of pixels based on signal strength before executing the phase unwrapping process. This preliminary action ensures that pixels with high SNR are processed first, establishing a reliable foundation for subsequent processing and preventing accuracy degradation without sacrificing processing efficiency.
3Ease of operation
If pixels are processed in arbitrary order, then processing is simple, but principal value rotation occurs due to large phase differences in adjacent pixels
Solution Approach 1:
The patent changes the sorting parameter from arbitrary or phase-difference-based ordering to signal strength-based ordering. This parameter change maintains processing simplicity through automated sorting while ensuring phase continuity by prioritizing high-SNR pixels that provide reliable reference values for adjacent pixel processing.
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 approach results in more accurate tissue state imaging by effectively avoiding principal value rotation and reducing noise influence, leading to improved separation of water and fat images.
Implementation Method 1
A Magnetic Resonance Imaging (hereinafter, MRI) apparatus measures a Nuclear Magnetic Resonance (hereinafter, NMR) signal generated by atomic nuclear spin comprising an object
Data Source
AI summary
A magnetic resonance imaging apparatus that can display an image showing conditions of tissues such as water and fat more accurately is provided. For this purpose, the signal processing unit 110 processes signals of each pixel of the first image 506 generated based on an NMR signal for each pixel of the first image 506 in order to generate the second image 509 and determines an order of processing unprocessed pixels of the first image 506 by preferentially selecting the unprocessed pixels with a high signal strength from among a plurality of unprocessed pixels for which no process has not been performed yet that are adjacent to the already-processed pixels of the first image 506.