Graph-Cut Optimization for MRE Harmonic Signal Estimation
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Solution Overview
Problem
Magnetic resonance elastography (MRE) data sets often suffer from low signal-to-noise ratio (SNR) and phase wrapping, leading to inaccurate estimates of temporal harmonic signals and tissue stiffness maps.
Innovation Solution
A method using graph-cut based optimization to estimate harmonic signals, which allows for the generation of spatial maps of mechanical parameters with increased accuracy, even in the presence of low SNR or phase wrapping, by employing complex-valued signals and a mathematical inversion technique.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional gradient-based optimization strategies are used to estimate temporal harmonic signals, then the computation is simpler, but the accuracy of the estimates deteriorates when SNR is low or phase wrapping is present
Solution Approach 1:
The patent transforms the optimization problem by changing parameters from direct harmonic signal estimation to phase unwrapping estimation. By estimating phase unwrapping fields and transforming to the harmonic domain, the method handles low SNR and phase wrapping issues more effectively, improving measurement precision while managing computational complexity through parameter transformation rather than direct complex optimization
Solution Approach 2:
The patent introduces an intermediary approach by using phase unwrapping fields as intermediate variables. Instead of directly optimizing for harmonic signals (which is difficult under low SNR and phase wrapping), the method optimizes for phase unwrapping fields first, then transforms to obtain harmonic signals. This intermediary step simplifies the optimization landscape and improves estimation accuracy
2Measurement precision
If phase-contrast images with low SNR or phase wrapping are used, then the data acquisition is simpler and faster, but the accuracy of spatial maps deteriorates
Solution Approach 1:
The patent converts the harmful effects of phase wrapping and low SNR into beneficial information by using graph-cut based optimization to estimate phase unwrapping fields. The method leverages the structural information in the phase-contrast images, even when corrupted by wrapping and noise, to recover accurate harmonic signals and generate precise spatial maps of tissue stiffness
Solution Approach 2:
The patent replaces direct mechanical signal processing with a computational optimization approach. Instead of relying on straightforward signal processing that fails under low SNR and phase wrapping, the method uses graph-cut optimization to estimate phase unwrapping fields and transform to harmonic signals, achieving robust accuracy improvement
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 robustly estimates harmonic signals and generates accurate spatial maps of tissue stiffness, overcoming the limitations of gradient-based optimization strategies and improving the accuracy of mechanical parameter estimation.
Implementation Method 1
a magnet system configured to generate a polarizing magnetic field about at least a portion of a subject
Implementation Method 2
a magnetic gradient system including a plurality of magnetic gradient coils configured to apply at least one magnetic gradient field to the polarizing magnetic field
Implementation Method 3
a radio frequency (RF) system configured to apply an RF field to the subject and to receive MR signals therefrom
Implementation Method 4
a driver system configured to deliver an oscillatory stress to the subject to, thereby, direct a shear wave through the subject
Data Source
AI summary
A system and method for generating a spatial map of parameters that describe the mechanically-induced harmonic motion information present within a magnetic resonance elastography (MRE) data set is provided. A first temporal harmonic signal is estimated using a graph-cut based optimization strategy, and can subsequently be used to generate a spatial map of mechanical parameters. The MRE data set is used to estimate the harmonic. The spatial map is of a mechanical parameter derived from the estimated harmonic.