MRI Phase Distribution Calculation Using Spherical Harmonics
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Solution Overview
Problem
Existing MRI techniques face challenges in accurately calculating local phase distributions, particularly at the brain surface area, due to limitations in background phase elimination and reduced calculation accuracy at tissue interfaces.
Innovation Solution
A magnetic resonance imaging apparatus that includes a computer system for extracting subject tissues, calculating phase distributions, correcting phase wrapping, dividing areas, calculating background phases, and combining these to accurately determine local phase distributions across the entire brain, including the brain surface area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the PDF-method is used for background phase elimination, then the background phase distribution can be estimated and eliminated, but the background phase distribution in portions that cannot be reproduced by the estimated magnetic susceptibility (e.g., paranasal cavity) cannot be eliminated
Solution Approach 1:
The patent introduces a spherical harmonic function as an intermediary model to represent the background phase distribution. This mathematical model serves as a mediator between the measured phase data and the underlying background phase, allowing for more comprehensive background phase elimination including regions that the PDF-method cannot handle, such as the paranasal cavity.
Solution Approach 2:
The patent changes the parameter representation from direct magnetic susceptibility estimation (PDF-method) to spherical harmonic function coefficients. By transforming the problem into the spherical harmonic domain, the method can globally model the background phase distribution and eliminate it more completely across all brain regions, including those with complex susceptibility patterns.
2Reliability
If the SHARP-method is used for background phase elimination, then the background phase distribution can be approximated using spherical harmonic function, but the calculation accuracy is decreased for the local phase distribution in the interface portion between brain inside and brain outside
Solution Approach 1:
The patent applies different processing strategies to different regions: using the spherical harmonic function for global background phase modeling while applying phase wrapping correction and local phase calculation specifically at the brain surface interface. This localized approach preserves the accuracy of local phase distribution at the brain surface while maintaining the completeness of background phase elimination in other regions.
Solution Approach 2:
The patent segments the phase distribution calculation into distinct components: global background phase (modeled by spherical harmonic function) and local phase (calculated after background elimination). By separating these components and processing them differently, the method achieves both complete background elimination and accurate local phase calculation at the brain surface.
3Measurement precision
If phase wrapping correction is applied to calculate total phase distribution, then the phase distribution can be corrected, but the background phase distribution generated due to subject shape cannot be separated from the local phase distribution
Solution Approach 1:
The patent replaces the mechanical/geometric approach of background phase elimination (PDF-method) with a mathematical field theory approach (spherical harmonic function). This substitution transforms the complex problem of separating background and local phase components into a systematic mathematical decomposition, making the separation process more rigorous and complete.
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
This approach enables precise calculation of local phase distributions throughout the brain, including the brain surface area, thereby improving diagnostic accuracy and reliability.
Implementation Method 1
a static magnetic field generation magnet configured to generate a static magnetic field in a space where a subject is arranged
Implementation Method 2
a transmission unit configured to transmit a high frequency magnetic field to the subject
Implementation Method 3
a reception unit configured to receive a nuclear magnetic resonance signal generated in the subject through transmission of the high frequency magnetic field thereto
Implementation Method 4
a gradient magnetic field application unit configured to apply a gradient magnetic field which adds positional information to the nuclear magnetic resonance signal
Data Source
AI summary
A magnetic resonance imaging apparatus includes: a static magnetic field generating magnet configured to generate a static magnetic field in a space where a subject is arranged; a transmission unit configured to transmit a high frequency magnetic field to the subject; a reception unit configured to receive a nuclear magnetic resonance signal generated in the subject due to transmission of the high-frequency magnetic field thereto; a gradient magnetic field application unit configured to apply a gradient magnetic field which adds positional information to the nuclear magnetic resonance signal; a computer configured to control the transmission unit, the reception unit, and the gradient magnetic field application unit, and configured to process the nuclear magnetic resonance signal; and a display unit configured to display an image processed by the computer; and the computer performs a predetermined calculation processing.