MRI Local Field Calculation via Multi-Echo Weighted Averaging
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Solution Overview
Problem
Conventional methods for calculating local magnetic field distributions from MRI data face challenges such as increased computation time and reduced signal-to-noise ratio (SNR) due to noise impact and inaccurate phase aliasing removal, especially in regions with large magnetic susceptibility differences.
Innovation Solution
The method involves converting multi-echo complex images into low-resolution images, separating global frequency and offset phase distributions, enhancing their resolution, and applying weighted averaging to calculate a final local frequency distribution, thereby reducing computation time and improving SNR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional phase aliasing removal processes are applied to multi-echo MRI data, then local magnetic field distribution can be calculated, but computation time increases and signal-to-noise ratio deteriorates due to noise impact
Solution Approach 1:
The patent segments the calculation process by first computing local magnetic field distributions for each individual echo time separately, then combining these segmented results through weighted averaging. This segmentation allows each sub-calculation to be optimized independently, reducing overall computation time while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary phase aliasing removal and background field estimation for each echo time before the final combination step. By preparing these components in advance, the main calculation process is streamlined, significantly reducing the computation time required for the final local magnetic field distribution calculation.
2Measurement precision
If conventional phase aliasing removal processes are applied to multi-echo MRI data, then local magnetic field distribution can be calculated, but signal-to-noise ratio decreases due to noise impact
Solution Approach 1:
The patent merges the local magnetic field distribution results from multiple echo times through weighted averaging. This combination merges the signal information while averaging out random noise components, thereby improving the overall signal-to-noise ratio compared to using a single echo time.
Solution Approach 2:
The patent skips the problematic step of performing phase aliasing removal on the combined multi-echo data by instead processing each echo separately and then combining results. This avoids the noise amplification that occurs when applying phase unwrapping algorithms to multi-echo combined data, preserving signal-to-noise ratio.
3Reliability
If phase distribution measurement is performed at longer echo times to maximize SNR, then signal-to-noise ratio improves, but phase aliasing removal becomes inaccurate in regions with large magnetic susceptibility differences
Solution Approach 1:
The patent segments the analysis into multiple echo time points, allowing each to be processed with optimized parameters. By using multiple TEs including longer ones for high SNR while processing them separately, the method captures both high-signal regions and accurately resolves phase aliasing in high-susceptibility regions through the combination process.
Solution Approach 2:
The patent changes the echo time parameter across multiple measurements, acquiring data at different TEs. This parameter variation allows the system to capture different signal characteristics - longer TEs provide higher SNR while shorter TEs provide better phase unwrapping accuracy, and the weighted combination optimizes both aspects.
4Measurement precision
If multiple echo times are used to acquire images for optimal SNR and phase aliasing removal, then local magnetic field distribution accuracy improves, but computation time increases
Solution Approach 1:
The patent segments the multi-echo data processing into independent per-echo calculations followed by a final combination step. This segmentation enables parallel processing of individual echoes and optimizes each sub-calculation, improving overall calculation efficiency while utilizing the full information from multiple echo times.
Solution Approach 2:
The patent performs preliminary processing of each echo including phase aliasing removal and background field estimation before the final combination. This preliminary action organizes the data structure in advance, making the final combination step computationally efficient and enabling the use of multiple echoes without excessive computation time.
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 allows for the efficient calculation of local magnetic field distributions with high SNR and reduced computation time, enhancing the accuracy and precision of magnetic susceptibility mapping in MRI imaging.
Implementation Method 1
An MRI apparatus is a medical-use diagnostic noninvasive imaging apparatus, utilizing nuclear magnetic resonance phenomenon. The nuclear magnetic resonance phenomenon indicates that hydrogen nucleus (protons) placed in a static magnetic field, are resonant with an RF magnetic field at a specific frequency.
Implementation Method 2
The magnetic susceptibility is a physical property that represents a degree of magnetic polarization (magnetization) of materials in the static magnetic field. In a living body, there are contained paramagnetic substances such as deoxyhemoglobin and iron protein in venous blood, and diamagnetic substances such as water constituting a large part of the living tissue and calcium serving as a basis of calcification.
Data Source
AI summary
In calculating a local magnetic field distribution caused by a magnetic susceptibility difference between living tissues, using MRI, a local frequency distribution with a high SNR is calculated in a short computation time. Multi-echo complex images obtained by measurement of at least two different echo times using the MRI are converted into low-resolution images. A global frequency distribution caused by global magnetic field changes and an offset phase distribution including a reception phase and a transmission phase are separated from a phase distribution of the low-resolution multi-echo complex images. Thus calculated global frequency distribution and the offset phase distribution are enhanced in resolution. A local frequency distribution of each echo is calculated from the measured multi-echo complex images, the high-resolution global frequency distribution, and the high-resolution offset phase distribution. The local frequency distributions of respective echoes are subjected to weighted averaging, whereby a final local frequency distribution is calculated.