MRI Phase-Based Aliasing Elimination
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Solution Overview
Problem
Existing MRI techniques face challenges in reducing measurement time and noise amplification due to the g-factor, particularly in 2D data processing and undersampled acquisitions, which lead to SNR degradation and aliasing issues.
Innovation Solution
The method employs phase differences between low-resolution and main captured images to separate true images, using complex number multiplication to minimize noise amplification, thereby eliminating aliasing without relying on sensitivity distribution of receiving coils.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallel imaging with undersampled k-space data is used to shorten measurement time, then productivity is improved, but noise amplification due to g-factor occurs and SNR degrades
Solution Approach 1:
The patent changes the parameter used for image separation from sensitivity distribution to phase information. By acquiring phase information at multiple time points and utilizing temporal phase variations, the method achieves image separation without the noise amplification associated with g-factor in traditional parallel imaging
Solution Approach 2:
The patent introduces time as an intermediary parameter to separate images. By acquiring phase information at different time points and exploiting temporal phase differences, the method separates superimposed images without requiring complex coil sensitivity modeling, thereby avoiding g-factor noise amplification
2Productivity
If acceleration factor is increased to reduce aliasing, then productivity is improved, but noise amplification increases and SNR degrades
Solution Approach 1:
The patent changes from using spatial sensitivity distribution to using temporal phase information for image separation. This parameter change allows for higher acceleration factors without the noise amplification penalty, because phase information naturally encodes spatial location without requiring high-gain coil configurations
3Reliability
If sensitivity distribution of receiving coils is used for image separation, then aliasing is eliminated, but noise amplification due to g-factor occurs
Solution Approach 1:
The patent introduces time as an intermediary to achieve image separation. By acquiring phase information at multiple time points and using temporal phase variations as the separating mechanism, the method eliminates aliasing without relying on coil sensitivity distribution, thereby avoiding g-factor noise amplification
Solution Approach 2:
The patent replaces the mechanical/physical system of coil sensitivity-based separation with a temporal-phase-based separation system. This substitution uses the natural temporal evolution of phase information rather than the spatial sensitivity profiles of coils, fundamentally changing the separation mechanism to avoid noise amplification
Data Source
AI summary
Provided is a novel aliasing elimination technique capable of suppressing noise amplification in an aliasing elimination calculation in parallel imaging and the like. The technique utilizes the fact that a phase of an image (a true image that is one of a plurality of images) to be separated from a main captured image obtained with the plurality of images superimposed is basically the same as a phase of an image obtained at a low resolution, to obtain a phase difference between a phase of a low-resolution image and a phase of the main captured image, and separates the true image by calculation using the phase difference and a pixel value of the main captured image. At this time, the low-resolution image is obtained by each of a plurality of receiving coils, and the true image is calculated after multiplying a plurality of low-resolution images by a complex number that minimizes the noise amplification.