MRI Phase Shift Correction Using Complex Linear Models
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Solution Overview
Problem
Magnetic resonance imaging (MRI) systems face challenges in correcting phase shifts in echo images due to noise introduced by eddy currents, which affect the accuracy of pixel homogeneity and image quality.
Innovation Solution
A system and method that identify homogeneous pixels in echo images by determining image gradients and using a complex linear model to correct phase shifts, incorporating phase and amplitude information to improve accuracy and reduce errors from phase wrapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If phase shift correction is performed using traditional methods, then image quality may be improved, but noise from eddy currents introduces errors in pixel homogeneity detection
Solution Approach 1:
The patent introduces an intermediary approach by using a complex linear model that separately processes phase and amplitude components. The model acts as a mediator between the noisy echo images and the corrected output, allowing phase shift correction while filtering out eddy current noise through the structured mathematical framework.
Solution Approach 2:
The patent transforms the phase shift correction problem by changing parameters from traditional real-valued processing to complex-valued processing. By representing pixel values as complex numbers with phase and amplitude components, the method can independently correct phase shifts while preserving amplitude information, thereby improving accuracy despite noise.
2Measurement precision
If homogeneous pixels are identified using image gradient methods, then phase shift correction can be applied, but phase wrapping errors reduce measurement precision
Solution Approach 1:
The patent moves the problem from a one-dimensional real-valued domain to a two-dimensional complex domain. By representing pixel values as complex numbers with both magnitude and phase components, the method can detect phase wrapping errors and correct them by analyzing the complex structure, thereby recovering lost phase information.
Solution Approach 2:
The patent implements a feedback mechanism where the complex linear model continuously refines phase shift estimates by comparing predicted and actual complex pixel values. This iterative feedback process allows the system to detect and correct phase wrapping errors by adjusting phase estimates until consistency is achieved across the complex domain.
Data Source
AI summary
A system and method for correcting phase shift in echo images are provided. The method may include one or more of the following operations. A plurality of echo images may be obtained. Homogeneous pixels in the plurality of echo images may be identified. A vector corresponding to each of at least some of the identified homogeneous pixels may be determined. A vector of a homogenous pixel includes a phase element and an amplitude element. A first complex linear model of phase shift may be determined based at least in part on the determined vectors. Phase shift of at least one of the plurality of echo images may be corrected based on the first complex linear model.