MRI Motion Correction via Blade Pair Correlation
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Solution Overview
Problem
The PROPELLER method for motion correction in MRI is not error-free, as it relies on choosing an appropriate reference blade and does not adequately address system noise, leading to potential inaccuracies in motion estimation and correction.
Innovation Solution
A method for motion correction in MRI that does not require a reference blade, by calculating relative shift values between pairs of blades to maximize correlation and using a system of linear equations to solve for the entire set of shifts simultaneously, thereby improving accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a reference blade is used for motion correction in the PROPELLER method, then the motion correction process is simplified, but the accuracy and reliability of motion estimation deteriorates due to potential poor reference blade selection and system noise
Solution Approach 1:
The patent removes the reference blade concept from the motion correction process. Instead of relying on a single reference blade that may introduce errors, the method extracts motion information from all blade pairs simultaneously through a system of linear equations, eliminating the source of reference-related inaccuracies while maintaining operational feasibility
Solution Approach 2:
The patent combines motion estimation from multiple blade pairs into a unified system of linear equations. Rather than processing blades individually against a reference, the method merges all pairwise correlation measurements to solve for a consistent set of motion parameters across the entire dataset, improving accuracy through collective information integration
2Productivity
If a reference blade is used for motion correction, then the computational process is reduced, but the precision of motion estimation deteriorates due to inadequate addressing of system noise
Solution Approach 1:
The patent merges multiple pairwise correlation measurements into a single system of linear equations that is solved simultaneously. This approach uses all available blade pair information to determine motion parameters, maximizing the use of data to improve precision while the systematic solution method maintains computational efficiency
Solution Approach 2:
The method incorporates correlation measurements from all blade pairs as feedback into the system of linear equations. Each pairwise correlation provides feedback information about relative motion, and the system iteratively solves for motion parameters that satisfy all feedback constraints simultaneously, improving precision through comprehensive feedback integration
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 enhances the accuracy and reliability of motion correction in MRI by eliminating the need for a reference blade and addressing precision issues related to system noise, resulting in improved image quality by effectively reducing motion artifacts.
Implementation Method 1
magnetic resonance imaging (MRI)
Implementation Method 2
A relative shift value that maximizes a correlation value between the first blade and the second blade is then calculated
Data Source
AI summary
Described here are systems and methods for estimating bulk rotation and translation of an imaged subject between different blades in a PROPELLER MRI or similar sequence. Correlations between unique pairs of blades are calculated and the relative shift values that maximize the correlation between each pair of blades are identified as relative shift values to be applied for motion correction. Using this method, no reference blade is required, nor does a computationally expensive iterative process need to be performed.