Readout-Segmented EPI Navigator Correction and K-Space Averaging
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Solution Overview
Problem
Magnetic resonance imaging (MRI) is adversely affected by patient motion, leading to motion artifacts such as blurring and ghosting due to the prolonged data acquisition time, which is exacerbated by the limitations of existing echo-planar imaging (EPI) techniques like readout-segmented EPI (RSEPI) that introduce inconsistencies between segments, necessitating improved methods for joint navigator correction and k-space domain averaging.
Innovation Solution
The implementation of readout-segmented echo planar imaging (RSEPI) with joint navigator correction and non-uniform k-space averaging, where navigator segments are used to correct phase differences between imaging segments across multiple acquisition sets, allowing for averaging in the k-space domain to enhance image quality while minimizing scan time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If readout-segmented EPI (RSEPI) is used to improve image quality, then image quality is improved, but motion artifacts are introduced due to inconsistencies between readout segments
Solution Approach 1:
Navigator echoes are acquired during the imaging process to provide feedback information about patient motion. This navigator data is used to correct phase errors in the imaging segments, creating a feedback loop that compensates for motion artifacts and maintains image quality despite the segmented readout approach
Solution Approach 2:
The patent changes the parameter of k-space sampling by concentrating more samples in low-frequency regions and fewer in high-frequency regions. This non-uniform sampling strategy, combined with navigator correction, allows the system to maintain image quality while reducing the负面影响 of motion artifacts in the segmented readout
2Loss of time
If single-shot EPI (SSEPI) is used to minimize patient motion effects, then scan time is reduced, but susceptibility artifacts and spatial blurring occur
Solution Approach 1:
The k-space acquisition is divided into multiple readout segments rather than acquiring all data in a single shot. This segmentation allows for navigator echo insertion and correction between segments, reducing susceptibility artifacts and blurring while maintaining relatively fast scan times compared to conventional sequential methods
Solution Approach 2:
Navigator echoes are acquired preliminarily during the imaging sequence to detect and correct motion and susceptibility effects before they degrade the final image quality, allowing the segmented EPI to achieve both speed and image quality
3Object-affected harmful factors
If navigator data is acquired during second and subsequent echoes to correct motion, then motion artifacts are reduced, but data across acquisition sets become disparate and cannot be averaged
Solution Approach 1:
The patent applies a consistent rephasing gradient strategy across all acquisition sets and segments, changing the parameter of gradient application to ensure that navigator data from different acquisition sets becomes comparable and can be jointly corrected. This standardization allows data averaging across all segments while maintaining motion correction
Data Source
AI summary
An apparatus and method are provided to correct motion artifacts in magnetic resonance imaging (MRI) data by obtaining magnetic resonance imaging (MRI) data, the MRI data including imaging segments and corresponding navigator segments, each imaging segment sampled over a respective regions of two or more regions of a k-space grid, one of the navigator segments being selected as a reference navigator segment; generating, for each imaging segment of the imaging segments, a respective phase map based on the reference navigator segment and a corresponding navigator segment of the each imaging segment; applying the respective phase maps to the corresponding imaging segments to generate corrected imaging segments; averaging the corrected imaging segments in k-space to generate averaged imaging segments; and reconstructing an MRI image based on the averaged imaging segments.