MRI Image Motion Correction for Region-Specific Artifacts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing motion correction techniques in medical imaging, such as MRI, fail to account for varying motion patterns across different body regions, leading to sub-optimal corrections and residual artifacts.
Innovation Solution
The method involves dividing imaging data into regions with distinct motion patterns and applying customized correction processes tailored to each region, using techniques like COCOA and self-navigation, and optionally incorporating data rejection and convolution kernels to synthesize motion-corrected images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a uniform motion correction process is applied to all regions of the body, then the correction process is simple and consistent, but the correction is sub-optimal and contains residual artifacts due to ignoring regional motion variations
Solution Approach 1:
The patent divides the imaging data into multiple sets, where each set corresponds to a specific region of the body with distinct motion characteristics. This segmentation allows different motion correction processes to be applied to different regions, improving overall correction accuracy while managing complexity through modular processing
Solution Approach 2:
The patent applies different motion correction processes tailored to the specific motion patterns of each body region. For example, cardiac motion correction is applied to heart regions while respiratory motion correction is applied to lung regions, ensuring that each region receives the most appropriate correction method for its unique motion characteristics
2Manufacturing precision
If different correction processes are applied to different regions with distinct motion patterns, then motion correction accuracy is improved, but the complexity of the correction process increases
Solution Approach 1:
The patent segments the imaging data into multiple sets corresponding to different body regions, enabling region-specific motion correction. This segmentation strategy improves correction accuracy by addressing unique motion patterns in each region while organizing the complex correction process into manageable modular components
Solution Approach 2:
The patent changes the correction parameters and methods based on the specific motion patterns detected in each region. By adapting correction parameters to match regional motion characteristics (e.g., periodic cardiac motion vs. aperiodic swallowing motion), the system achieves higher accuracy without requiring a completely different correction framework for each region
Data Source
AI summary
The present disclosure relates to dividing image data obtained from a scan (e.g. MRI) of an object into two or more sets of data corresponding do unique motion patterns and/or motion sources. Each of the two or more sets of data can be corrected using an appropriate correction technique. One appropriate correction techniques includes generating kernels for each divided imaging dataset using center and adjacent slice information to correct for through-plane and in-plane artifacts.