MRI Motion Correction via Sub-Region Segmentation
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Solution Overview
Problem
Current prospective motion correction techniques in magnetic resonance imaging (MRI) face limitations in accurately correcting movements that occur over short timescales, leading to motion artifacts and reduced image quality, especially in functional MRI (fMRI) where small head movements can significantly impair statistical results.
Innovation Solution
The method involves subdividing the region of interest into sub-regions for acquiring MR data, allowing for precise determination of motion correction parameters using a combination of first and second MR data sets, with optional reference MR data of lower resolution, enabling robust and efficient motion correction even during short scan times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If navigator scans are slotted in during scan time for prospective motion correction, then motion correction capability is improved, but scan sequence complexity increases
Solution Approach 1:
The patent divides the imaging volume into multiple slabs, each acquired separately with its own motion correction parameters. This segmentation allows motion correction to be applied independently to each slab without requiring complex navigator scans throughout the entire sequence, thereby reducing overall sequence complexity while maintaining motion correction capability.
Solution Approach 2:
The patent performs motion correction parameter determination for each slab before acquiring the remaining k-space data for that slab. This preliminary determination of motion parameters allows the scan sequence to be simplified, as subsequent data acquisition can proceed with pre-determined correction parameters rather than requiring continuous navigator scans.
2Measurement precision
If the region of interest is subdivided into sub-regions for motion correction, then motion correction precision is improved, but data acquisition time increases
Solution Approach 1:
The patent segments the imaging volume into multiple slabs that can be processed independently with dedicated motion correction parameters, improving precision for each sub-region. However, to mitigate time loss, the patent employs parallel acquisition techniques and efficient k-space sampling strategies that reduce the total acquisition time despite the increased number of sub-regions.
Solution Approach 2:
The patent adjusts acquisition parameters such as slab thickness, number of slabs, and k-space sampling density to optimize the balance between motion correction precision and acquisition time. By dynamically changing these parameters based on the specific imaging requirements and motion characteristics, the system achieves high precision without excessive time penalty.
Data Source
AI summary
For prospective motion correction in magnetic resonance imaging, first magnetic resonance data that map a first sub-region of a region of interest are acquired. Motion correction parameters are determined based on a comparison of at least the first magnetic resonance data with reference magnetic resonance data that map the region of interest. Second magnetic resonance data that map a second sub-region of the region of interest are determined using prospective motion correction based on the motion correction parameters. A magnetic resonance image is determined based on the first magnetic resonance data and based on the second magnetic resonance data.