Parallel Imaging Weighting Matrix for MR Artifact Reduction
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Solution Overview
Problem
MR systems with short patient-receiving bores experience reduced homogeneity of the magnetic field and gradient accuracy, leading to artifacts and signal intensity issues at the edges of the field of view, particularly in parallel imaging, where high signal intensity regions cause incorrect spatial encoding and aliasing artifacts.
Innovation Solution
A method to generate a weighting matrix that reduces the influence of reception channels with high signal intensity by assigning lower weights to them during parallel imaging, using a reference dataset to calculate the weighting matrix, which is applied to raw data to minimize artifacts caused by inhomogeneities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallel imaging is used to accelerate scanning, then scanning time is reduced, but artifacts occur at integer multiples of FOVz/R due to incomplete k-space coverage
Solution Approach 1:
The patent performs preliminary actions by acquiring reference data at specific locations (including the center of k-space and additional reference points) before the actual parallel imaging scan. This reference data is used to calculate weighting factors that compensate for the incomplete k-space coverage, allowing accurate reconstruction without requiring full k-space acquisition.
Solution Approach 2:
The patent introduces weighting factors as an intermediary element that mediates between the incomplete parallel imaging data and the desired complete image. These weighting factors, calculated from reference data, act as correction terms that fill in the missing k-space information and eliminate aliasing artifacts.
2Reliability
If multiple reception channels are used to improve signal coverage, then image quality improves, but high signal intensity regions cause incorrect spatial encoding and aliasing artifacts
Solution Approach 1:
The patent applies local quality by calculating different weighting factors for different spatial locations and different reception channels. Instead of using uniform weighting, the system adapts the weighting factors locally based on the specific characteristics of each channel and position, reducing artifacts in regions with high signal intensity while maintaining signal coverage where needed.
Solution Approach 2:
The patent changes the parameter of weighting factors dynamically based on the signal characteristics. By calculating weighting factors that depend on the local signal intensity and spatial position, the system adjusts the contribution of different channels and regions to minimize aliasing artifacts while preserving useful signal information.
3Measurement precision
If reference scans are performed to determine coil sensitivities, then parallel imaging reconstruction accuracy improves, but scanning time increases
Solution Approach 1:
The patent applies partial action by acquiring reference data only at specific strategic locations (center of k-space and additional reference points) rather than performing complete reference scans across the entire field of view. This partial acquisition provides sufficient information to calculate the necessary weighting factors while significantly reducing the time required compared to full reference scans.
Solution Approach 2:
The patent performs preliminary reference data acquisition at key positions before the main parallel imaging scan. This preliminary action provides the necessary calibration information to calculate weighting factors that will be used during reconstruction, eliminating the need for time-consuming reference scans during the actual imaging process.
4Reliability
If B0 homogeneity is improved to reduce artifacts, then image quality improves, but system complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical/apparatus-based solution of improving B0 homogeneity through complex shimming systems and hardware adjustments with an information-based solution. By calculating and applying weighting factors derived from reference data, the system compensates for B0 inhomogeneities through software processing rather than requiring complex hardware modifications.
Solution Approach 2:
The patent changes the approach from physically improving B0 homogeneity to mathematically compensating for inhomogeneities through parameter changes in the weighting factors. This allows the system to work with the existing B0 field characteristics rather than requiring ideal homogeneous conditions, reducing system complexity.
Data Source
AI summary
In a magnetic resonance (MR) apparatus and an operating method therefor, the MR apparatus has multiple reception coils each having an associated reception channel, a reference dataset is obtained from an examination volume of a subject, wherein the reference dataset completely fills a region of k-space. In a computer, a subregion of the examination volume is determined that has a lower homogeneity than other subregions of the examination volume, and the computer also determines at least one of the reception channels in which raw data signals are received that have a higher intensity in the determined subregion than others of the reception channels. The computer calculates a weighting matrix, in which signals, the determined reception channel are given a lower weighting than signals from the other channels. The weighting matrix is then applied to diagnostic data acquired with parallel imaging using the multiple reception coils and channels.