MRF Out-of-View Artifact Suppression via Adaptive Coil Combination
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Solution Overview
Problem
Conventional magnetic resonance fingerprinting (MRF) techniques lack effective suppression of out-of-view artifacts, which limits the quality of MRF images and subsequent parameter estimates, requiring manual selection of regions-of-interest and assuming equal artifact contribution across parallel receive coils.
Innovation Solution
A method and system for MRF that acquire data using a non-Cartesian, variable density sampling trajectory, generate coil images with a larger field-of-view, determine noise covariance, apply an adaptive coil combination for artifact suppression, and compare the suppressed data with a dictionary to identify tissue properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional MRF techniques are used without artifact suppression, then the acquisition process is simple and fast, but out-of-view artifacts degrade image quality and parameter estimation accuracy
Solution Approach 1:
The method performs preliminary actions by generating coil images with a larger field of view before the main processing, and calculating noise covariance from out-of-view regions in advance. This preliminary preparation enables the subsequent adaptive coil combination to effectively suppress artifacts while maintaining processing efficiency
Solution Approach 2:
The patent introduces an adaptive coil combination technique that uses noise covariance information as an intermediary to suppress out-of-view artifacts. The noise covariance calculated from out-of-view regions serves as a mediator to guide the artifact suppression process, improving image quality without requiring complex manual intervention
2Measurement precision
If manual selection of region-of-interest is used for artifact suppression, then artifact suppression can be targeted, but the process requires user skill and time
Solution Approach 1:
The system performs self-service by automatically determining the region-of-interest and calculating noise covariance without requiring manual user input. The adaptive coil combination technique autonomously identifies out-of-view regions and uses them to suppress artifacts, eliminating the need for user skill in region selection while maintaining high parameter estimation accuracy
Solution Approach 2:
The method performs preliminary action by automatically generating coil images with a larger field of view and calculating noise covariance from out-of-view regions before the main processing. This preliminary automated preparation eliminates the need for manual region-of-interest selection by the user
3Productivity
If equal artifact contribution is assumed across parallel receive coils, then the processing is simple, but the artifact suppression is sub-optimal
Solution Approach 1:
The patent applies local quality by calculating separate noise covariance information for each coil from out-of-view regions, rather than assuming equal artifact contribution. This localized approach allows each coil to be processed according to its specific noise characteristics, improving image quality while maintaining processing efficiency through automated methods
Solution Approach 2:
The method changes the parameter approach by transitioning from assuming equal artifact contribution across coils to calculating individual noise covariance for each coil. This parameter change enables the adaptive coil combination to optimally suppress artifacts from each coil based on its specific noise characteristics
Data Source
AI summary
A method for magnetic resonance fingerprinting with out-of-view artifact suppression includes acquiring MRF data from a region of interest in a subject. The MRF data is acquired using a non-Cartesian, variable density sampling trajectory. The MRF data includes data from within a desired field-of-view and data from outside the desired field-of-view. The method also includes generating a set of coil images based on the MRF data with a field-of-view larger than the desired field-of-view, determining a noise covariance based on the MRF data from outside the desired field-of-view, generating a coil combined image using an adaptive coil combination determined based on the noise covariance, applying the adaptive coil combination to the MRF data to grid each frame of the MRF data and generate MRF data with out-of-view artifact suppression. The method also includes identifying at least one property of the MRF data and generating a report.