MRI RF Interference Detection via K-Space Rotation Correlation
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Solution Overview
Problem
Current MRI systems require complex and costly RF shielding cabins to detect and eliminate external RF interference, which increases operational effort and costs, and existing methods for interference suppression are sequence-dependent and may not reliably suppress interference due to insufficient time for interference determination.
Innovation Solution
A method that scans k-space along a trajectory with a rotation angle α between scanning start positions of individual acquisitions, correlates images obtained from these acquisitions to identify RF interference by rotating and comparing them, and uses pattern recognition or machine learning algorithms to mark, delete, or replace interference points, without the need for additional antennas or RF cabins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex shielded RF cabins are installed to reduce external interference, then the signal-to-noise ratio is improved, but the costs and structural limitations increase
Solution Approach 1:
The patent extracts and removes the harmful RF interference signals from the received MRI signals through digital signal processing. By identifying and eliminating interference components in the frequency domain, the method achieves interference suppression without requiring physical shielding structures, thus resolving the contradiction between improving signal quality and reducing structural complexity
Solution Approach 2:
The patent replaces the mechanical/physical shielding system (RF cabins) with a digital signal processing system. Instead of using physical barriers to block interference, the invention uses computational methods to detect and suppress interference signals, thereby eliminating the need for complex structural shielding while maintaining or improving signal-to-noise ratio
2Difficulty of detecting and measuring
If additional receiving antennas are used to detect interference signals, then the interference detection capability is improved, but the device complexity and costs increase
Solution Approach 1:
The patent makes the existing receiving antennas perform multiple functions: they simultaneously capture both the desired MRI signals and the interfering RF signals. By processing the signals from these existing antennas, the system can detect and identify interference without requiring dedicated interference-detection antennas, thus resolving the contradiction between improving detection capability and reducing device complexity
Solution Approach 2:
The existing receiving antennas serve themselves by providing both imaging data and interference detection data. The system utilizes the signals already captured by the antennas for dual purposes: reconstructing images and identifying interference patterns, eliminating the need for separate detection hardware
3Device complexity
If RF cabins are removed to reduce costs, then the structural complexity is reduced, but the ability to detect and eliminate external interference worsens
Solution Approach 1:
The patent replaces physical RF shielding with digital signal processing methods. By analyzing signal characteristics in the frequency domain and applying interference suppression algorithms, the system achieves reliable interference elimination without mechanical shielding structures
Solution Approach 2:
The system continuously monitors the received signals for interference patterns and dynamically adjusts the suppression process. By detecting interference and applying corrective processing in real-time, the system maintains reliable interference suppression capability without requiring passive shielding structures
Data Source
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AI summary
The aim is to enable the detection of RF interference during imaging with a magnetic resonance imaging (MRI) system, particularly without an RF cabinet. A method is provided for this purpose, in which an acquisition is performed (S1), whereby a k-space is scanned along a trajectory and a rotation angle α exists between the starting position of a first single acquisition and the starting position of a subsequent second single acquisition. A first image is obtained from the first single acquisition and a second image from the second single acquisition (S2). One of the two images is rotated relative to the other image by the rotation angle α (S3). A correlation is determined between the rotated image and the other image (S4), and an interference point is identified from this correlation (S5).