MRI Frequency Response Correction for Low-Field Image Uniformity
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Solution Overview
Problem
Magnetic resonance imaging (MRI) systems with low-field strengths (≤1.5 T) face challenges in image quality due to narrower bandwidths and frequency dependencies, leading to brightness fluctuations and contrast issues, which existing solutions only partially address through high-quality hardware or limited correction methods.
Innovation Solution
A method that acquires frequency response data for magnetic resonance systems, applies frequency response correction to magnetic resonance data during image reconstruction, and uses prescan data to normalize and correct for spatial sensitivity variations, enabling improved image quality by compensating for frequency dependencies and ensuring uniform contrast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-field magnetic resonance systems (≤1.5 T) are used, then cost and accessibility are improved, but bandwidth of transmitting and receiving systems becomes significantly narrower leading to frequency dependency
Solution Approach 1:
The patent applies preliminary action by measuring the frequency response of the coil system before actual imaging, storing these characteristics in advance, and using them for correction during image reconstruction. This pre-characterization approach allows the system to compensate for the inherently narrow bandwidth of low-field systems without requiring expensive hardware modifications.
2Loss of energy
If low-field magnetic resonance systems are used, then ohmic losses and object losses are reduced, but frequency dependency causes brightness fluctuations in the image
Solution Approach 1:
The patent implements feedback by measuring the actual frequency response of the coil system, using this measured data to calculate correction factors, and applying these corrections during image reconstruction. This closed-loop approach compensates for frequency-dependent brightness variations while maintaining the energy efficiency benefits of low-field operation.
3Manufacturing precision
If high-quality hardware components are used to achieve consistent frequency response, then image quality is improved, but system cost and complexity increase
Solution Approach 1:
The patent replaces the mechanical/hardware approach of using high-quality components with narrow bandwidths by substituting it with a software-based signal processing solution. Instead of relying on expensive hardware to achieve flat frequency response, the system uses measured frequency response data and applies digital corrections during reconstruction, thereby achieving similar image quality without the associated hardware cost and complexity.
4Manufacturing precision
If bandwidth correction based on measured frequency response is applied, then image artifacts are reduced, but additional measurement and processing steps are required
Solution Approach 1:
The patent merges the frequency response measurement step with the existing coil sensitivity measurement process. By combining these two measurements into a single operational step, the system achieves bandwidth correction and artifact reduction without significantly increasing the overall measurement time or procedural complexity beyond what is already required for parallel imaging setups.
Data Source
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AI summary
The invention relates to a method and a magnetic resonance imaging (MRI) system (1) for improving the image quality of a magnetic resonance image (18) and a corresponding computer-readable storage medium (7). The invention provides that magnetic resonance data of an object under investigation (3) are acquired using the MRI system (1) according to a predetermined measurement sequence (9). Frequency response data for a subsystem (4, 5) of the MRI system are acquired separately from the measurement sequence (9). Based on the frequency data, a frequency response correction is then performed for the MRI data or for prescan data (13), which are taken into account when reconstructing the MRI image (18) from the MRI data.