MRI Coil Sensitivity Estimation Using K-Space Smoothing Filters
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Solution Overview
Problem
Current MRI methods using phased array coils suffer from low image contrast due to the lack of accurate coil sensitivity weighting, particularly with the sum-of-squares method, which does not account for individual coil sensitivities, leading to signal bias and reduced contrast.
Innovation Solution
The method employs a k-space smoothing filter, either triangular or pyramidal in shape, to estimate coil sensitivities by applying it to the k-space data from each coil, allowing for accurate weighting and improved image reconstruction using the SUPER algorithm, thereby enhancing image contrast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the sum-of-squares method is used to combine coil images, then the reconstruction process is simple and does not require coil sensitivity maps, but the image contrast is reduced due to signal bias
Solution Approach 1:
The patent applies preliminary smoothing filters to the coil images before combining them to estimate coil sensitivity profiles. This preliminary action allows the system to subsequently apply accurate sensitivity weighting during image combination, resolving the contradiction between reconstruction simplicity and image contrast by automating the sensitivity estimation process.
Solution Approach 2:
The system uses the acquired coil images themselves to generate the sensitivity estimates through automated smoothing and combination processes. Rather than requiring external sensitivity measurements or complex calibration procedures, the method makes the images self-describing by extracting sensitivity information directly from the acquired data.
2Illumination intensity
If coil sensitivity profiles are accurately estimated and applied for weighting, then image contrast is improved, but the reconstruction process becomes more complex
Solution Approach 1:
The patent changes the parameter of coil sensitivity estimation from requiring detailed RF field maps to using simplified smoothing filter-based estimation. By adjusting the complexity parameter of sensitivity estimation downward while maintaining accuracy through appropriate filter design, the system achieves good contrast without excessive reconstruction complexity.
Solution Approach 2:
The patent introduces smoothing filters as an intermediary tool between the raw coil images and the final combined image. These filters serve as a mediator that automatically generates sensitivity estimates, simplifying the overall process while still enabling accurate sensitivity-weighted combination for improved contrast.
3Measurement precision
If detailed RF field maps of each coil are obtained for sensitivity estimation, then accurate sensitivity weighting can be applied, but the measurement process becomes time-consuming and complex
Solution Approach 1:
The patent extracts sensitivity information directly from the acquired coil images through smoothing operations, rather than requiring separate detailed RF field mapping measurements. This extraction approach obtains the necessary sensitivity data as a byproduct of the normal imaging process, eliminating the need for additional time-consuming measurement steps.
Solution Approach 2:
The system uses the acquired images themselves to generate sensitivity estimates without requiring external calibration measurements. The images serve dual purposes: both as the source data for reconstruction and as the basis for estimating sensitivity profiles, making the process self-sufficient and time-efficient.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively increases image contrast by accurately estimating coil sensitivities and combining image data from phased array coils, resulting in a 10% gain in contrast compared to conventional sum-of-squares methods.
Implementation Method 1
The filter fi being a k-space filter with a triangular or pyramidal shape
Implementation Method 2
an estimated sensitivity Bi (Fourier domain) of each coil Ci of the array being used, which is determined by applying a smoothing filter fi to the k-space data si received from each coil Ci
Implementation Method 3
exciting magnetic resonant (MR) active nuclei in a region of interest
Implementation Method 4
receiving radio frequency data from the region of interest using an array of at least two radio frequency receive coils
Data Source
AI summary
A method of magnetic resonance imaging includes exciting magnetic resonant active nuclei in a region of interest; creating magnetic field gradients; receiving radio frequency data from the region of interest; and producing an image by combining images obtained from radio frequency signals of single coils of the array and weighting the images of each coil with a sensitivity of the corresponding coil, wherein an estimated sensitivity of each coil of the array being used is determined by applying a smoothing filter to a k-space data set received from each coil; and wherein for a one-dimensional sensitivity profile the filter is configured with a triangular shape and for a two-dimensional sensitivity profile the filter is configured with a pyramidal shape, the triangular filter having a width and the pyramidal filter having a base double a maximum spatial frequency of the corresponding coil field.