Scalable self-calibrated interpolation of undersampled magnetic resonance imaging data
AssigneeRegents of the University of Minnesota
InventorsSteen Moeller, Mehmet Akcakaya, Seng-Wei Chieh
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Abstract
A fully sampled calibration data set, which may be Cartesian k-space data, is used to obtain targeted and optimal interpolation kernels for non-regularly sampled data. The calibration data are self-calibration data obtained from a time-averaged image, or re-sampled data. ACS data are resampled for calibration of region-specific kernels. Subsequently, an explicit noise-based regularized solution can be utilized to estimate region-specific kernels for reconstruction.
Claims36
A method for producing an image of a subject with a magnetic resonance imaging (MRI) system, the steps of the method comprising:
- (a) acquiring undersampled k-space data with an MRI system using a radio frequency (RF) coil array having a plurality of coils, wherein the undersampled k-space data sample k-space along at least one non-Cartesian trajectory;
- (b) generating composite data from the undersampled k-space data;
- (c) generating regridded data from the composite data by regridding at least some of the composite data to a Cartesian grid;
- (d) determining a region-specific interpolation kernel (RIK) geometry;
- (e) generating calibration data from the regridded data by resampling the regridded data using the RIK geometry;
- (f) estimating reconstruction kernels from the calibration data;
- and
- (g) reconstructing an image of the subject from the undersampled k-space data using the computed reconstruction kernels to synthesize additional k-space data.
A method for producing an image of a subject with a magnetic resonance imaging (MRI) system, the steps of the method comprising:
- (a) acquiring undersampled k-space data with an MRI system using a radio frequency (RF) coil array having a plurality of coils;
- (b) determining a region-specific interpolation kernel (RIK) geometry;
- (c) generating calibration data using the RIK geometry;
- (d) estimating reconstruction kernels from the calibration data;
- and
- (e) reconstructing an image of the subject from the undersampled k-space data using the computed reconstruction kernels to synthesize additional k-space data.
Dependencies are inferred from the claim text.