Noise-suppressed nonlinear reconstruction of magnetic resonance images
OwnerSteen MOELLER, Mehmet AKÇAKAYA +1inventors
InventorsSteen MOELLER, Mehmet AKÇAKAYA, Kamil UGURBIL
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Abstract
Denoised magnetic resonance images are generated using a two-step process. An initial set of images is first denoised on a per channel basis using a locally low-rank-based denoising technique. The denoised coil channel images are transformed back into k-space and the denoised k-space data are then applied to a nonlinear image reconstruction. In some instances, the nonlinear image reconstruction can be implemented using a trained neural network. The neural network may be trained using a self-supervised learning technique.
Claims25
A method for reconstructing denoised magnetic resonance images, the method comprising:
- (a) accessing k-space data with a computer system, wherein the k-space data have been acquired using a multichannel receiver;
- (b) reconstructing coil channel images from the k-space data using the computer system, wherein each coil channel image corresponds to a different channel of the multichannel receiver;
- (c) generating denoised coil channel images with the computer system by applying a denoising algorithm to the coil channel images using the computer system;
- (d) generating denoised k-space data from the denoised coil channel images using the computer system to transform the denoised coil channel images into k-space;
- and
- (e) reconstructing denoised magnetic resonance images from the denoised k-space data using the computer system by applying the denoised k-space data to a nonlinear reconstruction algorithm, generating output as the denoised magnetic resonance images.
A method for reconstructing denoised magnetic resonance images, the method comprising:
- (a) accessing k-space data with a computer system, wherein the k-space data have been acquired using a multichannel receiver;
- (b) reconstructing coil channel images from the k-space data using the computer system, wherein each coil channel image corresponds to a different channel of the multichannel receiver;
- (c) generating denoised coil channel images with the computer system by applying a singular value thresholding using a locally low-rank (LLR) model to the coil channel images using the computer system;
- (d) generating denoised k-space data from the denoised coil channel images using the computer system to transform the denoised coil channel images into k-space;
- and
- (e) reconstructing denoised magnetic resonance images from the denoised k-space data using the computer system.
A method for reconstructing denoised magnetic resonance images, the method comprising:
- (a) accessing k-space data with a computer system;
- (b) generating denoised k-space data with the computer system by applying a singular value thresholding using a locally low-rank (LLR) model to the k-space data using the computer system;
- and
- (c) reconstructing denoised magnetic resonance images from the denoised k-space data using the computer system.
Dependencies are inferred from the claim text.