SYSTEMS AND METHODS FOR ACCELERATING THE ACQUISITION AND RECONSTRUCTION OF MAGNETIC RESONANCE IMAGES

• US 20110006768A1
• Filed: 07/09/2010
• Published: 01/13/2011
• Est. Priority Date: 07/09/2009
• Status: Active Grant

• Current Assignee: UWM Research Foundation
• Original Assignee: UWM Research Foundation
• Inventors: Liang, Dong, Ying, Lei
• Granted Patent: US 8,587,307 B2
• Time in Patent Office: Days
• US Class Current: 324/309
• CPC Class Codes: G01R 33/5611 Parallel magnetic resonance imaging, e.g. sensitivity encoding [SENSE], simultaneous acquisition of spatial harmonics [SMASH], unaliasing by Fourier encoding of the overlaps using the temporal dimension [UNFOLD], k-t-broad-use linear acquisition speed-up technique [k-t-BLAST], k-t-SENSE structural details of arrays of sub-coils G01R33/3415

Abstract

A method and system of accelerating the acquisition and reconstruction of magnetic resonance images. Magnetic resonance imaging (“MRI”) data is acquired from a plurality of coils using parallel MRI (“pMRI”). The MRI data represents a reduced field-of-view (“FOV”) image for each of a plurality of coils. The MRI data is further undersampled by sequentially applying a compressed sensing (“CS”) technique, such as SparseMRI. The undersampled, reduced FOV images are then reconstructed into a final magnetic resonance image using a pMRI reconstruction technique, such as SENSitivity encoding (“SENSE”). This combination of MR image acquisition, sampling, and reconstruction is referred to as CS-SENSE.

Claims

1. A method of reconstructing magnetic resonance (“

MR”

) images, the method comprising;

obtaining a first set of data from a first receiver coil, the first set of data being a subset of a second set of data, the second set of data being associated with a first reduced field-of-view (“

FOV”

) image;

obtaining a third set of data from a second receiver coil, the third set of data being a subset of a fourth set of data, the fourth set of data being associated with a second reduced FOV image;

generating the second set of data based on the first set of data;

generating the fourth set of data based on the third set of data; and

generating a fifth set of data based on the second set of data and the fourth set of data, the fifth set of data being associated with a reconstructed full FOV image.

2. The method of claim 1, further comprising applying sensitivity modulations to the first receiver coil and the second receiver coil.

3. The method of claim 1, further comprising

applying convex optimization to the first set of data to generate the second set of data, and

applying convex optimization to the third set of data to generate the fourth set of data.

4. The method of claim 1, further comprising applying a selected sampling pattern to obtain the first set of data.

5. The method of claim 4, wherein the sampling pattern is a random sampling pattern based on compressed sensing.

6. The method of claim 1, wherein the first set of data is a randomly undersampled subset of the second set of data.

7. A system for reconstructing images, the system comprising:

a processing unit configured to

obtain a first set of data from a first receiver coil, the first set of data being a subset of a second set of data, the second set of data associated with a first reduced field-of-view (“

FOV”

) image,

obtain a third set of data from a second receiver coil, the third set of data being a subset of a fourth set of data, the fourth set of data associated with a second reduced FOV image,

generate the second set of data based on the first set of data,

generate the fourth set of data based on the third set of data, and

generate a fifth set of data based on the second set of data and the fourth set of data, the fifth set of data being associated with a reconstructed full FOV image.

8. The system of claim 7, wherein the processing unit is further configured to apply sensitivity modulations to the first receiver coil and the second receiver coil.

9. The system of claim 7, wherein the processing unit is further configured to

apply convex optimization to the first set of data to generate the second set of data, and

apply convex optimization to the third set of data to generate the fourth set of data.

10. The system of claim 7, wherein the processing unit is further configured to apply a selected sampling pattern to obtain the first set of data.

11. The system of claim 10, wherein the sampling pattern is a random sampling pattern based on compressed sensing.

12. The system of claim 7, wherein the first set of data is a randomly undersampled subset of the second set of data.

13. A method of image reconstruction, the method comprising:

(a) sampling signals from each of a plurality of receiver coils based on compressed sensing to generate a first set of data, the first set of data being associated with an undersampled, reduced field-of-view (“

FOV”

) image from each of the plurality of receiver coils;

(b) applying a convex optimization to the first set of data to generate a second set of data, the second set of data being associated with a reduced FOV image from each of the plurality of receiver coils; and

(c) applying a parallel magnetic resonance imaging (“

pMRI”

) reconstruction to the second set of data to generate a third set of data, the third set of data being associated with a reconstructed full FOV image.

14. The method of claim 13, wherein the plurality of receiver coils includes eight receiver coils.

15. The method of claim 13, wherein the first set of data is a randomly undersampled subset of the second set of data.

16. The method of claim 13, wherein an overall data reduction factor associated with the reconstructed full FOV image is a product of a first reduction factor resulting from sampling signals from each of the plurality of receiver coils based on compressed sensing and a second reduction factor resulting from applying the pMRI reconstruction.

17. A system for reconstructing images, the system comprising:

a processing unit configured to

(a) sample signals from each of a plurality of receiver coils to generate a first set of data, the first set of data being associated with an undersampled, reduced field-of-view (“

FOV”

) image from each of the plurality of receiver coils,

(b) apply a convex optimization to the first set of data to generate a second set of data, the second set of data being associated with a reduced FOV image from each of the plurality of receiver coils, and

(c) apply parallel magnetic resonance imaging (“

pMRI”

) reconstruction to the second set of data to generate a third set of data, the third set of data being associated with a reconstructed full FOV image.

18. The system of claim 17, wherein the plurality of receiver coils includes eight receiver coils.

19. The system of claim 17, wherein the first set of data is a randomly undersampled subset of the second set of data.

20. The system of claim 17, wherein an overall data reduction factor associated with the reconstructed full FOV image is a product of a first reduction factor resulting from sampling signals from each of the plurality of receiver coils based on compressed sensing and a second reduction factor resulting from applying the pMRI reconstruction.