Systems and methods for accelerating the acquisition and reconstruction of magnetic resonance images with randomly undersampled and uniformly undersampled data
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.
1. A method of reconstructing magnetic resonance (“MR”) images, the method comprising:
obtaining a first set of data from a first receiver coil associated with an MR imaging device, the first set of data being a randomly undersampled subset of uniformly undersampled data;
generating a second set of data based on the first set of data, the second set of data being a set of uniformly undersampled data and being associated with a first reduced field-of-view (“FOV”) image;
obtaining a third set of data from a second receiver coil associated with an MR imaging device, the third set of data also being a randomly undersampled subset of uniformly undersampled data;
generating a fourth set of data based on the third set of data, the fourth set of data also being a set of uniformly undersampled data and being associated with a second reduced FOV image;
generating a fifth set of data based on the second set of data and the fourth set, the fifth set of data being associated with a reconstructed full FOV image; and
generating, using a processor associated with the MR imaging device, the reconstructed full FOV image based on the fifth set of data.
2. The method of claim 1 , further comprising applying a sensitivity modulation to the first receiver coil and the second receiver coil.
3. The method of claim 1 , further comprising
applying a convex optimization to the first set of data in order to generate the second set of data, and
applying a convex optimization to the third set of data in order to generate the fourth set of data.
4. The method of claim 1 , further comprising applying a selected sampling pattern in order to obtain the first set of data.
5. The method of claim 4 , wherein the sampling pattern is a random sampling pattern based on a compressed sensing.
6. A system configured for reconstructing magnetic resonance (“MR”) images, the system comprising:
a processing unit associated with an MR imaging device, the processing unit configured to
obtain a first set of data from a first receiver coil associated with an MR imaging device, the first set of data being a randomly undersampled subset of uniformly undersampled data,
generate a second set of data based on the first set of data, the second set of data being a set of uniformly undersampled data and being associated with a first reduced field-of-view (“FOV”) image,
obtain a third set of data from a second receiver coil associated with an MR imaging device, the third set of data also being a randomly undersampled subset of uniformly undersampled data,
generate a fourth set of data based on the third set of data, the fourth set of data also being a set of uniformly undersampled data and being associated with a second reduced FOV image,
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, and
generate the reconstructed full FOV image based on the fifth set of data.
7. The system of claim 6 , wherein the processing unit is further configured in order to apply a sensitivity modulation to the first receiver coil and the second receiver coil.
8. The system of claim 6 , wherein the processing unit is further configured in order to
apply a convex optimization to the first set of data in order to generate the second set of data, and
apply a convex optimization to the third set of data in order to generate the fourth set of data.
9. The system of claim 6 , wherein the processing unit is further configured in order to apply a selected sampling pattern in order to obtain the first set of data.
10. The system of claim 9 , wherein the sampling pattern is a random sampling pattern based on a compressed sensing.
11. A method of magnetic resonance (“MR”) image reconstruction configured for use with an MR imaging device, the method comprising:
(a) randomly undersampling uniformly undersampled signals from each of a plurality of receiver coils based on compressed sensing in order to generate a first set of data;
(b) applying a convex optimization to the first set of data in order to generate a second set of data, the second set of data being associated with a uniformly undersampled reduced field-of-view (“FOV”) image from each of the plurality of receiver coils;
(c) applying a parallel magnetic resonance imaging (“pMRI”) reconstruction to the second set of data in order to generate a third set of data, the third set of data being associated with a reconstructed full FOV image; and
(d) generating, using a processor associated with the MR imaging device, the reconstructed full FOV image based on the third set of data.
12. The method of claim 11 , wherein the plurality of receiver coils includes eight receiver coils.
13. The method of claim 11 , 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 a compressed sensing and a second reduction factor resulting from applying the pMRI reconstruction.
14. A system configured for reconstructing magnetic resonance (“MR”) images, the system comprising:
a processing unit associated with an MR imaging device, the processing unit configured to
(a) randomly undersample uniformly undersampled signals from each of a plurality of receiver coils based on compressed sensing in order to generate a first set of data,
(b) apply a convex optimization to the first set of data in order to generate a second set of data, the second set of data being associated with a uniformly undersampled, reduced field-of-view (“FOV”) image from each of the plurality of receiver coils,
(c) apply a parallel magnetic resonance imaging (“pMRI”) reconstruction to the second set of data in order to generate a third set of data, the third set of data being associated with a reconstructed full FOV image, and
(d) generate the reconstructed full FOV image based on the third set of data.
15. The system of claim 14 , wherein the plurality of receiver coils includes eight receiver coils.
16. The system of claim 14 , 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 a compressed sensing and a second reduction factor resulting from applying the pMRI reconstruction.