System And Method Of Parallel Imaging With Calibration To A Virtual Coil

• US 20100244825A1
• Filed: 03/31/2009
• Published: 09/30/2010
• Est. Priority Date: 03/31/2009
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Brau, Anja C.S., Beatty, Philip James
• Granted Patent: US 8,076,938 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 for generating a magnetic resonance (MR) image includes acquiring calibration data from each of a plurality of RF source coils. Calibration data for a virtual coil is generated based on the calibration data from the plurality of RF source coils and a set of synthesis weights is generated based on the calibration data from the plurality of RF source coils and the calibration data for the virtual coil. Accelerated MR data is acquired from each of the plurality of RF source coils. An image can be reconstructed based on an application of the set of synthesis weights to the accelerated MR data from the plurality of RF source coils.

Claims

1. A magnetic resonance imaging (MRI) system comprising:

a resonance assembly comprising a plurality of gradient coils and a plurality of RF source coils;

an RF transceiver system coupled to the plurality of RF source coils and configured to receive magnetic resonance (MR) data from the plurality of RF source coils; and

a controller programmed to;

receive MR data of an imaging subject from each of the plurality of RF source coils;

generate MR data for a virtual coil;

determine a set of weights based on the MR data received from each RF source coil and the MR data generated for the virtual coil;

generate a complete MR data set for the virtual coil based only on at least a portion of the MR data from at least two of the RF source coils and the set of weights; and

reconstruct an image based on the complete MR data set for the virtual coil.

2. An MRI system according to claim 1, wherein generating a complete MR data set for the virtual coil comprises applying the set of weights to the at least a portion of the MR data from at least two of the RF source coils.

3. An MRI system according to claim 1, wherein the MR data received from each of the plurality of RF source coils comprises calibration data.

4. An MRI system according to claim 3, wherein the MR data generated for the virtual coil comprises calibration data.

5. An MRI system according to claim 4, wherein generating the MR data for the virtual coil comprises:

transforming the calibration data from each source coil to form a low resolution image;

combining the low resolution images for the plurality of source coils to form a single combined image; and

inverse transforming the combined image to generate the calibration data for the virtual coil.

6. An MRI system according to claim 4, wherein the set of weights is determined based on the calibration data from each of the plurality of source coils and the calibration data for the virtual coil.

7. An MRI system according to claim 4, wherein the MR data received from each of the plurality of RF source coils further comprises a set of accelerated MR data.

8. An MRI system according to claim 7, wherein the set of weights are applied to the set of accelerated MR data from each source coil to generate the complete MR data set for the virtual coil.

9. An MRI system according to claim 1, wherein the set of weights is a set of merged coefficients.

10. An MRI system according to claim 9, wherein determining the set of merged coefficients comprises:

calculating a set of coil combination coefficients;

calculating a set of unaliasing coefficients; and

combining the set of coil combination coefficients and the set of unaliasing coefficients to form a single set of coefficients.

11. A method for generating a magnetic resonance (MR) image comprising:

acquiring calibration data from each of a plurality of RF source coils;

generating calibration data for a virtual coil based on the calibration data from the plurality of RF source coils;

generating a set of synthesis weights based on the calibration data from the plurality of RF source coils and the calibration data for the virtual coil;

acquiring accelerated MR data from each of the plurality of RF source coils;

generating a complete MR data set for the virtual coil based only on the accelerated MR data from at least two of the RF source coils and the set of synthesis weights; and

reconstructing an image based on the complete MR data set for the virtual coil.

12. A method according to claim 11, wherein generating a complete MR data set for the virtual coil comprises applying the set of synthesis weights to the accelerated MR data from at least two of the RF source coils.

13. A method according to claim 11, wherein generating a complete MR data set for the virtual coil comprises:

transforming the set of synthesis weights to hybrid space;

transforming the accelerated MR data from the at least two RF source coils to hybrid space; and

applying the transformed set of synthesis weights to the transformed accelerated MR data from the at least two RF source coils to generate a complete hybrid space data set for the virtual coil.

14. A method according to claim 13, wherein reconstructing an image comprises reconstructing an image from the complete hybrid space data set for the virtual coil.

15. A method according to claim 11, wherein generating calibration data for the virtual coil comprises:

transforming the calibration data from each source coil to form a low resolution image;

combining the low resolution images for the plurality of source coils to form a single combined image; and

inverse transforming the combined image to generate the calibration data for the virtual coil.

16. A method according to claim 11, wherein the set of synthesis weights is a set of merged coefficients.

17. A method according to claim 16, wherein generating a set of merged coefficients comprises:

calculating a set of coil combination coefficients;

calculating a set of unaliasing coefficients; and

combining the set of coil combination coefficients and the set of unaliasing coefficients to form a single set of coefficients.

18. A computer readable storage medium having a program stored thereon that when executed by a processor causes the processor to:

access MR data of an imaging subject acquired from each of at least two RF source coils;

generate MR data for a virtual coil;

determine a set of linear combination weights based on the MR data from the at least two RF source coils and the MR data for the virtual coil;

generate a complete MR data set for the virtual coil based only on the MR data from the at least two RF source coils and the set of linear combination weights; and

reconstruct an image based on the complete MR data set for the virtual coil.

19. A computer readable storage medium according to claim 18, wherein the MR data from the at least two RF source coils comprises calibration data and accelerated MR data.

20. A computer readable storage medium according to claim 19, wherein generating MR data for the virtual coil comprises generating calibration data for the virtual coil based on the calibration data from the at least two RF source coils.

21. A computer readable storage medium according to claim 20, wherein the set of linear combination weights are determined based on the calibration data from the at least two RF source coils and the calibration data generated for the virtual coil.

22. A computer readable storage medium according to claim 19, wherein the complete MR data set for the virtual coil is generated based only on the accelerated data from the at least two RF source coils and the linear combination weights.

23. A computer readable storage medium according to claim 22, wherein generating the complete MR data set for the virtual coil comprises applying the set of linear combination weights to the accelerated MR data from at least two of the RF source coils.

24. A computer readable storage medium according to claim 18, wherein the set of linear combination weights is a set of merged coefficients.

25. A computer readable storage medium according to claim 24, wherein to determine the set of linear combination weights the program further causes the processor to:

calculate a set of coil combination coefficients;

calculate a set of unaliasing coefficients; and

combine the set of combination coefficients and the set of unaliasing coefficients to form a single set of coefficients.

26. A method for generating a magnetic resonance (MR) image comprising:

acquiring calibration data from each of a plurality of RF source coils;

generating calibration data for a virtual coil based on the calibration data from the plurality of RF source coils;

generating a set of synthesis weights based on the calibration data from the plurality of RF source coils and the calibration data for the virtual coil;

accessing accelerated MR data associated with the plurality of RF source coils;

generating a complete MR data set for the virtual coil based only on the accelerated MR data associated with the plurality of RF source coils and the set of synthesis weights; and

reconstructing an image based on the complete MR data set for the virtual coil.

27. A method according to claim 26, wherein the accelerated MR data associated with the plurality of MR source coils includes accelerated MR data acquired from the plurality of RF source coils and accelerated MR data synthesized from the acquired accelerated MR data.

28. A method according to claim 27, wherein generating a complete MR data set for the virtual coil comprises applying the set of synthesis weights to at least a portion of the synthesized accelerated MR data.

29. A method according to claim 27, wherein generating a complete MR data set for the virtual coil comprises applying the set of synthesis weights to at least a portion of the acquired accelerated MR data.

30. A method according to claim 27, wherein generating a complete MR data set for the virtual coil comprises applying the set of synthesis weights to at least a portion of the synthesized accelerated MR data and at least a portion of the acquired accelerated MR data.