Method and system for correcting errors in MR images due to regions of gradient non-uniformity for parametric imaging such as quantitative flow analysis

• US 6,163,152 A
• Filed: 06/15/1998
• Issued: 12/19/2000
• Est. Priority Date: 06/15/1998
• Status: Expired due to Term

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Polzin, Jason A., Bernstein, Matthew A.
• Primary Examiner(s): Oda, Christine K.
• Assistant Examiner(s): Fetzner, Tiffany A.
• Application Number:
  US09/097,525
• Time in Patent Office: 918 Days
• Field of Search: 324/306, 324/307, 324/309
• US Class Current: 324/306
• CPC Class Codes: G01R 33/56518 due to eddy currents, e.g. caused by switching of the gradient magnetic field

Abstract

A system and method for correcting systematic errors that occur in MR images due to magnetic gradient non-uniformity is disclosed for use with parametric analysis. A GradWarp geometric correction operation is applied in reconstructing quantitative parametric analysis images in regions of gradient non-uniformity. The method includes generating an error map of magnetic gradient strength as a function of distance for an MR image scan and acquiring MR data that contain such systematic errors. The method next includes either calculating a measured diffusion image, a phase difference image, or similar image, based on the acquired MR data, and then calculating a corrected parametric image using the error map and the measured diffusion image, the phase difference image, or other similar parametric image. The method is incorporated into a system having a computer programmed to perform the aforementioned steps and functions.

Claims

1. A method of correcting systematic errors occurring due to magnetic gradient non-uniformity in phase contrast MR images for quantitative flow analysis comprising the steps of

generating a gradient non-uniformity error map for an MR image scan that includes a representation of magnetic gradient strength non-uniformity as a function of distance;

acquiring at least two MR data sets having flow sensitive gradients containing systematic errors due to magnetic gradient non-uniformity;

calculating a phase difference image to determine a measured velocity image; and

calculating a corrected velocity image using the measured velocity image and the gradient non-uniformity error map.

2. The method of claim 1 wherein the step of calculating the corrected velocity image is further defined as dividing the measured velocity image by the gradient non-uniformity error map.

3. The method of claim 1 wherein each MR data set has imaginary and real components and the MR data sets are acquired in a time domain, and further comprising the step of Fourier transforming the time domain data sets into a frequency domain.

4. The method of claim 1 wherein the direction of the flow sensitive gradients are defined by three direction angles (θ

₁, θ

₂, θ

₃), each measured with respect to three orthogonal axes.

5. The method of claim 4 further comprising the step of calculating a cosine of each direction angle to form a set of direction cosines (cos θ

₁, cos θ

₂,cos θ

₃).

6. The method of claim 4 wherein the step of calculating a corrected velocity image is calculated according to:

##EQU10## where θ

_i is the direction angle associated with axis i, ƒ

_i is the gradient non-uniformity error map associated with axis i, and i is one of three axes x, y, z.

7. The method of claim 1 wherein the step of generating a gradient non-uniformity error map is further defined as generating the error map as a spatial function based on pixel displacement from a gradient isocenter as measured along three axes.

8. A system for correcting systematic errors occurring due to magnetic gradient non-uniformity in phase contrast MR images for quantitative flow analysis comprising:

means for acquiring at least two MR data sets having flow sensitive gradients containing systematic errors due to magnetic gradient iron-uniformity and generating a phase image therefrom for each acquired MR data set;

means for generating a gradient non-uniformity error for an MR image scan, that includes a representation of magnetic gradient strength non-uniformity as a function of distance, calculating a phase difference image from each phase image generated to determine a measured velocity image, calculating a corrected velocity image using the measured velocity image and the gradient non-uniformity error map.

9. The system of claim 8 where in the means for calculating the corrected velocity image is further defined as dividing the measured velocity image by the gradient non-uniformity error map.

10. The system of claim 8 wherein the MR data sets contain imaginary and real components and are acquired in a time domain, and the means for calculating further comprising the step of Fourier transforms the time domain data sets into a frequency domain.

11. The system of claim 8 wherein each MR data set comprises three components, each component having a direction angle associated with one of three axes.

12. The system of claim 11 further comprising means for calculating a cosine of each direction angle to form a set of direction cosines (cos θ

₁,cos θ

₂,cos θ

₃).

13. The system of claim 11 wherein the means for calculates, a corrected velocity image according to:

##EQU11## where θ

_i is the direction angle associated with axis i, f_i is the gradient non-uniformity map associated with axis i, one of three axes x, y, z.

14. A system to correct systematic errors occurring due to magnetic gradient non-uniformity in phase contrast MR images for quantitative flow analysis comprising a processor programmed to:

generate a gradient non-uniformity error map for an MR image scan that includes a representation of magnetic gradient strength non-uniformity as a function of distance;

acquire at least two NM data sets having flow sensitive gradients containing a systematic error due to magnetic gradient non-uniformity;

calculate a phase difference image to determine a measured velocity image; and

calculate a corrected velocity image using the measured velocity image and the gradient non-uniformity error map.

15. The system of claim 14 wherein the processor is farther programmed to generate a gradient non-uniformity error spatial function based on pixel displacement from gradient isocenter as measured along three axes.

16. The system of claim 14 wherein each MR data set comprises three components, each component having a direction angle associated with one of three axes.

17. The system of claim 16 wherein the processor is further programmed to generate a cosine of each direction angle to form direction cosines (cosθ

₁,cosθ

₂,cos θ

₃).

18. The system of claim 14 wherein the processor is further programmed to generate a corrected velocity image according to:

##EQU12## where θ

_i is the direction angle associated with axis i, ƒ

_i is the gradient non-uniformity error map associated with axis i, and i is one of three axes x, y, z.

19. A method of correcting systematic errors occurring due to magnetic gradient non-uniformity in diffusion MR images comprising the steps of

generating at least one gradient non-uniformity error map for an MR image scan that includes a representation of magnetic gradient strength non-uniformity as a function of distance;

acquiring at least one MR data set with diffusion sensitizing gradients containing systematic errors due to magnetic gradient non-uniformity;

calculating a measured diffusion image based on the acquired MR data set, and

calculating a corrected diffusion image using the measured diffusion image and at least one gradient non-uniformity error map.

20. The method of claim 19 wherein the corrected diffusion image is calculated according to:

##EQU13## where D is the diffusion coefficient, ƒ

_i,j are gradient non-uniformity error maps.

21. The method of claim 20 wherein i=j and:

##EQU14##

22. A system for correcting systematic errors occurring due to magnetic gradient non-uniformity in diffusion MR images comprising:

means for acquiring at least one MR data set with diffusion sensitizing gradients that contain systematic errors due to magnetic gradient non-uniformity;

means for generating at least one gradient non-uniformity error map for an MR image scan, that includes a representation of magnetic gradient strength non-uniformity as a function of distance, calculating a measured diffusion image based on the acquired MR data sets, and calculating a corrected diffusion image using the measured diffusion image and at least one gradient non-uniformity error map.

23. The method of claim 22 wherein the corrected diffusion image is calculated according to:

##EQU15## where D is the diffusion coefficient, ƒ

_i,j are gradient non-uniformity error maps.

24. The method of claim 23 wherein i=j and:

##EQU16##

25. A system to correct systematic errors occurring due to magnetic gradient non-uniformity in diffusion MR images comprising a processor programmed to:

generate at least one gradient non-uniformity error map for an MR image scan that includes a representation of magnetic gradient strength non-uniformity as a function of distance;

acquire at least one MR data set with diffusion sensitizing gradients that contain systematic errors due to magnetic gradient non uniformity;

calculate a measured diffusion image based on the at least one MR data set acquired; and

calculate a corrected diffusion image using the measured diffusion image and the at least one gradient non-uniformity error map.

26. The method of claim 25 wherein the corrected diffusion image is calculated according to:

##EQU17## where D is the diffusion coefficient, ƒ

_i,j is the gradient non-uniformity error map.

27. The method of claim 25 wherein i=j and:

##EQU18##