Automatic Registration of Image Series with Varying Contrast Based on Synthetic Images Derived from Intensity Behavior Model

• US 20120189183A1
• Filed: 09/20/2011
• Published: 07/26/2012
• Est. Priority Date: 09/28/2010
• Status: Active Grant

• Current Assignee: Siemens Healthineers AG (Siemens AG)
• Original Assignee: Siemens Corp. (Siemens AG)
• Inventors: Xue, Hui, Shah, Saurabh, Gühring, Jens, Greiser, Andreas, Chefd'hotel, Christophe, Guetter, Christoph, Jolly, Marie-Pierre, Zuehlsdorff, Sven
• Granted Patent: US 8,848,990 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: G01R 33/448 Relaxometry, i.e. quantification of relaxation times or spin density G01R33/50 takes precedence
• CPC Class Codes: G01R 33/56509 due to motion, displacement or flow, e.g. gradient moment nulling G01R33/567 takes precedence
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/20201 Motion blur correction
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration

Abstract

A method for performing motion compensation in a series of magnetic resonance (MR) images includes acquiring a set of MR image frames spanning different points along an MR recovery curve. A motion-free synthetic image is generated for each of the acquired MR image frames using prior knowledge pertaining to an MR recovery curve. Each of the acquired MR images is registered to its corresponding generated synthetic images. Motion within each of the acquired MR image is corrected based on its corresponding generated synthetic image that has been registered thereto.

Claims

1. A method for performing motion compensation in a series of magnetic resonance (MR) images, comprising:

acquiring a set of MR image frames spanning different points along an MR recovery curve;

generating a motion-free synthetic image for each of the acquired MR image frames using prior knowledge pertaining to an MR recovery curve;

registering each of the acquired MR images to its corresponding generated synthetic image; and

correcting motion within each of the acquired MR image frames based on its corresponding generated synthetic image that has been registered thereto.

2. The method of claim 1, wherein the set of acquired MR image frames includes the myocardium.

3. The method of claim 1, wherein the set of MR image frames comprise T1 relaxation images and the MR recovery curve is a T1 recovery curve.

4. The method of claim 1, wherein each of the set of MR image frames is acquired at a substantially identical point within a cardiac cycle using cardiac gating.

5. The method of claim 1, wherein using prior knowledge pertaining to the MR recovery curve includes generating the synthetic images using a known signal model for the MR recovery curve.

6. The method of claim 1, wherein each of the synthetic images has similar contrast characteristics to the corresponding acquired MR images.

7. The method of claim 1, wherein registration of the acquired MR images to the corresponding synthetic images is performed using a partial-differential equation-based non-rigid registration algorithm.

8. The method of claim 1, wherein the generation of the synthetic images is performed using variational energy-minimization.

9. The method of claim 1, wherein the registration of each of the acquired MR images to the corresponding synthetic image is used to relate each of the original acquired MR images to a common spatial reference, which results in correcting the motion between original acquired MR images.

10. A method for performing motion compensation in a series of magnetic resonance (MR) images, comprising:

acquiring a set of T1 image frames spanning different points along an T1 recovery curve;

generating a motion-free synthetic image for each of the acquired T1 image frames; and

correcting for motion in the acquired T1 image frames using the generated motion-free synthetic images.

11. The method of claim 10, wherein the set of acquired T1 image frames includes the myocardium.

12. The method of claim 10, wherein the synthetic images are based on a known signal model for a T1 recovery curve.

13. The method of claim 10, wherein the synthetic images each have similar contrast characteristics to corresponding acquired T1 images.

14. The method of claim 10, wherein the synthetic images are spatially aligned.

15. The method of claim 10, wherein registration of the T1 images to the corresponding the synthetic images is performed using a partial-differential equation-based non-rigid registration algorithm.

16. The method of claim 10, wherein the generation of the synthetic images is performed using variational energy-minimization.

17. The method of claim 10, additionally comprising merging the synthetic images into one dataset according to relative location along the T1 recovery curve.

18. The method of claim 17, wherein merging the synthetic images relative location along the T1 recovery curve is performed in accordance with a Modified Look-Locker Inversion (MOLLI) recovery sequence technique.

19. A system for performing motion compensation in a series of magnetic resonance (MR) images, comprising:

an image receiving unit for receiving a set of MR image frames spanning different points along an MR recovery curve; and

an image processing unit for generating a motion-free synthetic image for each of the received MR image frames and registering each of the received MR images to the corresponding synthetic image.

20. The system of claim 19, wherein the synthetic images are generated using a known signal model for the MR recovery curve.