Feature-based composing for 3D MR angiography images

• US 20060052686A1
• Filed: 07/20/2005
• Published: 03/09/2006
• Est. Priority Date: 08/24/2004
• Status: Active Grant

• Current Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Zhang, Li, Sofka, Michal, Schafer, Ulf
• Granted Patent: US 8,265,354 B2
• Time in Patent Office: Days
• US Class Current: 600/407
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/32 using correlation-based methods

Abstract

Multiple volumes that are to be aligned to form a single volume are processed. The system and method use an equalization step, a edge detection step and a correlation step to determine the overlapping positions between the first volume and the second volume of a volume pair having a maximum correlation value, and the best alignment of the first volume and the second volume of the volume pair is determined by the correlation value. A coarse correlation step using lower resolution volumes can be performed first followed by a fine correlation step using higher resolution images to save processing time. Initial preprocessing steps such as volume shearing can be performed. Equalization involves equalizing voxel size and edge detection can be performed using a Canny edge detector.

Claims

10. A system for aligning a plurality of volumes from a patient, comprising:

means for equalizing the plurality of volumes with the highest resolution of the plurality of volumes;

means for detecting edges in a first and a second of the plurality of volumes to form a first and a second edge map, respectively;

means for determining the correlation of the first edge map to the second edge map at a plurality of overlapping positions to determine the best alignment of the first volume and the second volume.

1. A method of aligning a plurality of volumes from a patient, comprising:

equalizing the plurality of volumes with the highest resolution of the plurality of volumes;

detecting edges in a first and a second of the plurality of volumes to form a first and a second edge map, respectively;

determining the correlation of the first edge map to the second edge map at a plurality of overlapping positions to determine the best alignment of the first volume and the second volume.

2. The method as claimed in claim 1, further comprising:

detetecting edges in the remaining plurality of volumes to form additional edge maps; and

determining the correlation of adjacent edge maps to determine the best alignment of the remaining plurality of volumes.

3. The method as claimed in claim 1, further comprising aligning the first volume and the second volume based on the correlation step to form a single image.

4. The method as claimed in claim 1, wherein the best alignment between the first volume and the second volume is found when the correlation of the plurality of overlapping positions is maximized.

5. The method as claimed in claim 1, wherein the correlating step is determined by maximizing the output of the formula:

6. The method as claimed in claim 1, wherein the step of equalizing equalizes the size of voxels in all the volumes.

7. The method as claimed in claim 1, wherein the step of detecting edges uses a Canny edge detector.

8. The method as claimed in claim 1, further comprising:

forming the first and second edge maps by down-sampling edge maps derived from volumes having full resolution, whereby the first and second edge maps represent a coarse resolution;

selecting an optimized alignment on the coarse resolution edge maps by maximizing coarse correlation values; and

determining an optimized alignment on the original resolution edge maps by maximizing fine correlation values around the optimized alignment on the coarse resolution.

9. The method as claimed in claim 1, wherein the plurality of volumes are obtained from a magnetic resonance imaging device.

11. The system as claimed in claim 10, further comprising:

means for detecting edges in the remaining plurality of volumes to form additional edge maps; and

means for determining the correlation of adjacent edge maps to determine the best alignment of the remaining plurality of volumes.

12. The system as claimed in claim 10, further comprising means for aligning the first volume and the second volume based on the correlation step to form a single image.

13. The system as claimed in claim 10, wherein the best alignment between the first volume and the second volume is found when the correlation of the plurality of overlapping positions is maximized.

14. The system as claimed in claim 10, wherein the means for determining the correlation maximizes the output of the formula:

15. The system as claimed in claim 10, wherein the means for equalizing equalizes the size of voxels in all the volumes.

16. The system as claimed in claim 10, wherein the means for detecting edges uses a Canny edge detector.

17. The system as claimed in claim 10, further comprising:

means for forming the first and second edge maps by down-sampling edge maps derived from volumes having full resolution, whereby the first and second edge maps represent a coarse resolution;

means for selecting an optimized alignment on the coarse resolution edge maps by maximizing coarse correlation values; and

means for determining an optimized alignment on the original resolution edge maps by maximizing fine correlation values.

18. The system as claimed in claim 10, wherein the plurality of volumes are obtained from a magnetic resonance imaging device.

12-1. The system as claimed in claim 10, further comprising means for aligning the remaining volumes based on the correlation step to form a single image.

19. A system for aligning a first volume of image data and a second volume of image data from a single patient, comprising:

a device for imaging a body part to form the first volume and the second volume;

a processor that equalizes data from the first volume and data from the second volume, that detects edges in the first volume to from a first edge map, that detects edges in the second volume to form a second edge map, that performs determines the correlation between the first edge map and the second edge map at a plurality of overlapping positions between the first edge map and the second edge map, and that determines the best alignment of the first volume and the second volume based on the correlation; and

means for displaying a single image derived from the first and second volumes.

20. The system as claimed in claim 19, wherein a plurality of volumes from a single patient are processed and the best alignment of the plurality of volumes is determined.