MEDICAL IMAGE ANALYSIS SYSTEM USING N-WAY BELIEF PROPAGATION FOR ANATOMICAL IMAGES SUBJECT TO DEFORMATION AND RELATED METHODS

• US 20110081055A1
• Filed: 10/02/2009
• Published: 04/07/2011
• Est. Priority Date: 10/02/2009
• Status: Abandoned Application

• Current Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Original Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Inventors: Jackson, Jeremy D., Burrell, Lauren S., Culp, Timothy R., Bell, David M.
• Application Number:
  US12/572,614
• Publication Number:
  US 20110081055A1
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/35 using statistical methods

Abstract

A medical image analysis system is for first and second anatomical image data of a same body area and subject to deformation, with the first and second anatomical image data including respective first and second sets of voxels. The medical image analysis system may include a processor cooperating with a memory and configured to generate a plurality of cost arrays, with each cost array based upon probabilities of a subset of voxels of the second anatomical image data matching voxels of the first anatomical image data. The processor may also solve each cost array using three-dimensional, N-way belief propagation to thereby generate a deformation vector array between the first and second anatomical image data, where N is an integer greater than or equal to six.

Claims

1. A medical image analysis system for first and second anatomical image data of a same body area and subject to deformation, the first and second anatomical image data comprising respective first and second sets of voxels, the medical image analysis system comprising:

a memory; and

a processor cooperating with said memory and configured to

generate a plurality of cost arrays, each cost array based upon probabilities of a subset of voxels of the second anatomical image data matching voxels of the first anatomical image data, and

solve each cost array using three-dimensional, N-way belief propagation to thereby generate a deformation vector array between the first and second anatomical image data, where N is an integer greater than or equal to six.

2. The medical image analysis system of claim 1 wherein N is less than or equal to twenty-six.

3. The medical image analysis system of claim 1 wherein N is fourteen.

4. The medical image analysis system of claim 1 wherein N is eighteen.

5. The medical image analysis system of claim 1 wherein said processor is also configured to register the first and second anatomical image data based upon the deformation vector array to thereby generate composite anatomical image data.

6. The medical image analysis system of claim 5 wherein said processor is also configured to determine changes between the first and second anatomical image data as part of the composite anatomical image data.

7. The medical image analysis system of claim 6 further comprising a display coupled to said processor;

and wherein said processor is also configured to generate a composite image on said display based upon the composite anatomical image data.

8. The medical image analysis system of claim 1 wherein the first anatomical image data includes a target treatment area therein;

and wherein said processor is further configured to map the target treatment area into the second anatomical image data based upon the deformation vector array.

9. The medical image analysis system of claim 1 wherein the first and second anatomical image data have different resolutions;

and wherein said processor is further configured to resample at least one of the first and second anatomical image data to a common resolution.

10. The medical image analysis system of claim 1 wherein each cost array is a three-dimensional array of three-dimensional sub-arrays of scalar cost values.

11. The medical image analysis system of claim 1 said processor is further configured to solve each cost area by at least:

generating the N belief messages for each cost message, each belief message being based upon another cost message and N−

1 belief messages associated therewith;

adding each cost message with the N belief messages associated therewith to generate a cost-belief sum; and

forming a vector of the deformation array based upon a smallest cost-belief sum of each cost array.

12. A medical image analysis system for first and second anatomical image data of a same body area and subject to deformation, the first and second anatomical image data comprising respective first and second sets of voxels, the medical image analysis system comprising:

a memory; and

a processor cooperating with said memory and configured to

generate a plurality of cost arrays, each cost array based upon probabilities of a subset of voxels of the second anatomical image data matching voxels of the first anatomical image data,

solve each cost array using three-dimensional, N-way belief propagation to thereby generate a deformation vector array between the first and second anatomical image data, where N is an integer greater than or equal to six and less than or equal to twenty-six, and

register the first and second anatomical image data based upon the deformation vector array to thereby generate composite anatomical image data.

13. The medical image analysis system of claim 12 wherein, said processor is also configured to determine changes between the first and second anatomical image data as part of the composite anatomical image data.

14. The medical image analysis system of claim 13 further comprising a display coupled to said processor;

and wherein said processor is also configured to generate a composite image on said display based upon the composite anatomical image data.

15. The medical image analysis system of claim 12 wherein the first anatomical image data includes a target treatment area therein;

and wherein said processor is further configured to map the target treatment area into the second anatomical image data based upon the deformation vector array.

16. The medical image analysis system of claim 12 wherein the first and second anatomical image data have different resolutions;

and wherein said processor is further configured to resample at least one of the first and second anatomical image data to a common resolution.

17. An image analysis system for first and second image data of a same area and subject to deformation, the first and second image data comprising respective first and second sets of voxels, the image analysis system comprising:

a memory; and

a processor cooperating with said memory and configured to

generate a plurality of cost arrays, each cost array based upon probabilities of a subset of voxels of the second image data matching voxels of the first image data, and

solve each cost array using three-dimensional, N-way belief propagation to thereby generate a deformation vector array between the first and second image data, where N is an integer greater than or equal to six.

18. The image analysis system of claim 17 wherein N is fourteen.

19. The image analysis system of claim 17 wherein said processor is also configured to register the first and second image data based upon the deformation vector array to thereby generate composite image data;

and wherein said processor is also configured to determine changes between the first and second image data as part of the composite image data.

20. The image analysis system of claim 19 further comprising a display coupled to said processor;

and wherein said processor is also configured to generate a composite image on said display based upon the composite image data.

21. A method of operating a medical image analysis system for first and second anatomical image data of a same body area and subject to deformation, the first and second anatomical image data comprising respective first and second sets of voxels, the method comprising:

generating, using a processor, a plurality of cost arrays, each cost array based upon probabilities of a subset of voxels of the second anatomical image data matching voxels of the first anatomical image data; and

solving, using the processor, each cost array using three-dimensional, N-way belief propagation to thereby generate a deformation vector array between the first and second anatomical image data, where N is an integer greater than or equal to six.

22. The method of claim 21 wherein N is less than or equal to twenty-six.

23. The method of claim 21 wherein N is fourteen.

24. The method of claim 21 wherein N is eighteen.

25. The method of claim 21 further comprising registering, using the processor, the first and second anatomical image data based upon the deformation vector array to thereby generate composite anatomical image data.

26. The method of claim 25 further comprising determining, using the processor, changes between the first and second anatomical image data as part of the composite anatomical image data;

and further comprising generating, using the processor, a composite image on a display based upon the composite anatomical image data.

27. The method of claim 21 wherein the first anatomical image data includes a target treatment area therein;

and further comprising mapping, using the processor, the target treatment area into the second anatomical image data based upon the deformation vector array.

28. The method of claim 21 wherein the first and second anatomical image data have different resolutions;

and further comprising resampling, using the processor, at least one of the first and second anatomical image data to a common resolution.