Automated registration of 3-D medical scans of similar anatomical structures

1. A method for registering images, comprising the steps of:

receiving a first image and a second image, said first image and said second image including data sets of at least two dimensions;

globally transforming one of said images via a rigid transformation technique;

locally transforming one of said images via an iterative motion tracking technique; and

outputting a registered image;

wherein said globally transforming includes the steps of:

constructing a first pyramid for said first image;

constructing a second pyramid for said second image;

determining a set of optimal scale factors;

performing a uniform scaling on said second image in accordance with said set of optimal scale factors to obtain a rescaled second image;

determining a set of optimal translation and rotation parameters; and

performing a transformation on said resealed second image based on said set of optimal translation and rotation parameters.

2. The method of claim 1 , further comprising the step of:

reconstructing said second pyramid after said uniform scaling step.

3. The method of claim 1 , wherein said determining a set of optimal scale factors includes the steps of:

determining a first voxel size in said first image;

determining a second voxel size in said second image; and

constructing a scaling matrix based on said first voxel size and said second voxel size.

4. The method of claim 1 , wherein said determining a set of optimal scale factors includes the steps of:

segmenting a first anatomical structure in said first image;

segmenting a second anatomical structure in said second image;

determining a first largest span in said first anatomical structure;

determining a second largest span in said second anatomical structure; and

constructing a scaling matrix based on said first largest span and said second largest span.

5. The method of claim 1 , wherein said determining a set of optimal translation and rotation parameters includes the steps of:

segmenting a first anatomical structure in said first image to obtain a first map;

segmenting a second anatomical structure in said second image to obtain a second map;

identifying a first set of identifiable points or contours in said first map and a second set of identifiable points or contours in said second map;

constructing a transformation matrix based on said first set of identifiable points or contours and said second set of identifiable points or contours; and

transforming said second image in accordance with said transformation matrix to obtain a transformed second image.

6. The method of claim 5 , further comprising the step of:

subsampling said first image and said second image based on said first map and said second map.

7. The method of claim 5 , further comprising the steps of:

measuring an error between said transformed second image and said first image;

comparing said error to a threshold error; and

repeating said identifying step if said error is greater than said threshold error.

8. The method of claim 5 , further comprising the steps of:

measuring an error between said transformed second image and said first image;

comparing said error to a previous error; and

repeating said identifying step if said error is greater than said previous error.

9. The method of claim 1 , wherein said locally transforming includes the steps of:

selecting a set of feature points in at least one of said images;

performing a feature tracking process on each of said set of feature points; and

performing a transformation weighting process on each point in at least one of said images that is not a feature point.

10. A method for registering images, comprising the steps of:

receiving a first image and a second image, said first image and said second image including data sets of at least two dimensions;

globally transforming one of said images via a rigid transformation technique;

locally transforming one of said images via an iterative motion tracking technique; and

outputting a registered image;

wherein said locally transforming includes the steps of:

selecting a set of feature points in at least one of said images;

performing a feature tracking process on each of said set of feature points; and

performing a transformation weighting process on each point in at least one of said images that is not a feature point.

11. The method of claim 10 wherein said globally transforming includes the steps of:

determining a set of optimal scale factors;

performing a uniform scaling on one of said images in accordance with said set of optimal scale factors to obtain a rescaled image;

determining a set of optimal translation and rotation parameters; and

performing a transformation on said rescaled image based on said set of optimal translation and rotation parameters.

12. The method of claim 11 , wherein said determining a set of optimal scale factors includes the steps of:

determining a first voxel size in said first image;

determining a second voxel size in said second image; and

constructing a scaling matrix based on said first voxel size and said second voxel size.

13. The method of claim 11 , wherein said determining a set of optimal scale factors includes the steps of:

segmenting a first anatomical structure in said first image;

segmenting a second anatomical structure in said second image;

determining a first largest span in said first anatomical structure;

determining a second largest span in said second anatomical structure; and

constructing a scaling matrix based on said first largest span and said second largest span.

14. The method of claim 11 , wherein said determining a set of optimal translation and rotation parameters includes the steps of:

segmenting a first anatomical structure in said first image to obtain a first map;

segmenting a second anatomical structure in said second image to obtain a second map;

identifying a first set of identifiable points or contours in said first map and a second set of identifiable points or contours in said second map;

constructing a transformation matrix based on said first set of identifiable points or contours and said second set of identifiable points or contours; and

transforming said second image in accordance with said transformation matrix to obtain a transformed second image.

15. A computer program product embodied in a computer readable medium for registering multiple images, comprising:

logic code for receiving a first image and a second image, said first image and said second image including data sets of at least two dimensions;

logic code for globally transforming at least one of said images via a rigid transformation technique;

logic code for locally transforming at least one of said images via an iterative motion tracking technique; and

logic code for outputting a registered image;

wherein said logic code for globally transforming includes:

logic code for constructing a first pyramid for said first image;

logic code for constructing a second pyramid for said second image;

logic code for determining a set of optimal scale factors based on said first pyramid and said second pyramid;

logic code for performing a uniform scaling on said second image in accordance with said set of optimal scale factors to obtain a rescaled second image;

logic code for determining a set of optimal translation and rotation parameters; and

logic code for performing a transformation on said rescaled second image based on said set of optimal translation and rotation parameters.

16. The computer program product of claim 15 , further comprising logic code for reconstructing said second pyramid after said uniform scaling.

17. The computer program product of claim 12 , wherein said logic code for determining a set of optimal scale factors includes:

logic code for determining a first voxel size in said first image;

logic code for determining a second voxel size in said second image; and

logic code for constructing a scaling matrix based on said first voxel size and said second voxel size.

18. The computer program product of claim 15 , wherein said logic code for determining a set of optimal scale factors includes:

logic code for segmenting a first anatomical structure in said first image;

logic code for segmenting a second anatomical structure in said second image;

logic code for determining a first largest span in said first anatomical structure;

logic code for determining a second largest span in said second anatomical structure; and

logic code for constructing a scaling matrix based on said first largest span and said second largest span.

19. The computer program product of claim 15 , wherein said logic code for determining a set of optimal translation and rotation parameters includes:

logic code for segmenting a first anatomical structure in said first image to obtain a first map;

logic code for segmenting a second anatomical structure in said second image to obtain a second map;

logic code for identifying a first set of identifiable points or contours in said first map and a second set of identifiable points or contours in said second map;

logic code for constructing a transformation matrix based on said first set of identifiable points or contours and said second set of identifiable points or contours; and

logic code for transforming said second image in accordance with said transformation matrix to obtain a transformed second image.

20. The computer program product of claim 19 , further comprising:

logic code for subsampling said first image and said second image based on said first map and said second map.

21. The computer program product of claim 19 , further comprising:

logic code for measuring an error between said transformed second image and said first image;

logic code for comparing said error to a threshold error; and

logic code for repeating said identifying step if said error is greater than said threshold error.

22. The computer program product of claim 19 , further comprising:

logic code for measuring an error between said transformed second image and said first image;

logic code for comparing said error to a previous error; and

logic code for repeating said identifying step if said error is greater than said previous error.

23. The computer program product of claim 15 , wherein said logic code for locally transforming at least one of said images includes:

logic code for selecting a set of feature points in at least one of said images;

logic code for performing a feature tracking process on each of said set of feature points; and

logic code for performing a transformation weighting process on each point in at least one of said images that is not a feature point.

24. A computer program product embodied in a computer readable medium for registering multiple images, comprising:

logic code for receiving a first image and a second image, said first image and said second image including data sets of at least two dimensions;

logic code for globally transforming at least one of said images via a rigid transformation technique;

logic code for locally transforming at least one of said images via an iterative motion tracking technique;

logic code for outputting a registered image;

wherein said logic code for locally transforming at least one of said images includes:

logic code for selecting a set of feature points in at least one of said images;

logic code for performing a feature tracking process on each of said set of feature points; and

logic code for performing a transformation weighting process on each point in at least one of said images that is not a feature point.

25. The computer program product of claim 24 wherein said logic code for globally transforming includes:

logic code for determining a set of optimal scale factors;

logic code for performing a uniform scaling on one of said images in accordance with said set of optimal scale factors to obtain a rescaled image;

logic code for determining a set of optimal translation and rotation parameters; and

logic code for performing a transformation on said rescaled image based on said set of optimal translation and rotation parameters.

26. The computer program product of claim 25 , wherein said logic code for determining a set of optimal scale factors includes:

logic code for determining a first voxel size in said first image;

logic code for determining a second voxel size in said second image; and

logic code for constructing a scaling matrix based on said first voxel size and said second voxel size.

27. The computer program product of claim 25 , wherein said logic code for determining a set of optimal scale factors includes:

logic code for segmenting a first anatomical structure in said first image;

logic code for segmenting a second anatomical structure in said second image;

logic code for determining a first largest span in said first anatomical structure;

logic code for determining a second largest span in said second anatomical structure; and

logic code for constructing a scaling matrix based on said first largest span and said second largest span.

28. The computer program product of claim 25 , wherein said logic code for determining a set of optimal translation and rotation parameters includes:

logic code for segmenting a first anatomical structure in said first image to obtain a first map;

logic code for segmenting a second anatomical structure in said second image to obtain a second map;

logic code for identifying a first set of identifiable points or contours in said first map and a second set of identifiable points or contours in said second map;

logic code for constructing a transformation matrix based on said first set of identifiable points or contours and said second set of identifiable points or contours; and

logic code for transforming said second image in accordance with said transformation matrix to obtain a transformed second image.