METHOD, SYSTEM AND SOFTWARE PRODUCT FOR PROVIDING EFFICIENT REGISTRATION OF VOLUMETRIC IMAGES

• US 20090097722A1
• Filed: 10/12/2007
• Published: 04/16/2009
• Est. Priority Date: 10/12/2007
• Status: Active Grant

• Current Assignee: Hyland Switzerland, Sarl (HSI Holdings II Incorporated)
• Original Assignee: Claron Technology Inc (Tungsten Automation Corp.)
• Inventors: Chandrashekara, Raghavendra, Dekel, Doron
• Granted Patent: US 8,218,905 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 15/10 Geometric effects
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration
• CPC Class Codes: G06T 7/33 using feature-based methods
• CPC Class Codes: Y10S 128/922 including image analysis

Abstract

The invention relates to a method, system and computer program product for registering 3D image data. It comprises (a) receiving a first 3D image and a second 3D image; (b) determining a rendering transform for applying to each of the first 3D image and the second 3D image; (c) applying the rendering transform to the first 3D image to provide a first 2D projection and to the second 3D image to provide a second 2D projection; and (d) determining an elastic registration for mapping locations of the first 2D projection to homologous locations in the second 2D projection.

Claims

1. A method for registering 3D image data, the method comprising;

a) receiving a first 3D image and a second 3D image;

b) determining a rendering transform for applying to each of the first 3D image and the second 3D image;

c) applying the rendering transform to i) the first 3D image to provide a first 2D projection and ii) the second 3D image to provide a second 2D projection; and

,

d) determining an elastic registration for mapping locations of the first 2D projection to homologous locations in the second 2D projection.

2. The method as defined in claim 1 wherein b) comprises

i) selecting a first structure in the first 3D image and a second structure in the second 3D image, the second structure being homologous to the first structure;

and

ii) determining the rendering transform such that the first 2D projection comprises the first structure, and the second 2D projection comprises the second structure and is similarly oriented to the first 2D projection.

3. The method as defined in claim 2 wherein d) comprises

i) determining the elastic registration to map a location of the first structure in the first 2D projection to a location of the second structure in the second 2D projection;

and then,

ii) applying the elastic registration to map locations in the first 2D projection other than the location of the first structure in the first 2D projection to locations in the second 2D projection other than the location of the second structure in the second 2D projection.

4. The method as defined in claim 3 wherein the first structure and the second structure are anatomical structures.

5. The method as defined in claim 3 wherein the first structure and the second structure are anatomical structures consisting of at least one of bones, organs, and blood vessels.

6. The method as defined in claim 3 wherein

b) comprises determining a plurality of rendering transforms for applying to each of the first 3D image and the second 3D image;

c) comprises applying the plurality of rendering transforms to i) the first 3D image to provide a plurality of first 2D projections and ii) the second 3D image to provide a plurality of second 2D projections; and

,

d) comprises determining a plurality of elastic registrations for mapping locations of the plurality of first 2D projections to homologous locations in the plurality of second 2D projections.

7. The method as defined in claim 6 wherein d) comprises determining the plurality of elastic registrations based partly on a known relation between the plurality of rendering transforms.

8. The method as defined in claim 7 wherein each elastic registration in the plurality of elastic registrations is defined by an associated plurality of parameters and d) further comprises iteratively determining the associated plurality of parameters for each elastic registration in the plurality of elastic registrations based on a prior iteration of the associated plurality of parameters defining that elastic registration and a prior iteration of a parallel associated plurality of parameters defining a different elastic registration in the plurality of elastic registrations.

9. The method as defined in claim 8 wherein,

for each elastic registration in the plurality of elastic registrations, the associated plurality of parameters comprise an associated scaling parameter;

and,

in d), the associated scaling parameters of the plurality of elastic registrations are iteratively determined to converge together.

10. The method as defined in claim 6 wherein

each second 2D projection of the plurality of second 2D projections comprises a contour surrounding an area of interest;

and

in d), the plurality of elastic registrations are operable to map the contours of the second 2D projections to homologous contours in the plurality of first 2D projections.

11. The method as defined in claim 10 further comprising generating a contour extrusion intersection sub-volume using the contour for each first 2D projection of the plurality of first 2D projections.

12. The method as defined in claim 10 wherein

the first structure and the second structure comprise skeletal structure;

the contour in the second 3D image is selected to surround specific soft tissue based on a location of the specific soft tissue relative to the skeletal structure of the second 3D image such that the associated mapped projection contour for each first 2D projection of the plurality of first 2D projections surrounds the specific soft tissue of a first patient.

13. The method as defined in claim 2 further comprising

for each point in the first structure of the first 2D projection, storing 3D location information for mapping that point back to a corresponding point in the first 3D image;

and,

for each point in the second structure of the second 2D projection, storing 3D location information for mapping that point back to a corresponding point in the second 3D image.

14. The method as defined in claim 13 further comprising determining a 3D elastic registration based on the elastic registration determined in d).

15. The method as defined in claim 5 wherein

the first structure comprises a first anatomical surface;

the second structure comprises a second anatomical surface;

the method further comprises, for each point of a first plurality of points in the first anatomical structure of the first 2D projection, deriving a first surface parameter from the first anatomical surface of the first anatomical structure;

the method further comprises, for each point of a second plurality of points in the second anatomical structure of the second 2D projection, deriving a second surface parameter from the second anatomical surface of the second anatomical structure; and

d) comprises, for each point in the first plurality of points and for each point in the second plurality of points determining the elastic registration based on the first surface parameter and the second surface parameter.

16. The method as defined in claim 15 wherein

the method further comprises, for each point of the first plurality of points deriving a plurality of first surface parameters including the first surface parameter from the first anatomical surface of the first anatomical structure;

the method further comprises, for each point of the second plurality of points deriving a plurality of second surface parameters including the second surface parameter, from the second anatomical surface of the first anatomical structure; and

d) comprises, for each point in the first plurality of points and for each point in the second plurality of points determining the elastic registration based on the plurality of first surface parameters and the plurality of second surface parameters.

17. The method as defined in claim 6 wherein

each second 2D projection of the plurality of second 2D projections comprises a marked position within an area of interest;

in d), the plurality of elastic registrations are operable to map the marked positions of the second 2D projections to homologous locations in the plurality of first 2D projections;

the method further comprises e) generating a seed point from the intersection in 3D of the homologous locations in the plurality of first 2D projections; and

the method further comprises f) using the seed point as a starting point for a segmentation algorithm based on region growing.

18. The method of claim 5 wherein

the first 2D projection has a first longitudinal axis and a first lateral axis;

the second 2D projection has a second longitudinal axis and a second lateral axis where the second longitudinal axis is divided into a plurality of longitudinal increments; and

d) comprises

for each longitudinal increment in the plurality of longitudinal increments, generating a candidate mapping defined by a plurality of mapping parameters for mapping locations of the first 2D projection to homologous locations in the second 2D projection where generating the candidate mapping comprises

aligning the first longitudinal axis with the second longitudinal axis;

shifting the first 2D projection along the second longitudinal axis to the longitudinal increment such that a first overlap region of the first 2D projection overlaps with a second overlap region of the second 2D; and

selecting the plurality of mapping parameters to maximize a similarity value where the similarity value is a measure of how similar the first overlap region is to the second overlap region; and

determining the elastic registration based on the candidate mapping with a highest similarity value.

19. The method of claim 5 wherein

the first 2D projection has a first longitudinal axis and a first lateral axis;

the second 2D projection has a second longitudinal axis and a second lateral axis where the second longitudinal axis is divided into a plurality of longitudinal increments; and

d) comprises, for each longitudinal increment in the plurality of longitudinal increments,

i) generating a candidate mapping defined by a plurality of mapping parameters for mapping locations of the first 2D projection to homologous locations in the second 2D projection where generating the candidate mapping comprises

ii) defining a first region along the first longitudinal axis of the first 2D projection;

iii) based on the longitudinal increment, defining a second region along the second longitudinal axis of the second 2D projection;

iv) selecting the plurality of mapping parameters to maximize a similarity value where the maximized similarity value is a measure of how similar the first region is to the second region;

after i), ii), iii) and iv), for each longitudinal increment in the plurality of longitudinal increments, determining the elastic registration based on the candidate mapping with a highest similarity value in a plurality of similarity values, wherein the plurality of similarity values comprises the maximized similarity value for each longitudinal increment in the plurality of longitudinal increments.

20. The method of claim 19 wherein the mapping parameters include a longitudinal scaling parameter for adjusting scaling of the first 2D projection along the second longitudinal axis and a lateral scaling parameter for adjusting scaling of the first 2D projection along the second lateral axis.

21. The method of claim 5 wherein d) comprises

determining whether the first 2D projection exceeds a specified threshold size and where the first 2D projection exceeds the specified threshold size, dividing the first 2D projection into a first region and a second region where the first region and the second region are not co-extensive;

determining a first elastic registration for mapping locations of the first region of the first 2D projection to homologous locations in the second 2D projection; and

determining a second elastic registration for mapping locations of the second region of the first 2D projection to homologous locations in the second 2D projection where the second elastic registration is based on the first elastic registration.

22. The method of claim 19 wherein

the first 2D projection has a first resolution defined by a first number of points in the first 2D projection

the second 2D projection has a second resolution defined by a second number of points in the second 2D projection;

the method further comprises reducing the first resolution of the first 2D projection by averaging each nxn block of points prior to determining the elastic registration wherein n is any integer greater than one; and

the method further comprises reducing the second resolution of the second 2D projection by averaging each nxn block of points prior to determining the elastic registration wherein n is any integer greater than one.

23. A system for registering 3D image data comprising:

a processor;

a memory for storing a first 3D image, a second 3D image, and means for configuring the processor to perform the steps of

a) determining a rendering transform for applying to each of the first 3D image and the second 3D image;

b) applying the rendering transform to i) the first 3D image to provide a first 2D projection and ii) the second 3D image to provide a second 2D projection; and

c) determining an elastic registration for mapping locations of the first 2D projection to homologous locations in the second 2D projection.

24. A computer program product for use on a computer system to register 3D image data, the computer program product comprising:

a recording medium;

means recorded on the medium for instructing the computer system to perform the steps of;

a) receiving a first 3D image and a second 3D image;

b) determining a rendering transform for applying to each of the first 3D image and the second 3D image;

c) applying the rendering transform to i) the first 3D image to provide a first 2D projection and ii) the second 3D image to provide a second 2D projection; and

,

d) determining an elastic registration for mapping locations of the first 2D projection to homologous locations in the second 2D projection.