Method and apparatus for three-dimensional reconstruction of coronary vessels from angiographic images

• US 6,047,080 A
• Filed: 06/19/1996
• Issued: 04/04/2000
• Est. Priority Date: 06/19/1996
• Status: Expired due to Term

• Current Assignee: ARCH Development Corporation (University of Chicago)
• Original Assignee: ARCH Development Corporation (University of Chicago)
• Inventors: Carroll, John D., Metz, Charles E., Hoffmann, Kenneth R., Chen, Shiuh-Yung James
• Primary Examiner(s): Chang, Jon
• Assistant Examiner(s): Patel, Jayanti K.
• Application Number:
  US08/665,836
• Time in Patent Office: 1,385 Days
• Field of Search: 382/128-134, 382/262, 378/4, 378/901, 378/9, 378/8, 128/653.1, 434/272, 623/1, 600/483
• US Class Current: 382/128
• CPC Class Codes: G06T 11/006 Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
• CPC Class Codes: G06T 2211/404 Angiography

Abstract

A method for in-room computer reconstruction of a three-dimensional (3-D) coronary arterial tree from routine biplane angiograms acquired at arbitrary angles and without using calibration objects. The method includes eight major steps: (1) acquiring biplane projection images of the coronary structure, (2) detecting, segmenting and identifying vessel centerlines and constructing a vessel hierarchy representation, (3) calculating bifurcation points and measuring vessel diameters in coronary angiograms if biplane imaging geometry data is not available, (4) determining biplane imaging parameters in terms of a rotation matrix R and a unit translation vector t based on the identified bifurcation points, (5) retrieving imaging parameters if biplane imaging geometry data is already known, (6) establishing the centerline correspondences of the two-dimensional arterial representations, (7) calculating and recovering the 3-D coronary arterial tree based on the calculated biplane imaging parameters, correspondences of vessel centerlines, and vessel diameters, and (8) rendering the reconstructed 3-D coronary tree and estimating an optimal view of the vasculature to minimize vessel overlap and vessel foreshortening.

Claims

1. A method for three-dimensional reconstruction of a target object from two-dimensional images, said target object having a plurality of branch-like vessels, the method comprising the steps of:

a) placing the target object in a position to be scanned by an imaging system, said imaging system having a plurality of imaging portions;

b) acquiring a plurality of projection images of the target object, each imaging portion providing a projection image of the target object, each imaging portion disposed at an unknown orientation relative to the other imaging portions;

c) identifying two-dimensional vessel centerlines for a predetermined number of the vessels in each of the projection images;

d) creating a vessel hierarchy data structure for each projection image, said data structure including the identified two-dimensional vessel centerlines defined by a plurality of data points in the vessel hierarchy data structure;

e) calculating a predetermined number of bifurcation points for each projection image by traversing the corresponding vessel hierarchy data structure, said bifurcation points defined by intersections of the two-dimensional vessel centerlines;

f) determining a transformation in the form of a rotation matrix and a translation vector utilizing non-linear constrained minimization techniques and the bifurcation points corresponding to each of the projections images, said non-linear constrained minimization techniques minimizing the square of the distance between the bifurcation points and projections of calculated three-dimensional points, said rotation matrix and said translation vector representing imaging parameters corresponding to the orientation of each imaging portion relative to the other imaging portions of the imaging system;

g) utilizing the data points and the transformation to establish a correspondence between the two-dimensional vessel centerlines corresponding to each of the projection images such that each data point corresponding to one projection image is linked to a data point corresponding to the other projection images, said linked data points representing an identical location in the vessel of the target object;

h) calculating three-dimensional vessel centerlines utilizing the two-dimensional vessel centerlines and the correspondence between the data points of the two-dimensional vessel centerlines; and

i) reconstructing a three-dimensional visual representation of the target object based on the three-dimensional vessel centerlines and diameters of each vessel estimated along the three-dimensional centerline of each vessel.

2. The method of claim 1 wherein the two-dimensional images are two-dimensional angiographic projection images.

3. The method of claim 1 wherein the target object is scanned substantially simultaneously by the plurality of imaging portions of the imaging system.

4. The method of claim 3 wherein a moving target object experiences substantially no movement during said substantially simultaneous scanning such that the projection images provided by the plurality of imaging portions represent images of the target object acquired substantially at a same point in time.

5. The method of claim 1 wherein the imaging system is a biplane imaging system having two imaging portions, said imaging portions configured to simultaneously scan the target object and provide biplane projection images of the target object.

6. The method of claim 1 wherein the imaging system is an X-ray based projection imaging system.

7. The method of claim 1 wherein the imaging system is selected from the group of non-orthogonal imaging systems consisting of X-ray imaging systems, particle-beam imaging systems, radar imaging systems, ultrasound imaging systems, photographic imaging systems, and laser imaging systems.

8. The method of claim 1 wherein the step of identifying the two-dimensional vessel centerlines includes the steps of determining a maximum vessel diameter at a beginning portion of the vessel and determining a minimum vessel diameter at an ending portion of the vessel.

9. The method of claim 1 wherein the step of identifying the two-dimensional vessel centerlines is performed by a human operator.

10. The method of claim 1 wherein the step of identifying the two-dimensional vessel centerlines includes the step of identifying at least six vessels in each projection image.

11. The method of claim 10 wherein the step of identifying at least six vessels in each projection image permits five bifurcation points to be calculated.

12. The method of claim 1 wherein the predetermined number of bifurcation points calculated for each projection image is at least five bifurcation points.

13. The method of claim 1 wherein the step of reconstructing the visual representation of the target object includes the steps of modeling the target object by calculating estimated vessel diameters along the three-dimensional centerline of each vessel based on the minimum and maximum diameter and a predetermined change in diameter per unit length along the vessel.

14. The method of claim 1 wherein the step of reconstructing a visual representation of the target object further includes the steps of:

a) providing an optimal three-dimensional visual representation of the target object such that vessel overlap and vessel foreshortening are minimized in the visual representation by rotating the three-dimensional visual representation in at least one of three dimensions;

b) calculating image parameters corresponding to the rotated three-dimensional visual representation; and

c) providing said calculated parameters to the imaging system to permit the imaging system to further scan the target object such that optimal projection images of the target object are produced.

15. The method of claim 1, wherein said imaging system has an isocenter, and wherein said non-linear constrained minimization techniques are constrained by said isocenter.

16. A method for three-dimensional reconstruction of a target object from two-dimensional images, said target object having a plurality of branch-like vessels, the method comprising the steps of:

a) placing the target object in a position to be scanned by a biplane imaging system, said biplane imaging system having first and second imaging portions;

b) acquiring biplane projection images of the target object, each imaging portion providing a biplane projection image of the target object, each imaging portion disposed at an unknown orientation relative to the other imaging portion;

c) identifying two-dimensional vessel centerlines for a predetermined number of the vessels in each of the biplane projection images;

d) creating a vessel hierarchy data structure for each biplane projection image, said data structure including the identified two-dimensional vessel centerlines defined by a plurality of data points in the vessel hierarchy data structure;

e) calculating a predetermined number of bifurcation points for each biplane projection image by traversing the corresponding vessel hierarchy data structure, said bifurcation points defined by intersections of the two-dimensional vessel centerlines;

f) determining a transformation in the form of a rotation matrix and a translation vector utilizing non-linear constrained minimization techniques and the bifurcation points corresponding to each of the biplane projections images, said non-linear constrained minimization techniques minimizing the square of the distance between the bifurcation points and projections of calculated three-dimensional points, said rotation matrix and said translation vector representing biplane imaging parameters corresponding to the orientation of each imaging portion relative to the other imaging portion of the biplane imaging system;

g) utilizing the data points and the transformation to establish a correspondence between the two-dimensional vessel centerlines corresponding to each of the biplane projection images such that each data point corresponding to one biplane projection image is linked to a data point corresponding to the other biplane projection image, said linked data points representing an identical location in the vessel of the target object;

h) calculating three-dimensional vessel centerlines utilizing the two-dimensional vessel centerlines and the correspondence between the data points of the two-dimensional vessel centerlines; and

i) reconstructing a three-dimensional visual representation of the target object based on the three-dimensional vessel centerlines and diameters of each vessel estimated along the three-dimensional centerline of each vessel.

17. The method of claim 16 wherein the two-dimensional images are two-dimensional angiographic projection images.

18. The method of claim 16 wherein the target object is scanned substantially simultaneously by the plurality of imaging portions of the biplane imaging system.

19. The method of claim 18 wherein a moving target object experiences substantially no movement during said substantially simultaneous scanning such that the projection images provided by the plurality of imaging portions represent images of the target object acquired substantially at a same point in time.

20. The method of claim 16 wherein the step of reconstructing a visual representation of the target object further includes the steps of:

a) providing an optimal three-dimensional visual representation of the target object such that vessel overlap and vessel foreshortening are minimized in the visual representation by rotating the three-dimensional visual representation in at least one of three dimensions;

b) calculating image parameters corresponding to the rotated three-dimensional visual representation; and

c) providing said calculated parameters to the biplane imaging system to permit the imaging system to further scan the target object such that optimal projection images of the target object are produced.

21. The method of claim 16, wherein said biplane imaging system has a first isocenter corresponding to said first imaging portion and a second isocenter corresponding to said second imaging portion, and wherein said non-linear constrained minimization techniques are constrained by said first and second isocenters.

22. A method for three-dimensional reconstruction of a target object from two-dimensional images, said target object having a plurality of branch-like vessels, the method comprising the steps of:

a) placing the target object in a position to be scanned by a single-plane system, said imaging system having one imaging portion;

b) acquiring projection images of the target object, the imaging portion providing a plurality of projection images of the target object produced at different times, each projection image produced during an identical phase of a cardiac cycle of the target object, the imaging portion corresponding to one of the plurality of projection images disposed at an unknown orientation relative to the imaging portion corresponding to the others of the plurality of projection images;

c) identifying two-dimensional vessel centerlines for a predetermined number of the vessels in each of the projection images;

d) creating a vessel hierarchy data structure for each projection image, said data structure including the identified two-dimensional vessel centerlines defined by a plurality of data points in the vessel hierarchy data structure;

e) calculating a predetermined number of bifurcation points for each projection image by traversing the corresponding vessel hierarchy data structure, said bifurcation points defined by intersections of the two-dimensional vessel centerlines;

f) determining a transformation in the form of a rotation matrix and a translation vector utilizing non-linear constrained minimization techniques and the bifurcation points corresponding to each of the projections images, said non-linear constrained minimization techniques minimizing the square of the distance between the bifurcation points and projections of calculated three-dimensional points, said rotation matrix and said translation vector representing imaging parameters corresponding to the relative orientations of the imaging portion corresponding to the plurality of projection images;

g) utilizing the data points and the transformation to establish a correspondence between the two-dimensional vessel centerlines corresponding to each of the projection images such that each data point corresponding to one projection image is linked to a data point corresponding to the other projection images, said linked data points representing an identical location in the vessel of the target object;

h) calculating three-dimensional vessel centerlines utilizing the two-dimensional vessel centerlines and the correspondence between the data points of the two-dimensional vessel centerlines; and

i) reconstructing a three-dimensional visual representation of the target object based on the three-dimensional vessel centerlines and diameters of each vessel estimated along the three-dimensional centerline of each vessel.

23. The method of claim 22, wherein said imaging system has an isocenter, and wherein said non-linear constrained minimization techniques are constrained by said isocenter.