Registration of three dimensional image data with patient in a projection imaging system

• US 20060269165A1
• Filed: 05/05/2006
• Published: 11/30/2006
• Est. Priority Date: 05/06/2005
• Status: Active Grant

• Current Assignee: Stereotaxis, Inc.
• Original Assignee: Stereotaxis, Inc.
• Inventors: Viswanathan, Raju R.
• Granted Patent: US 7,623,736 B2
• Time in Patent Office: Days
• US Class Current: 382/293
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/33 using feature-based methods

Abstract

A method for determining a translation of a three-dimensional pre-operative image data set to obtain a registration of the three-dimensional image data with a patient positioned in a projection imaging system. In one embodiment the user identifies an initial three-dimensional organ center from projections and extreme contour landmark points of the object on a set of projections. A set of contour points for the image object in each of a plurality of three-dimensional cross-section planes; is obtained and the points projecting nearest to the user-identified landmark points are selected. A three-dimensional grid having a predetermined number of intervals at a predetermined interval spacing centered at the user-identified organ center is defined. The three-dimensional image data contour points as centered onto each grid point are projected for evaluation and selection of the grid point leading to contour points projecting nearest to the user-identified landmark points. This selection leads to the iterative definition of a series of improved estimated three-dimensional organ centers, and associated translation vectors. Registration of a three dimensional image data to the patient positioned in a projection imaging system will allow, among other things, overlay of a visual representation of a pre-operative image object onto a projection image plane that can serve as a visual tool and a surgical navigation aid. In particular, the position and orientation of a medical device can be shown with respect to the three-dimensional image data and thus enable quicker, safer, and less invasive navigation of the medical device to and within an organ of interest.

Claims

1. A method for registration of a previously acquired three-dimensional image data set of an organ of interest in a patient, to the patient positioned in a projection imaging system, comprising the steps of:

(a) identifying landmark points on a set of projections acquired in the projection imaging system;

(b) identifying surface contour points for the organ of interest in the three-dimensional image;

(c) projecting the surface contour points of step (b) in the geometry of the projection imaging system;

(d) defining as a registration figure-of-merit a distance between projected contour points of step (c) and landmark points of step (a); and

(e) calculating a translation vector that when applied to the three-dimensional image data set minimizes the registration figure-of-merit of step (d),

whereby registration of the previously acquired three-dimensional data set of an organ of interest to the patient positioned in a projection imaging system is achieved with a degree of efficiency by applying the translation vector of step (d) to the three-dimensional data set.

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

3. The method of claim 1, wherein the step of identifying landmark points is performed by the user.

4. The method of claim 1, wherein the step of identifying surface contour points of an organ of interest is performed automatically by segmentation of the three-dimensional data set.

5. The method of claim 1, wherein the figure-of-merit of step (d) further comprises the sum of the distances between the landmark points and the projection of the contour points that project closest to the landmark points.

6. The method of claim 1, wherein the translation vector is calculated iteratively by centering the three-dimensional data set on each of a set of grid points in turn and retaining as the new organ center estimate the grid point that minimizes the figure-of-merit.

7. The method of claim 6, wherein the grid of points is iteratively refined over a number of iterations by defining finer grid parameters and centering at each iteration the new grid onto the most recently obtained organ center estimate.

8. A method for registration of a previously acquired three-dimensional image data set of an organ of interest in a patient, to the patient positioned in a projection imaging system, comprising the steps of:

(a) identifying an initial three-dimensional center point estimate for the three-dimensional organ of interest from projections acquired in the projection imaging system;

(b) identifying at least two extreme landmark points on a set of at least one projection acquired in the projection imaging system and defining a set of landmark-associated projections;

(c) defining a plurality of cross-section planes with respect to the three-dimensional data, and automatically obtaining by segmentation of the three-dimensional image data a set of contour points for a plurality of lines on each of the plurality of cross-section planes;

(d) defining a plurality of three-dimensional grid points for an initial set of grid parameters, and centering the three-dimensional grid on the initial estimate of the organ center obtained in step (a);

(e) centering the three-dimensional image data set on a point of the grid defined in step (d) and for each of the projection in the projection set of step (b), performing a projection of every contour point in a first subset of the cross-section plane set obtained in step (c), and selecting from the cross-section plane subset the extreme cross-section plane with the contour point projecting nearest to the user-identified landmark point of step (b), and retaining the distance from the projection of that extreme contour point to the identified landmark projection point as an additive component to a figure-of-merit;

(f) defining a refined set of sampling parameters for the cross-section plane set of step (c), and an associated second subset of cross-section planes in the neighborhood of the extreme plane identified in step (e), and iterating over step (e);

(g) calculating the figure-of-merit as the sum over the projection set of step (b) of the additive figure-of-merit components of step (f);

(h) iterating steps (e) to (g) for each grid point of the grid defined in step (d) in turn by placing the center of the three-dimensional image set on the grid point, and selecting as the new three-dimensional organ center estimate the grid point that minimizes the figure-of-merit; and

(i) iterating step (h) over a series of three-dimensional grids replacing the grid of step (d) and defining successively finer samplings of the three-dimensional volume in a neighborhood of the three-dimensional organ center estimate obtained in step (h), and obtaining a final three-dimensional organ center estimate from which to calculate a translation vector,

whereby registration of the previously acquired three-dimensional data set of an organ of interest to the patient positioned in the projection imaging system is achieved with a degree of efficiency by applying the translation vector of step (i) to the three-dimensional data set.

9. The method of claim 8, wherein the initial organ center estimate of step (a) is obtained by the user selecting an estimate of the organ center in one projection, and then selecting an estimate of the organ center on a second projection along an epipolar line drawn automatically from knowledge of the projections geometry.

10. The method of claim 8, wherein in step (b) the user is assisted in selecting extreme landmark points by automated image processing and image segmentation tools.

11. The method of claim 8, wherein the first grid parameters of step (d) comprise a grid sampling interval in the range of 1 to 3 cm, and the grid comprises 9×

9×

9 points.

12. The method of claim 8, wherein in step (c) the minimum and maximum range of the organ of interest along the anterior-posterior axis is identified, and wherein a number of planes in the range 100 to 200 is retained, and the planes are equispaced within the range of interest.

13. The method of claim 8, wherein the step (c) of identifying cross-section planes also comprises the step of defining a cut-off plane to eliminate data on one side of the plane in the projections of the three-dimensional data set.

14. The method of claim 8, wherein in step (c) in each plane the organ of interest range along the inferior-superior direction is identified, and wherein a number of lines in the range 60 to 120 is retained, and the lines are equispaced within the range of interest.

15. The method of claim 8, wherein the step of defining contour points on each line of step (c) by segmentation comprises the steps of pre-filtering the gray-scale volumetric data, performing thresholding, and imposing connectivity constraints.

16. The method of claim 8, wherein the step of evaluating a distance between points in step (e) as an additive component to a figure-of-merit comprises calculating an Euclidian norm distance between the points.

17. The method of claim 8, wherein the steps of defining a first subset of cross-section planes in step (e) and defining a second subset of cross-section planes in step (f) comprises the steps of first selecting a subset of N evenly-spaced planes from the full cross-section plane set, and second of selecting the nearest M planes in the neighborhood of the extreme plane of step (e), with an equal number of planes on either side of the extreme plane, and wherein N is in the range 3 to 21 and M is in the range 7 to 51.

18. The method of claim 8, wherein the step of calculating the figure-of-merit in step (g) comprises the step of summing the Euclidian distance between the landmark points and the contour points that project closest thereto, and wherein each distance component is associated with a separate landmark point.

19. The method of claim 8, wherein the step (i) of iterating over a series of three-dimensional grids comprises the steps of defining a second grid with grid interval of X mm and a third grid with grid interval of Y mm, wherein X is in the range 2 to 8 mm, and Y is in the range 0.2 to 0.8 mm.

20. The method of claim 8, wherein the step (i) of iterating over a series of three-dimensional grids comprises the steps of defining a series of decreasing grid intervals, and iterating over the grids until either a figure-of-merit less than a given value has been obtained or a maximum number of grid iterations has been reached.