Method for dynamic road mapping

1. A method of determining a three-dimensional (3D) position of a catheter tip, the method comprising:

compensating a 2D position of the tip of the catheter for respiratory motion to generate a compensated 2D catheter position;

generating weighted 2D sample points around the compensated 2D catheter position;

determining 3D correspondent points of the weighted sample points in a 3D image;

computing, with a processor, 3D sample points around each 3D correspondent point using a modified transformation derived from evaluating an iterative closest point cost function;

computing, with a processor, a weighted mean of each 3D correspondent point from the corresponding 3D sample points using a weight corresponding to the modified transformation;

computing, with a processor, a weighted covariance of each 3D correspondent point based on a difference between the corresponding weighted mean and the corresponding 3D sample points; and

determining the 3D position of the catheter tip in the 3D image from a fusion of the weighted means and weighted covariances.

2. The method of claim 1 , wherein the uncompensated 2D position is derived from a 2D fluoroscopic sequence depicting the catheter and the method further comprises:

motion compensating an image of the 2D sequence using the compensated 2D catheter position; and

overlaying a 3D vessel tree of the 3D image with the motion compensated image using the determined 3D position.

3. The method of claim 2 , wherein the compensating comprises:

selecting a region in a first image in which the catheter is visible and has a distinguishable shape as a template;

determining a difference between a position of a matching region in a second image of the sequence and the position of the template to determine a respiratory motion displacement; and

subtracting the respiratory motion displacement from the uncompensated 2D position.

4. The method of claim 1 , wherein determining correspondent points of the weighted sample points in the 3D image comprises back-projecting each weighted sample point as a 3D line.

5. The method of claim 3 , wherein generating weighted sample points around the compensated 2D catheter position comprises:

generating modified displacements from the respiratory motion displacement;

determining sample points around the compensated 2D catheter position based on the modified displacements; and

applying weights to each sample point based on a result of a cost function associated with the compensation of the respiratory motion.

6. The method of claim 5 , wherein the cost function is evaluated using the modified displacements.

7. The method of claim 6 , wherein the weights are generated by:

evaluating the cost function;

normalizing results of the cost function; and

deriving the weights from the noimalized results.

8. The method of claim 5 , wherein the weighted mean and the weighted covariance of each correspondent point is based on a reciprocal of the cost function associated with the compensation of the respiratory motion.

9. The method of claim 1 , wherein determining the 3D position of the catheter tip in the 3D image from a fusion of the weighted means and weighted covariances are fused using Variable-Bandwidth Density-Based Fusion.

10. The method of claim 4 , wherein the back-projecting is performed via a projection matrix.

11. The method of claim 10 , wherein the projection is generated by aligning a Digital Subtraction Angiography (DSA) image with a 3D vessel model.

12. The method of claim 1 , wherein determining the 3D position of the catheter tip in the 3D image from a fusion of the weighted means and weighted covariances:

obtaining a common mean from information of the fusion; and

determining a point on a vessel in the 3D image that is closest to the common mean.

13. The method of claim 1 , further comprising using the determined 3D position to guide a catheter.

14. A method of guiding a catheter in a vessel, the method comprising:

registering, with a processor, a Digital Subtraction Angiography (DSA) image with a 3D vessel model to generate a projection matrix;

detecting a 2D catheter tip position in a 2D image;

compensating for motion in the catheter tip position based on the 2D image and a reference 2D image;

generating weighted 2D sample points around the compensated catheter tip position;

determining correspondent 3D points of he weighted 2D sample points in the 3D vessel model;

selecting one of the correspondent 3D points based on an uncertainty of the registration and the compensation; and

guiding the catheter using the selected correspondent 3D point.

15. The method of claim 14 , wherein the detecting the catheter tip position comprises using one of a magnetic tracking or optical tracking.

16. The method of claim 14 , wherein the 2D image comprises an image from a fluoroscope.

17. The method of claim 14 , wherein the DSA image and the 3D vessel model are derived from a 3D computed tomography angiography image.

18. The method of claim 14 , wherein the catheter tip position is determined from a first image of a sequence of 2D images.

19. The method of claim 18 , wherein the compensating comprises:

selecting a region in the first image in which the catheter is visible and has a distinguishable shape as a template;

determining a difference between a position of a matching region in a second image of the sequence and the position of the template to determine a respiratory motion displacement; and

subtracting the respiratory motion displacement from the catheter tip position.

20. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps of determining a three-dimensional (3D) position of a catheter tip, the method steps comprising:

compensating a 2D position of a catheter tip for motion to generate a compensated 2D catheter position;

generating first sample points around the compensated 2D catheter tip position;

determining correspondent points of the first sample points in a 3D image;

computing second sample points around each correspondent point using a modified transformation derived from evaluating an iterative closest point cost function;

computing a weighted mean for each correspondent point from the corresponding second sample points using a weight corresponding to the modified transformation;

computing a weighted covariance of each correspondent point based on a difference between the corresponding weighted mean and the corresponding second sampling points; and

determining the 3D position of the catheter tip in the 3D image from a fusion of the weighted means and weighted covariances.