Virtual Surgical System and Methods

• US 20070208234A1
• Filed: 04/13/2005
• Published: 09/06/2007
• Est. Priority Date: 04/13/2004
• Status: Active Grant

• Current Assignee: The University of Georgia Research Foundation, Inc.
• Original Assignee: The University of Georgia Research Foundation, Inc.
• Inventors: Tollner, Ernest, Bhandarkar, Suchendra
• Granted Patent: US 8,860,753 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 2090/374 NMR or MRI
• CPC Class Codes: A61B 2090/376 using X-rays, e.g. fluoroscopy
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/25 User interfaces for surgical systems
• CPC Class Codes: A61B 34/30 Surgical robots
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A virtual surgical system receives an image, such as a computer tomography (CT) scan, of an area of the patient in need of surgical reconstruction prior to an incision being made in a surgery. Bone fragments that are to be reduced are automatically selected using the virtual surgical system. The system performs surface matching techniques using surface data representing the contour of the end surfaces of the fragments to determine how the corresponding fragments should be oriented to perform the reduction. At least one of the fragments may then be transformed (e.g. via translation and/or rotation) to join the surfaces based on the matched surfaces. An image may be generated of the reconstructed area providing a virtual representation of a reconstructed object. Thus, before actual dissection of the area, and the subsequent physical surgical reduction of the bones, an image of the reconstructed object may be displayed such that a prosthesis may be determined and/or manufactured.

Claims

1. A method for providing virtual alignment of fractured surfaces comprising:

matching at least two fragment surfaces of a fractured object based on surface data corresponding to each of the fragment surfaces, the surface data representing the contour for each of the at least two fragment surfaces;

determining a transformation that places the at least two fragment surfaces in three-dimensional alignment to form a reconstructed object; and

generating an image of the reconstructed object, the reconstructed object including the at least two fragments aligned by the transformation.

2. The method of claim 1, further comprising:

receiving data representing at least one image of at least a portion of the fractured object.

3. The method of claim 2, further comprising:

comparing the value of each pixel in the at least one image to a threshold value;

setting the value of each pixel in each image that is above the threshold value to a first single pixel value; and

setting the value of each pixel in each image that is above the threshold value to a first single pixel value.

4. The method of claim 3, further comprising:

identifying objects in each image based on pixel connectivity; and

filtering identified objects having an area less than a predetermined value from each image.

5. The method of claim 1, wherein the step of determining the transformation includes determining at least one component selected from the group consisting of:

a translational component and a rotational component.

6. The method of claim 1, wherein the step of matching the fragment surfaces includes a surface matching algorithm selected from the group consisting of:

an iterative closest point (ICP) surface matching algorithm and a data aligned rigidity constrained exhaustive search (DARCES) surface matching algorithm.

7. The method of claim 1, wherein the surface data of each of the fragment surfaces forms a fragment surface data set for each fragment surface, and the step of matching the fragment surfaces includes:

matching the fragment surfaces with a data aligned rigidity constrained exhaustive search (DARCES) surface matching algorithm using the fragment surface data sets to produce a transformed sample data set for at least one of the fragment surfaces; and

matching the fragment surfaces with a closest point (ICP) surface matching algorithm using the transformed sample data set.

8. The method of claim 1, further comprising:

displaying the image of the reconstructed object.

9. The method of claim 1, further comprising:

transforming one of the at least two fragment surfaces to place the one of the at least two fragment surfaces in three-dimensional alignment with another of the at least two fragment surfaces.

10. The method of claim 1, wherein the method is performed by a device selected from the group consisting of:

a computer, a computer tomography (CT) scanner, an x-ray machine, a medical imaging device, a magnetic resonance imaging (MRI) device, a sonogram device, a robotic surgical system, a telerobotic surgical system, and a telerobotic surgical interface.

11. The method of claim 1, further comprising:

generating a contour surface data set corresponding to the surface data of each of the at least two fragment surfaces.

12. The method of claim 11, wherein the step of generating the contour surface data set comprises:

receiving a plurality of user selected endpoints; and

determining a plurality of intervening points between the user selected endpoints.

13. A virtual surgical system comprising:

a memory including instructions for providing virtual alignment of fractured surfaces; and

a processor configured to execute the instructions to;

match at least two fragment surfaces of a fractured object based on surface data corresponding to each of the fragment surfaces, the surface data representing the contour for each of the at least two fragment surfaces;

determine a transformation that places the at least two fragment surfaces in three-dimensional alignment to form a reconstructed object; and

generate an image of the reconstructed object, the reconstructed object including the at least two fragments aligned by the transformation.

14. The virtual surgical system of claim 13, wherein the processor is further configured to:

receive data representing at least one image of at least a portion of the fractured object.

15. The virtual surgical system of claim 14, wherein the processor is further configured to:

compare the value of each pixel in the at least one image to a threshold value;

set the value of each pixel in each image that is above the threshold value to a first single pixel value; and

set the value of each pixel in each image that is above the threshold value to a first single pixel value.

16. The virtual surgical system of claim 15, wherein the processor is further configured to:

identify objects in each image based on pixel connectivity; and

filter identified objects having an area less than a predetermined value from each image.

17. The virtual surgical system of claim 13, wherein the processor is further configured to:

determine the transformation by determining at least one component selected from the group consisting of;

a translational component and a rotational component.

18. The virtual surgical system of claim 13, wherein the processor is further configured to:

match the fragment surfaces with a surface matching algorithm selected from the group consisting of;

an iterative closest point (ICP) surface matching algorithm and a data aligned rigidity constrained exhaustive search (DARCES) surface matching algorithm.

19. The virtual surgical system of claim 13, wherein the surface data of each of the fragment surfaces forms a fragment surface data set for each fragment surface, and wherein the processor is further configured to:

match the fragment surfaces by matching the fragment surfaces with a data aligned rigidity constrained exhaustive search (DARCES) surface matching algorithm using the fragment surface data sets to produce a transformed sample data set for at least one of the fragment surfaces; and

match the fragment surfaces with a closest point (ICP) surface matching algorithm using the transformed sample data set.

20. The virtual surgical system of claim 13, further comprising:

an output device for the displaying the image of the reconstructed object.

21. The virtual surgical system of claim 13, wherein the processor is further configured to:

transform one of the at least two fragment surfaces to place the one of the at least two fragment surfaces in three-dimensional alignment with another of the at least two fragment surfaces.

22. The virtual surgical system of claim 13, wherein the virtual surgical system forms at least part of a device selected from the group consisting of:

a computer, a computer tomography (CT) scanner, an x-ray machine, a medical imaging device, a magnetic resonance imaging (MRI) device, a sonogram device, a robotic surgical system, a telerobotic surgical system, and a telerobotic surgical interface.

23. The virtual surgical system of claim 13, wherein the processor is further configured to:

generate a contour surface data set corresponding to the surface data of each of the at least two fragment surfaces.

24. The virtual surgical system of claim 23, wherein the processor is further configured to generate the contour surface data set by:

receiving a plurality of user selected endpoints; and

determining a plurality of intervening points between the user selected endpoints.

25. A computer-readable medium having a computer program for providing virtual alignment of fractured surfaces comprising:

logic configured to match at least two fragment surfaces of a fractured object based on surface data corresponding to each of the fragment surfaces, the surface data representing the contour for each of the at least two fragment surfaces;

logic configured to determine a transformation that places the at least two fragment surfaces in three-dimensional alignment to form a reconstructed object; and

logic configured to generate an image of the reconstructed object, the reconstructed object including the at least two fragments aligned by the transformation.

26. The computer-readable medium of claim 25, further comprising:

logic configured to receive data representing at least one image of at least a portion of the fractured object.

27. The computer-readable medium of claim 26, further comprising:

logic configured to compare the value of each pixel in the at least one image to a threshold value;

logic configured to set the value of each pixel in each image that is above the threshold value to a first single pixel value; and

logic configured to set the value of each pixel in each image that is above the threshold value to a first single pixel value.

28. The computer-readable medium of claim 27, further comprising:

logic configured to identify objects in each image based on pixel connectivity; and

logic configured to filter identified objects having an area less than a predetermined value from each image.

29. The computer-readable medium of claim 25, wherein the logic configured to determine the transformation includes logic configured to determine at least one component selected from the group consisting of:

a translational component and a rotational component.

30. The computer-readable medium of claim 25, wherein the logic configured to match the fragment surfaces includes a surface matching algorithm selected from the group consisting of:

an iterative closest point (ICP) surface matching algorithm and a data aligned rigidity constrained exhaustive search (DARCES) surface matching algorithm.

31. The computer-readable medium of claim 25, wherein the surface data of each of the fragment surfaces forms a fragment surface data set for each fragment surface, and the logic configured to match the fragment surfaces includes

logic configured to match the fragment surfaces with a data aligned rigidity constrained exhaustive search (DARCES) surface matching algorithm using the fragment surface data sets to produce a transformed sample data set for at least one of the fragment surfaces;

and

logic configured to match the fragment surfaces with a closest point (ICP) surface matching algorithm using the transformed sample data set.

32. The computer-readable medium of claim 25, further comprising:

logic configured to display the image of the reconstructed object.

33. The computer-readable medium of claim 25, further comprising:

logic configured to transform one of the at least two fragment surfaces to place the one of the at least two fragment surfaces in three-dimensional alignment with another of the at least two fragment surfaces.

34. The computer-readable medium of claim 25, further comprising:

logic configured to generate a contour surface data set corresponding to the surface data of each of the at least two fragment surfaces.

35. The computer-readable medium of claim 34, wherein the logic configured to generate the contour surface data set comprises:

logic configured to receive a plurality of user selected endpoints; and

logic configured to determine a plurality of intervening points between the user selected endpoints.