Virtual surgical system and methods

• US 8,860,753 B2
• Filed: 04/13/2005
• Issued: 10/14/2014
• Est. Priority Date: 04/13/2004
• Status: Expired due to Fees

• Current Assignee: The University of Georgia Research Foundation, Inc.
• Original Assignee: The University of Georgia Research Foundation, Inc.
• Inventors: Tollner, Ernest William, Bhandarkar, Suchendra M.
• Primary Examiner(s): Amini, Javid A
• Application Number:
  US11/578,258
• Publication Number:
  US 20070208234A1
• Time in Patent Office: 3,471 Days
• Field of Search: 345/619, 382/378, 382/132
• US Class Current: 345/619
• 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 bones comprising:

capturing image data of fragments of a bone that were separated due to bone fracture;

pre-processing the image data by;

comparing a value of each pixel in the image data to a threshold value;

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

identifying objects in the image data based on pixel connectivity; and

filtering identified objects having an area less than a predetermined value from the image data;

generating three-dimensional models of the bone fragments from the image data;

determining contours of fractured ends of the bone fragments;

matching the fractured ends of the bone fragments;

determining a transformation that places the fractured ends in three-dimensional alignment to form a reconstructed bone; and

generating an image of the reconstructed bone that results from the transformation.

2. The method of claim 1, wherein determining the transformation includes determining at least one component selected from the group consisting of a translational component and a rotational component.

3. The method of claim 1, wherein matching the fractured ends includes applying 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.

4. The method of claim 1, wherein surface data of each of the fractured ends forms a surface data set for each of the fractured ends, and matching the fractured ends includes:

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

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

5. The method of claim 1, further comprising displaying the image of the reconstructed bone.

6. The method of claim 1, wherein the computing device is selected from a group consisting of:

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.

7. The method of claim 1, further comprising generating a contour surface data set corresponding to each of the fractured surfaces.

8. The method of claim 7, wherein 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.

9. A virtual surgical system comprising:

a memory including instructions for providing virtual alignment of bone fragments; and

a processor configured to execute the instructions to;

receive captured image data of the bone fragments;

pre-process the image data by;

comparing the value of each pixel in the image data to a threshold value;

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

identifying objects in the image data based on pixel connectivity; and

filtering identified objects having an area less than a predetermined value from the image data;

generate three-dimensional models of the bone fragments;

determine contours of fractured ends of the bone fragments;

match the fractured ends of the bone fragments;

determine a transformation that places the fractured ends in three-dimensional alignment to form a reconstructed bone; and

generate an image of the reconstructed bone that results from the transformation.

10. The virtual surgical system of claim 9, 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.

11. A virtual surgical system of claim 9, wherein the processor is further configured to match the fractured ends 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.

12. The virtual surgical system of claim 9, wherein surface data of each of the fractured ends forms a surface data set for each fractured ends, and wherein the processor is further configured to:

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

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

13. The virtual surgical system of claim 9, further comprising an output device for displaying the image of the reconstructed bone.

14. The virtual surgical system of claim 9, 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.

15. The virtual surgical system of claim 9, wherein the processor is further configured to generate a contour surface data set corresponding to each of the fractured ends.

16. The virtual surgical system of claim 15, 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.

17. A non-transitory computer-readable memory that stores a computer program for providing virtual alignment of bone fragments comprising:

logic configured to generate three-dimensional models of bone fragments that were separated due to bone fracture;

logic configured to compare the value of each pixel in the image data to a threshold value;

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

logic configured to identify objects in the image data based on pixel connectivity;

logic configured to filter identified objects having an area less than a predetermined value from the image data;

logic configured to determine contours of fractured ends of the bone fragments;

logic configured to match the fractured ends of the bone fragments;

logic configured to determine a transformation that places the fractured ends in three-dimensional alignment to form a reconstructed bone; and

logic configured to generate an image of the reconstructed bone that results from the transformation.

18. The non-transitory computer-readable memory of claim 17, 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.

19. The non-transitory computer-readable memory of claim 17, wherein the logic configured to match the fractured ends 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.

20. The non-transitory computer-readable memory of claim 17, wherein the surface data of each of the fractured ends forms a surface data set for each fragment surface, and the logic configured to match the fractured ends includes:

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

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

21. The non-transitory computer-readable memory of claim 17, further comprising logic configured to display the image of the reconstructed bone.

22. The non-transitory computer-readable memory of claim 17, further comprising logic configured to generate a contour surface data set corresponding to each of the fractured surfaces.

23. The non-transitory computer-readable memory of claim 22, 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.