Apparatus and methods of cortical surface registration and deformation tracking for patient-to-image alignment in relation to image-guided surgery

• US 7,647,087 B2
• Filed: 08/02/2006
• Issued: 01/12/2010
• Est. Priority Date: 09/08/2003
• Status: Active Grant

• Current Assignee: Vanderbilt University
• Original Assignee: Vanderbilt University
• Inventors: Sinha, Tuhin K., Miga, Michael I., Dawant, Benoit M.
• Primary Examiner(s): Le; Long V
• Assistant Examiner(s): FONTENOT, NIGEL RAI
• Application Number:
  US11/497,589
• Publication Number:
  US 20070021669A1
• Time in Patent Office: 1,259 Days
• Field of Search: 600/411, 600/417, 600/425, 600/427, 600/426, 600/429
• US Class Current: 600/425
• CPC Class Codes: A61B 2017/00694 with means correcting for movement of or for synchronisation with the body
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2034/2055 Optical tracking systems
• CPC Class Codes: A61B 2034/2065 Tracking using image or pattern recognition
• CPC Class Codes: A61B 2034/256 having a database of accessory information, e.g. including context sensitive help or scientific articles
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 2090/373 using light, e.g. by using optical scanners
• CPC Class Codes: A61B 2090/378 using ultrasound
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for
• CPC Class Codes: G06T 7/35 using statistical methods
• CPC Class Codes: G06T 7/38 Registration of image sequences
• CPC Class Codes: G06V 10/757 Matching configurations of points or features
• CPC Class Codes: G06V 10/758 Involving statistics of pixels or of feature values, e.g. histogram matching
• CPC Class Codes: G06V 20/653 by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
• CPC Class Codes: G06V 2201/031 of internal organs

Abstract

A cortical surface registration procedure related to a diagnostic or surgical procedure. In one embodiment, the procedure includes the steps of pre-operatively obtaining a first textured point cloud of the cortical surface of a targeted region of a brain of a living subject, intra-operatively obtaining optically a second textured point cloud of the cortical surface of the brain of the living subject, and aligning the first textured point cloud of the cortical surface to the second textured point cloud of the cortical surface so as to register images of the brain of the living subject to the cortical surface of the living subject.

Claims

1. A cortical surface registration procedure related to a diagnostic or surgical procedure, comprising:

(a) pre-operatively obtaining a first textured point cloud of the cortical surface of a targeted region of a brain of a living subject;

(b) intra-operatively obtaining optically a second textured point cloud of the cortical surface of the brain of the living subject;

(c) aligning the first textured point cloud of the cortical surface to the second textured point cloud of the cortical surface so as to register images of the brain of the living subject to the cortical surface of the living subject; and

(d) generating an image of the registered images,

wherein at least the second textured point cloud contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature related to the cortical surface of the brain of the living subject.

2. The procedure of claim 1, wherein the step of pre-operatively obtaining a first textured point cloud comprises the steps of:

(a) pre-operatively acquiring an image volume from the brain of the living subject;

(b) segmenting the acquired image volume;

(b) extracting a point cloud representation of the brain surface geometry from the segmented image volume;

(c) performing a ray-casting and voxel intensity averaging on the point cloud representation so as to generate a grayscale encoded brain surface that contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature; and

(d) obtaining the first textured point cloud from the grayscale encoded brain surface.

3. The procedure of claim 2, wherein the image volume of the brain of the living subject comprises image data with respect to the brain surface geometry.

4. The procedure of claim 3, wherein the image data with respect to the brain surface geometry is obtained through the use of at least one of positron emission tomography, electroencephalography, computer tomography, functional magnetic resonance imaging and magnetic resonance imaging.

5. The procedure of claim 1, wherein the step of intra-operatively obtaining optically a second textured point cloud comprises the steps of:

(a) optically scanning an exposed brain surface of the living subject during surgery;

(b) capturing surface-reflected light from the brain surface of the living subject;

(c) acquiring a point cloud representation of the geometry of the cortical surface from the captured surface-reflected light; and

(d) color-encoding the acquired point cloud representation with intensity values of a field of view so as to obtain the second textured point cloud of the cortical surface of the at least one targeted region of the brain.

6. The procedure of claim 5, wherein the step of optically scanning an exposed brain surface is performed with an optical device that is capable of obtaining frequency, intensity and geometric data with respect to the cortical surface simultaneously.

7. The procedure of claim 6, wherein the optical device is a laser range scanner.

8. The procedure of claim 1, wherein the step of aligning the first textured point cloud of the cortical surface to the second textured point cloud of the cortical surface comprises the steps of:

(a) registering the first textured point cloud of the cortical surface to the second textured point cloud of the cortical surface using an iterative closest point algorithm; and

(b) optimizing the first textured point cloud of the cortical surface to the second textured point cloud of the cortical surface using normalized mutual information.

9. A system for cortical surface registration related to a diagnostic or surgical procedure, comprising:

(a) an imaging acquiring device configured for pre-operatively obtaining a first textured point cloud of the cortical surface of a targeted region of a brain of a living subject;

(b) an optical device configured for intra-operatively obtaining a second textured point cloud of the cortical surface of the brain of the living subject; and

(c) a computer configured for receiving and processing data related to the first textured point cloud of the cortical surface and the second textured point cloud of the cortical surface so as to register images of the brain of the living subject to the cortical surface of the living subject,

wherein at least the second textured point cloud contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature related to the cortical surface of the brain of the living subject.

10. The system of claim 9, further comprising a display device coupled to the computer for displaying the cortical surface registration dynamically to facilitate the diagnostic or surgical procedure.

11. The system of claim 9, wherein the imaging acquiring device comprises at least one of positron emission tomography device, electroencephalography device, computer tomography device, functional magnetic resonance imaging device and magnetic resonance imaging device.

12. The system of claim 9, wherein the optical device comprises a laser device.

13. The system of claim 12, wherein the laser device is a laser range scanner configured for optically scanning an exposed brain surface of the living subject during the diagnostic or surgical procedure.

14. The system of claim 13, wherein the optical device further comprises a first digital camera configured for capturing surface-reflected light from the brain surface of the living subject when the brain surface of the living subject is scanned by the laser range scanner.

15. The system of claim 14, wherein the optical device further comprises a second digital camera configured for capturing an image of the surgical field of view.

16. A method of deformable cortical surface registration related to a diagnostic or surgical procedure to track brain deformation, comprising the steps of:

(a) obtaining a first 3D textured point cloud of a brain of a living subject prior to or during brain deformation at a first time, wherein each 3D point of the first 3D textured point cloud is color-encoded;

(b) generating a first 2D photographic image from the first 3D textured point cloud;

(c) obtaining a second 3D textured point cloud of the brain during or after brain deformation at a second time, wherein each 3D point of the second 3D textured point cloud representation is color-encoded;

(d) generating a second 2D photographic image from the second 3D textured point cloud; and

(e) non-rigidly aligning the first 2D photographic image and the second 2D photographic image so as to track the brain deformation,

wherein the first 3D textured point cloud contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature related to the brain of the living subject at the first time, and the second 3D textured point cloud contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature related to the brain of the living subject at the second time.

17. The method of claim 16, wherein the step of obtaining a first 3D textured point cloud comprises the steps of:

(a) optically scanning an exposed brain surface of the living subject at a time prior to or during brain deformation;

(b) capturing surface-reflected light from the brain surface of the living subject;

(c) acquiring a first poi

(d) nt cloud representation of the geometry of the cortical surface from the captured surface-reflected light; and

(e) color-encoding the acquired each point of the first point cloud representation by a direct linear transform representation so as to construct the first 3D textured point cloud.

18. The method of claim 17, wherein the step of optically scanning an exposed brain surface is performed with an optical device that is capable of obtaining frequency, intensity and geometric data with respect to the cortical surface simultaneously.

19. The method of claim 18, wherein the optical device is a laser range scanner.

20. The method of claim 17, wherein the step of obtaining a second 3D textured point cloud comprises the steps of:

(a) optically scanning an exposed brain surface of the living subject at a time during or after the step of obtaining a first 3D textured point cloud;

(b) capturing surface-reflected light from the brain surface of the living subject;

(c) acquiring a second point cloud representation of the geometry of the cortical surface from the captured surface-reflected light; and

(d) color-encoding the acquired each point of the second point cloud representation by a direct linear transform representation so as to construct the second 3D textured point cloud.

21. The method of claim 16, wherein the step of non-rigidly aligning the first 2D photographic image and the second 2D photographic image so as to track the brain deformation comprises the steps of:

(a) transforming the first and second 2D photographic images from RGB images into corresponding gray level images; and

(b) obtaining a final deformation field that registers gray level images one to the other.

22. The method of claim 21, wherein the step of obtaining a deformation field comprises the steps of:

(a) calculating a deformation field for each of a series of levels, wherein each level is corresponding to a particular combination of scale and resolution for an image; and

(b) adding all the deformation fields for all of the series of levels to generate the final deformation field.

23. A system of deformable cortical surface registration related to a diagnostic or surgical procedure to track brain deformation, comprising:

(a) image data acquiring means for obtaining a first 3D textured point cloud of a brain of a living subject prior to or during brain deformation at a first time, wherein each 3D point of the first 3D textured point cloud is color-encoded, and a second 3D textured point cloud of the brain during or after brain deformation at a second time, wherein each 3D point of the second 3D textured point cloud representation is color-encoded, respectively;

(b) image generating means for generating a first 2D photographic image from the first 3D textured point cloud, and a second 2D photographic image from the second 3D textured point cloud, respectively; and

(c) registration means for non-rigidly aligning the first 2D photographic image and the second 2D photographic image so as to track the brain deformation,

wherein the first 3D textured point cloud contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature related to the brain of the living subject at the first time, and the second 3D textured point cloud contains intensity patterns representing sulcal-gyrus differences and contrast-enhanced vasculature related to the brain of the living subject at the second time.

24. The system of claim 23, wherein the image data acquiring means is capable of:

(a) optically scanning an exposed brain surface of the living subject at a selected time;

(b) capturing surface-reflected light from the brain surface of the living subject;

(c) acquiring a point cloud representation of the geometry of the cortical surface from the captured surface-reflected light; and

(d) color-encoding the acquired each point of the point cloud representation by a direct linear transform representation so as to construct a 3D textured point cloud.

25. The system of claim 24, wherein the image data acquiring means comprises an optical device that is capable of obtaining frequency, intensity and geometric data with respect to the cortical surface simultaneously.

26. The system of claim 25, wherein the optical device is a laser range scanner.

27. The system of claim 25, wherein the image data acquiring means further comprises a first digital camera configured for capturing surface-reflected light from the brain surface of the living subject when the brain surface of the living subject is scanned by the laser range scanner.

28. The system of claim 27, wherein the image data acquiring means further comprises a second digital camera configured for capturing an image of the surgical field of view.

29. The system of claim 23, wherein the image generating means comprises a computer.

30. The system of claim 23, wherein the registration means comprises a controller.