Method for registering a physical space to image space

• US 8,548,563 B2
• Filed: 03/19/2012
• Issued: 10/01/2013
• Est. Priority Date: 03/29/2007
• Status: Active Grant

• Current Assignee: Medtronic Navigation Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Navigation Incorporated (Medtronic Plc)
• Inventors: Simon, David A., Ghanei, Amir, Mark, Kevin E., Lajoie, Andrew, Ruckel, Geoffrey M.
• Primary Examiner(s): Kish, James
• Assistant Examiner(s): COOK, CHRISTOPHER L
• Application Number:
  US13/423,984
• Publication Number:
  US 20120179026A1
• Time in Patent Office: 561 Days
• Field of Search: 600/407, 600/410, 600/414, 600/424, 600/425, 600/426, 382/128, 382/131
• US Class Current: 600/414
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/2051 Electromagnetic tracking systems
• CPC Class Codes: A61B 2034/2055 Optical tracking systems
• CPC Class Codes: A61B 2034/2068 using pointers, e.g. pointers having reference marks for determining coordinates of body points
• 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 2090/367 creating a 3D dataset from 2D images using position information
• CPC Class Codes: A61B 2090/376 using X-rays, e.g. fluoroscopy
• 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: A61B 90/39 Markers, e.g. radio-opaque or breast lesions markers

Abstract

A method and apparatus for registering physical space to image space is disclosed. The system allows for determining fiducial markers as pixels or voxels in image data. The system can correlate and register the determined fiducial points with fiducial markers in physical space.

Claims

1. A method of registering image space and physical space in a computer aided surgical navigation system, comprising:

forming a computer readable template of a fiducial;

acquiring image data;

comparing, by executing instructions with a processor, the template to a plurality of points in the image data, wherein the plurality of points includes a sub-plurality of fiducial points;

determining the sub-plurality of fiducial points from the plurality of points based on comparing the template;

identifying a plurality of fiducial markers in the physical space;

matching a first subset of the determined sub-plurality of fiducial points with a first subset of the identified plurality of fiducial markers;

calculating a transformation of the image space to the physical space based on matching the first subset of the determined sub-plurality of fiducial points with the first subset of the identified plurality of fiducial markers;

registering the image space to the physical space; and

forming a local 2D tangential resection of the acquired image data;

wherein comparing the template to the plurality of points includes comparing at least a two dimensional template to the local 2D tangential resection data.

2. The method of claim 1, further comprising:

performing an image guided navigation procedure with the registered image space image data;

displaying the registered image data on a display device; and

displaying an icon representing a position of an instrument superimposed on the image data.

3. The method of claim 1 further comprising:

providing the fiducial marker;

attaching the fiducial marker to a member; and

wherein acquiring image data includes imaging the member that includes the fiducial marker.

4. The method of claim 1, wherein acquiring image data includes acquiring magnetic resonance image data, acquiring ultra sound image data, acquiring computed tomography image data, acquiring X-ray image data, acquiring PET image data, acquiring SPECT image data, or combinations thereof.

5. The method of claim 1, wherein comparing the formed template to the plurality of points include systematically and virtually overlaying the formed template on the plurality of points in the image data;

and

determining a match of the formed template to at least one of the plurality of points in the image data.

6. The method of claim 1 wherein determining the sub-plurality of fiducial points includes determining a score of a comparison of the formed template to at least one of the plurality of points;

wherein the score is based upon a determined match between the formed template and at least one of the plurality of points.

7. The method of claim 6, further comprising:

scoring each of the candidates;

forming a list of candidate fiducial points based upon the determined sub-plurality of fiducial points; and

sorting the list of candidate fiducial points based upon the score.

8. The method of claim 7, further comprising:

determining a threshold score;

wherein forming the list includes including candidate fiducial points having at least the threshold score.

9. The method of claim 1, wherein forming the template further includes forming a three dimensional template.

10. The method of claim 1, further comprising:

determining at least N candidate fiducial points in the image data;

wherein identifying a plurality of fiducial markers include identifying at least N-fiducial markers;

forming a N-fiducial point subset in the image data and producing a N-fiducial marker subset in the physical space;

matching the N-fiducial point subset and the N-fiducial marker subset;

wherein calculating a transformation includes calculating a first transformation based upon the matched N-fiducial point subset and the N-fiducial marker subset.

11. The method of claim 10, further comprising:

selecting a match criterion;

determining at least a N+1 candidate fiducial point;

wherein identifying a plurality of fiducial markers include identifying at least a N+1 fiducial marker;

determining whether the N+1 candidate fiducial point meets the match criterion when compared to the N+1 fiducial marker;

forming a N+1-fiducial point subset with the N+1 candidate fiducial point and a N+1-fiducial marker subset with the N+1 fiducial marker if the match criterion is met between the N+1 candidate fiducial point and the N+1 fiducial marker.

12. The method of claim 11, wherein calculating a transformation includes determining a match for each of the determined sub-plurality of fiducial points and identified fiducial markers.

13. The method of claim 11, further comprising:

matching the N+1-fiducial point subset and the N+1-fiducial marker subset; and

calculating a second transformation based upon the N+1-fiducial point subset and the N+1-fiducial marker subset.

14. The method of claim 13, further comprising:

determining whether the N+1-fiducial point subset includes all of the identified plurality of fiducial markers.

15. The method of claim 14, further comprising:

identifying in the image data the position of identified fiducial markers based upon the calculated transformation;

comparing the formed template at the identified points;

determining a second sub-plurality of fiducial points;

matching the second sub-plurality of the fiducial points to at least a sub-plurality of the identified fiducial markers.

16. The method of claim 15, further comprising:

registering the image space to the physical space based upon the identification of the fiducial points in the image data based upon the second determination of fiducial points.

17. The method of claim 10, wherein forming a N-fiducial point subset in the image data and producing a N-fiducial marker subset in the physical space, includes:

determining a distance between each of the fiducial point candidates in the N-fiducial point subset; and

determining a distance between each of the fiducial markers in the N-fiducial marker subset.

18. The method of claim 1, wherein identifying a plurality of fiducial markers includes:

contacting the fiducial markers with a device; and

determining a location of the device.

19. The method of claim 1, further comprising:

determining candidate fiducial points in the image data from the sub-plurality of fiducial points;

forming a fiducial point subset in the image data and forming a fiducial marker subset in the physical space;

matching the fiducial point subset and the fiducial marker subset;

wherein calculating a transformation includes calculating a first transformation based upon the matched fiducial point subset and the fiducial marker subset.

20. The method of claim 19, further comprising:

selecting a match criterion;

identifying at least one additional candidate fiducial point not in the fiducial point subset;

identifying at least one additional fiducial marker not in the fiducial marker subset;

determining whether the identified at least one additional candidate fiducial point meets the match criterion when compared to the identified at least one additional fiducial marker;

successively adding the identified at least one additional candidate fiducial point to the fiducial point subset and adding the identified at least one additional candidate fiducial marker to the fiducial marker subset until no additional fiducial points meet the match criterion; and

forming a final fiducial point subset when no additional candidate fiducial points can be added and a final fiducial marker subset when no additional fiducial markers can be added.

21. The method of claim 20, further comprising:

matching the final fiducial point subset and the final fiducial marker subset; and

calculating a second transformation based upon the final fiducial point subset and the final fiducial marker subset.

22. The method of claim 21, further comprising:

determining whether the final fiducial point subset includes all of the identified plurality of fiducial markers.

23. A method of registering image space and physical space in a computer aided surgical navigation system, comprising:

forming a computer readable template of a fiducial marker;

acquiring an image data;

comparing the template to a plurality of points in the image data, wherein the plurality of points includes a sub-plurality of fiducial points;

determining the sub-plurality of fiducial points from the plurality of points based on the comparing the template;

identifying a plurality of fiducial markers in the physical space;

matching a first subset of the fiducial points with a first subset of the fiducial markers;

calculating a transformation of the image space to the physical space;

registering the image space to the physical space; and

forming a local 2D tangential resection of the acquired image data;

wherein comparing the template to the plurality of points includes comparing at least a two dimensional template to the local 2D tangential resection data.

24. The method of claim 23, wherein determining the sub-plurality of fiducial points includes determining an initial list of candidate fiducial points based upon comparing the two dimensional template to the formed 2D tangential resection data set.

25. The method of claim 24, further comprising:

comparing a three dimensional template to the acquired image data at the location of the candidate fiducial points;

wherein the acquired image data includes 3D image data.

26. The method of claim 25, further comprising:

determining a score for each of the comparisons made to the three dimensional template;

selecting the candidate fiducial points having the determined score above a selected threshold score; and

sorting the selected fiducial candidate points.

27. The method of claim 26, further comprising:

comparing the three dimensional fiducial template to the selected fiducial candidate points.

28. A method of registering image space and physical space in a computer aided surgical navigation system, comprising:

acquiring image data;

comparing, with a processor system, a computer readable fiducial template of a fiducial marker to the image data to identify fiducial points defined by the image data of a member with the fiducial marker affixed to the member;

tracking a device defining a single registration point relative to the fiducial marker;

determining a position of the fiducial marker based on tracking the device;

forming a two dimensional tangential resection of the image data;

comparing the two dimensional computer readable fiducial template to the two dimensional tangential resected image data;

matching, with the processor system, the identified fiducial points and the determined fiducial markers; and

registering the image space and the physical space based at least on matching the identified fiducial points and the determined fiducial markers.

29. The method of claim 28, further comprising:

forming a two dimensional computer readable fiducial template as the computer readable fiducial template of the fiducial marker, forming a three dimensional computer readable fiducial template as the computer readable fiducial template of the fiducial marker, or combinations thereof.

30. The method of claim 29, wherein acquiring the image data includes acquiring three dimensional image data of a member including the fiducial marker.

31. The method of claim 30, further comprising:

determining a first list of fiducial point candidates based upon the comparison of the two dimensional computer readable fiducial template to the two dimensional tangential resected data.

32. The method of claim 31, wherein comparing a computer readable fiducial template includes comparing the three dimensional fiducial template to the image data only at the locations in the first list of candidate fiducial points;

producing a second list of fiducial point candidates including a score of the candidate fiducial points.

33. The method of claim 32, further comprising:

determining a threshold score of the fiducial point candidates in the second list;

removing each of the fiducial point candidates from a second list that have a score less than the threshold score; and

comparing the three dimensional computer readable fiducial template substantially more precisely to the point in the image data identified to at least have the threshold score.

34. The method of claim 33, wherein comparing the three dimensional computer readable fiducial template substantially more precisely includes:

determining an orientation, a position, or combinations thereof of the fiducial point candidate by matching it to the three dimensional computer readable fiducial template.

35. The method of claim 28, wherein comparing a computer readable fiducial template to identified fiducial points includes:

determining a list of fiducial point candidates;

determining a plurality of N-fiducial point subsets from all of the fiducial point candidates; and

determining a N-point fiducial marker subset from all of the determined positions of the fiducial markers.

36. The method of claim 35, further comprising:

comparing each of the N-fiducial point subsets to each of the N-fiducial marker subsets; and

determining a match between each of the compared N-fiducial point subsets and the N-fiducial marker subsets.

37. The method of claim 36, further comprising:

transforming the image data to the physical space based upon at least one match of the N-fiducial point subsets and the N-fiducial marker subsets;

determining at least one additional fiducial point match to a fiducial marker; and

adding the additional point to at least one of the N-fiducial point subsets to form an N+1-fiducial point subset and adding at least one fiducial marker to the N-fiducial marker subset to create an N+1-fiducial marker subset.

38. The method of claim 36, further comprising:

adding at least one fiducial point to the N-fiducial point subset and at least one fiducial marker to the N-fiducial marker subset until an identified fiducial point from the candidate list is not within a criterion when compared to the determined position of the fiducial marker.

39. The method of claim 38, wherein the criterion includes a distance, an angle, a geometry, or combinations thereof.

40. The method of claim 28, wherein comparing the identified fiducial points to the determined fiducial markers includes determining whether each of the determined fiducial markers is matched to only one of the identified fiducial points;

wherein if at least one of the determined fiducial markers is not matched to at least one fiducial point then comparing the template to the portion of the image data transformed to the position of the determined fiducial marker.

41. The method of claim 40, further comprising:

calculating a transformation of the image data to the physical space based upon the match of at least three of the fiducial markers to at least three of the identified fiducial points;

determining a position in the image data of the position of the determined fiducial marker; and

comparing the computer readable fiducial template to the area identified as containing a determined fiducial marker.

42. The method of claim 28, wherein imaging the member includes acquiring magnetic resonance image data, computed tomography image data, X-ray image data, ultra sound image data, PET image data, SPECT image data, or combinations thereof.

43. The method of claim 28, wherein the device defining the single registration point includes a reference point defined relative to a curved surface and operable to contact the fiducial marker;

wherein comparing the computer readable fiducial template includes identifying in the image data the position of the fiducial point that can be registered to the reference point.