Methods, apparatuses, and systems useful in conducting image guided interventions

• US 7,398,116 B2
• Filed: 08/26/2003
• Issued: 07/08/2008
• Est. Priority Date: 08/11/2003
• Status: Active Grant

• Current Assignee: Veran Medical Technologies, Inc. (Olympus Corporation)
• Original Assignee: Veran Medical Technologies, Inc. (Olympus Corporation)
• Inventors: Edwards, Jerome R.
• Primary Examiner(s): Casler; Brian L.
• Assistant Examiner(s): Cheng; Jacqueline
• Application Number:
  US10/649,600
• Publication Number:
  US 20050038337A1
• Time in Patent Office: 1,778 Days
• Field of Search: 600/414, 600/426, 600/424, 600/411, 600/427
• US Class Current: 600/424
• CPC Class Codes: A61B 2017/00694 with means correcting for movement of or for synchronisation with the body
• CPC Class Codes: A61B 2034/2051 Electromagnetic tracking systems
• CPC Class Codes: A61B 2034/2072 Reference field transducer attached to an instrument or patient
• CPC Class Codes: A61B 2090/3954 magnetic, e.g. NMR or MRI
• CPC Class Codes: A61B 2090/3958 emitting a signal
• CPC Class Codes: A61B 2576/00 Medical imaging apparatus involving image processing or analysis A61B1/00009, A61B6/52 and A61B8/52 take precedence; image processing per se G06T; details of algorithms for analysing medical images G06T7/0012
• 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 5/7289 Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition
• CPC Class Codes: A61B 6/12 Arrangements for detecting or locating foreign bodies
• CPC Class Codes: A61B 6/541 involving acquisition triggered by a physiological signal
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for

Abstract

Methods, apparatuses, and systems relating to image guided interventions on dynamic tissue. One embodiment is a method that includes creating a dataset that includes images, one of the images depicting a non-tissue internal reference marker, being linked to non-tissue internal reference marker positional information, and being at least 2-dimensional. Another embodiment is a method that includes receiving a position of an instrument reference marker coupled to an instrument; transforming the position into image space using a position of a non-tissue internal reference marker implanted in a patient; and superimposing a representation of the instrument on an image in which the non-tissue internal reference marker appears. Computer readable media that include machine readable instructions for carrying out the steps of the disclosed methods. Apparatuses, such as integrated circuits, configured to carry out the steps of the disclosed methods. Systems that include devices configured to carry out steps of the disclosed methods.

Claims

1. A method, comprising:

creating a dataset that includes a plurality of images associated with a cyclical movement of a body part, at least one image from the plurality of images depicting a non-tissue internal reference marker, being associated with non-tissue internal reference marker positional information, and being at least 2-dimensional;

associating a separate transformation from a tracking space to an image space with each image in the dataset;

calculating for each image in the dataset a dataset vector using a position of an external reference marker and a position of the non-tissue internal reference marker;

outputting data values associated with a display of an image from the plurality of images;

receiving image space coordinates of the non-tissue internal reference marker in the image associated with the dataset vector;

calculating a transformation from the separate transformations using the image space coordinates and the tracking space coordinates;

associating the transformation with the image associated with the dataset vector;

receiving data associated with a current position of the external reference marker;

receiving data associated with a current position of the non-tissue internal reference marker;

calculating a current vector using the data associated with the current position of the external reference marker and the data associated with the current position of the non-tissue internal reference marker;

identifying a match dataset vector (MDV), the MDV being the dataset vector most similar to the current vector, the MDV being associated with an image from the dataset;

receiving a current position of an instrument reference marker coupled to an instrument;

applying the transformation associated with the image associated with the MDV to the current position of the instrument reference marker, thus transforming the current position of the instrument reference marker into image space; and

superimposing a representation of the instrument on the image associated with the MDV.

2. The method of claim 1, wherein the plurality of images includes images taken using fluoroscopy.

3. The method of claim 1, wherein the plurality of images includes images taken using computed tomography (CT).

4. The method of claim 1, wherein the plurality of images includes images taken using magnetic resonance imaging (MRI).

5. The method of claim 1, wherein the plurality of images includes 3-dimensional images.

6. The method of claim 1, further comprising before the superimposing, receiving an image signal that includes the image.

7. A method, comprising:

creating a dataset that includes a plurality of images associated with a cyclical movement of a body part, at least one image from the plurality of images depicting a non-tissue internal reference marker, being associated with non-tissue internal reference marker positional information, and being at least 2-dimensional;

associating a separate transformation from a tracking space to an image space with each image in the dataset;

calculating for each image in the dataset a dataset vector using a position of an external reference marker and a position of the non-tissue internal reference marker;

outputting data values associated with a display of an image from the plurality of images;

receiving data associated with a current position of the external reference marker;

receiving data associated with a current position of the non-tissue internal reference marker;

calculating a current vector using the data associated with the current position of the external reference marker and the data associated with the current position of the non-tissue internal reference marker;

identifying a match dataset vector (MDV), the MDV being the dataset vector most similar to the current vector, the MDV being associated with an image from the dataset;

receiving a current position of an instrument reference marker coupled to an instrument;

applying the transformation associated with the image associated with the MDV to the current position of the instrument reference marker, thus transforming the current position of the instrument reference marker into image space; and

superimposing a representation of the instrument on the image associated with the MDV, before outputting data values associated with the display.

8. The method of claim 7, wherein the plurality of images includes images taken using fluoroscopy.

9. The method of claim 7, wherein the plurality of images includes images taken using computed tomography (CT).

10. The method of claim 7, wherein the plurality of images includes images taken using magnetic resonance imaging (MRI).

11. The method of claim 7, wherein the plurality of images includes 3-dimensional images.

12. The method of claim 7, further comprising before the superimposing, receiving an image signal that includes the image.

13. A processor-readable medium storing code representing instructions to cause a processor to perform a process, the code comprising code to:

create a dataset that includes a plurality of images associated with a cyclical movement of a body part, at least one image from the plurality of images depicting a non-tissue internal reference marker, being associated with non-tissue internal reference marker positional information, and being at least 2-dimensional;

associate a separate transformation from a tracking space to an image space with each image in the dataset;

calculate for each image in the dataset a dataset vector using a position of an external reference marker and a position of the non-tissue internal reference marker;

output data values associated with a display of an image from the plurality of images;

receive data associated with a current position of the external reference marker;

receive data associated with a current position of the non-tissue internal reference marker;

calculate a current vector using the data associated with the current position of the external reference marker and the data associated with the current position of the non-tissue internal reference marker;

identify a match dataset vector (MDV), the MDV being the dataset vector most similar to the current vector, the MDV being associated with an image from the dataset;

receive a current position of an instrument reference marker coupled to an instrument;

apply the transformation associated with the image associated with the MDV to the current position of the instrument reference marker, thus transforming the current position of the instrument reference marker into image space; and

superimposing a representation of the instrument on the image associated with the MDV.

14. The method of claim 13, wherein the plurality of images includes images taken using fluoroscopy.

15. The method of claim 13, wherein the plurality of images includes images taken using computed tomography (CT).

16. The method of claim 13, wherein the plurality of images includes images taken using magnetic resonance imaging (MRI).

17. The method of claim 13, wherein the plurality of images includes 3-dimensional images.

18. The method of claim 13, further comprising before the superimposing, receiving an image signal that includes the image.

19. A processor-readable medium storing code representing instructions to cause a processor to perform a process, the code comprising code to:

create a dataset that includes a plurality of images associated with a cyclical movement of a body part, at least one image from the plurality of images depicting a non-tissue internal reference marker, being associated with non-tissue internal reference marker positional information, and being at least 2-dimensional;

associate a separate transformation from a tracking space to an image space with each image in the dataset;

calculate for each image in the dataset a dataset vector using a position of an external reference marker and a position of the non-tissue internal reference marker;

output data values associated with a display of an image from the plurality of images;

receive data associated with a current position of the external reference marker;

receive data associated with a current position of the non-tissue internal reference marker;

calculate a current vector using the data associated with the current position of the external reference marker and the data associated with the current position of the non-tissue internal reference marker;

identify a match dataset vector (MDV), the MDV being the dataset vector most similar to the current vector, the MDV being associated with an image from the dataset;

receive a current position of an instrument reference marker coupled to an instrument;

apply the transformation associated with the image associated with the MDV to the current position of the instrument reference marker, thus transforming the current position of the instrument reference marker into image space; and

superimpose a representation of the instrument on the image associated with the MDV, before outputting data values associated with the display.

20. The method of claim 19, wherein the plurality of images includes images taken using fluoroscopy.

21. The method of claim 19, wherein the plurality of images includes images taken using computed tomography (CT).

22. The method of claim 19, wherein the plurality of images includes images taken using magnetic resonance imaging (MRI).

23. The method of claim 19, wherein the plurality of images includes 3-dimensional images.

24. The method of claim 19, further comprising before the superimposing, receiving an image signal that includes the image.