System and method for lidar-based anatomical mapping
System and method for lidar-based anatomical mapping is provided. In one implementation, a LIDAR imaging technology is utilized to create a surface-based anatomical map of an exposed anatomical surface of at least a portion of the spine, or other anatomical features, using anatomical and/or artificial landmarks are disclosed. The surface mapping can then be registered with previously acquired images of at least the portion of the spine, or other anatomical features. The surface mapping can then be used to identify important structures, including an entry point in tissue (including soft tissue and bone) for the placement of a medical instrument or implant, or for Information the orientation of a medical instrument or device. The information can be displayed in an augmented reality overlay on a device display (e.g., wearable eyeglasses). The LIDAR imaging technology may be incorporated into wearable eyeglasses.
1. A system for facilitating insertion of a surgical tool or a medical device into a subject, the system comprising:
a computing device comprising:
a LIDAR scanner;
an optical camera, configured to obtain one or more images;
a display screen; and
one or more processors configured to:
receive scanning data from the LIDAR scanner that corresponds to an anatomical surface at a desired location of the subject;
identify one or more anatomical landmarks based on the received scanning data by applying one or more trained neural networks or machine learning databases trained using a set of anatomical surface scans and diagnostic images;
generate an anatomical surface map of the anatomical surface of the desired location of the subject using the one or more anatomical landmarks identified based on the received scanning data;
correlate the anatomical surface map with one or more diagnostic images of at least the desired location of the subject;
determine an anatomical entry point for insertion of the surgical tool or the medical device based on the correlation and based on at least one of the one or more anatomical landmarks identified by applying the one or more trained neural networks or machine learning databases; and
generate an output indicative of the determined anatomical entry point for display.
2. The system of claim 1 , wherein the computing device further comprises an orientation sensor.
3. The system of claim 1 , wherein the one or more diagnostic images comprise CT or MRI images.
4. The system of claim 1 , wherein the display screen of the computing device is configured to provide an augmented reality display that displays virtual digital images superimposed on a video provided by the optical camera.
5. The system of claim 4 , wherein the output comprises a 2D or 3D virtual digital icon or image that is superimposed on the video presented on the display screen of the computing device.
6. The system of claim 5 , wherein the virtual digital icon or image comprises:
a cross-hair digital icon; or
a 3D image of a medical instrument or shape that is also indicative of a trajectory.
7. The system of claim 1 , wherein the LIDAR scanner, the optical camera, and the one or more processors are housed within the computing device; and wherein the display screen is housed within a wearable augmented reality device communicatively coupled to the computing device.
8. The system of claim 1 , wherein the LIDAR scanner, the optical camera, the one or more processors, and the display screen of the computing device reside on or in a wearable augmented reality device.
9. The system of claim 1 , wherein the anatomical surface at the desired location is at or adjacent to a surgically exposed surface.
10. The system of claim 9 , wherein the surgically exposed surface is at least a portion of a spine.
11. The system of claim 1 , wherein the anatomical surface at the desired location is a portion of an exterior surface of the subject.
12. The system of claim 1 , wherein the computing device is a mobile computing device.
13. The system of claim 1 , wherein the one or more processors are further configured to determine a surgical trajectory.
14. The system of claim 13 , wherein the surgical trajectory is a 3D trajectory.
15. An apparatus for positioning a surgical tool, the apparatus comprising:
a LIDAR scanner;
a display screen; and
one or more processors configured to:
receive data from the LIDAR scanner of a surgical surface;
identify one or more anatomical landmarks based on the received data by applying one or more trained neural networks or machine learning databases trained using a set of anatomical surface scans and diagnostic images;
generate a surface map of the surgical surface based on at least the data from the LIDAR scanner;
determine an insertion point for the surgical tool based at least on the surface map and one or more diagnostic images and based on at least one of the one or more anatomical landmarks identified by applying the one or more trained neural networks or machine learning databases; and
generate an indication of the insertion point on the display screen.
16. The apparatus of claim 15 , wherein the one or more processors are further configured to determine a desired orientation for the surgical tool based at least on the surface map and the insertion point.
17. The apparatus of claim 16 , wherein the one or more processors are further configured to generate a simulation of the desired orientation for the surgical tool.
18. The apparatus of claim 17 , wherein the one or more processors are further configured to:
determine a current orientation of the surgical tool; and
responsive to the current orientation of the surgical tool being within a threshold of the desired orientation, output a notification.
19. The apparatus of claim 15 , wherein the LIDAR scanner, the display screen, and the one or more processors reside on or in a wearable augmented reality device.
20. A method for guiding a surgical tool or a medical device into a subject, the method comprising:
receiving, by one or more processors, scanning data from a LIDAR scanner, the scanning data corresponding to an anatomical surface at a desired location;
identifying, by the one or more processors, one or more anatomical landmarks based on the received scanning data by applying one or more trained neural networks or machine learning databases trained using a set of anatomical surface scans and diagnostic images;
generating, by the one or more processors, an anatomical surface map of the anatomical surface of the desired location of the subject;
correlating, by the one or more processors, the anatomical surface map with one or more diagnostic images of at least the desired location of the subject;
determining, by the one or more processors, an anatomical entry point for insertion of the surgical tool or the medical device based on the correlation and based on at least one of the one or more anatomical landmarks identified by applying the one or more trained neural networks or machine learning databases; and
presenting, by the one or more processors, for display an output indicative of the anatomical entry point.
21. The method of claim 20 , wherein the one or more diagnostic images comprise CT or MRI images.
22. The method of claim 20 , wherein the output comprises a 2D or 3D virtual digital icon or image that is superimposed on a video of the desired location of the subject on a display screen of a computing device.
23. The method of claim 20 , further comprising:
determining, by the one or more processors, a desired orientation of the surgical tool or the medical device to follow at the anatomical entry point using an orientation sensor.
24. The method of claim 23 , further comprising:
generating, by the one or more processors, an output of the desired orientation of the surgical tool or the medical device on a display.