Methods and systems for registering preoperative image data to intraoperative image data of a scene, such as a surgical scene

1. A method of registering medical scan data of a patient to intraoperative image data of a scene including the patient, the method comprising:

determining one or more characteristics of the intraoperative image data;

based on the determined one or more characteristics, determining that (a) a first portion of the intraoperative image data corresponds to a first type of anatomy the patient and (b) a second portion of the intraoperative image data corresponds to a second type of anatomy of the patient, wherein the first type of anatomy corresponds to the medical scan data; and

registering the preoperative image data to the first portion of the intraoperative image data, wherein registering the preoperative image data to the first portion of the intraoperative image data includes—

utilizing a registration algorithm to compute a registration transform between the preoperative image data and the first portion of the intraoperative image data, wherein utilizing the registration algorithm includes computing a plurality of point-to-point correspondences between first points in the intraoperative image data and second points in the preoperative image data; and

adjusting the registration algorithm based on the determined one or more characteristics, wherein adjusting the registration algorithm includes adjusting weights of the point-to-point correspondences based on a determination that the first points in the point-to-point correspondences correspond to the first type of anatomy or the second type of anatomy.

2. The method of claim 1 wherein the preoperative image data is computerized tomography (CT) scan data.

3. The method of claim 1 wherein the first type of anatomy is bone.

4. The method of claim 1 wherein adjusting the weights of the point-to-point correspondences includes (a) increasing the weights of ones of the point-to-point correspondences including first points corresponding to the first type of anatomy and (b) decreasing weights of ones of the point-to-point correspondences including first points corresponding to the second type of anatomy.

5. The method of claim 1 wherein the one or more characteristics include at least one of color information, angular information, and specular information.

6. The method of claim 1 wherein the one or more characteristics include at least one of hue, saturation, and value information.

7. The method of claim 1 wherein the intraoperative image data includes light-field image data of the scene.

8. The method of claim 7 wherein the intraoperative image data further includes image data from a depth camera including depth data of the scene, wherein determining the one or more characteristics of the image data includes determining the one or more characteristics based on the light-field image data, and wherein registering the preoperative image data to the first portion of the intraoperative image data includes registering the depth data to the preoperative image data.

9. The method of claim 1 wherein the method further comprises:

generating a three-dimensional (3D) image of the scene based on the intraoperative image data; and

displaying the medical scan data over the first type of anatomy in the 3D image of the scene.

10. A mediated-reality system, comprising:

a camera array including a plurality of cameras configured to capture intraoperative image data of a scene including a patient;

an input controller configured to control a position and orientation of a virtual perspective of the scene;

a processing device communicatively coupled to the camera array and the input controller, wherein the processing device is configured to—

synthesize a virtual image corresponding to the virtual perspective based on the intraoperative image data;

receive medical scan data of the patient;

determine one or more characteristics of the intraoperative image data;

based on the determined one or more characteristics, determine that (a) a first portion of the intraoperative image data corresponds to a first type of anatomy the patient and (b) a second portion of the intraoperative image data corresponds to a second type of anatomy of the patient, wherein the first type of anatomy corresponds to the medical scan data;

register the preoperative image data to the first portion of the intraoperative image data by—

utilizing a registration algorithm to compute a plurality of point-to-point correspondences between first points in the intraoperative image data and second points in the preoperative image data; and

adjusting weights of the point-to-point correspondences based on the determination that the first points in the point-to-point correspondences correspond to the first type of anatomy or the second type of anatomy; and

overlay the medical scan data over the first type of anatomy in the virtual image.

11. The mediated-reality system of claim 10 wherein the scene is a surgical scene, wherein the first type of anatomy is a spine of the patient, and wherein the medical scan data is computerized tomography (CT) scan data.

12. The mediated-reality system of claim 10 wherein the one or more characteristics include at least one of hue, saturation, and value information, and wherein the intraoperative image data includes light-field image data of the scene.

13. The mediated-reality system of claim 10 wherein the processor is further configured to adjust the weights of the point-to-point correspondences by (a) increasing the weights of ones the point-to-point correspondences including first points corresponding to the first type of anatomy and (b) decreasing the weights of ones of the point-to-point correspondences including first points corresponding to the second type of anatomy.

14. A method of registering previously-captured image data to real-time image data of a scene, the method comprising:

receiving the real-time image data including light-field image data of the scene;

generating a three-dimensional (3D) virtual view of the scene based on the real-time image data, wherein the scene includes an object of interest, and wherein the previously-captured image data corresponds to the object of interest;

determining one or more characteristics of the light-field image data;

based on the determined one or more characteristics, determining that (a) a first portion of the real-time image data likely corresponds to the object of interest and (b) a second portion of the real-time image data likely does not correspond to the object of interest;

registering the previously-captured image data to the first portion of the real-time image data, wherein registering the previously-captured image data to the first portion of the real-time image data includes—

utilizing a registration algorithm to compute a plurality of point-to-point correspondences between first points in the real-time image data and second points in the previously-captured image data; and

adjusting weights of the point-to-point correspondences based on the determination that the first points in the point-to-point correspondences likely correspond to the object of interest; and

displaying the previously-captured image data over the object of interest in the 3D virtual view of the scene.

15. The method of claim 14 wherein the one or more characteristics include at least one of color information, angular information, and specular information.

16. The method of claim 14 wherein determining that the first portion of the real-time image data likely corresponds to the object of interest includes determining that the light-field image data corresponding to the first portion of the real-time image data has a lower saturation than other portions of the light-field image data.