US 12,087,007 B2
Vision-based 6DOF camera pose estimation in bronchoscopy
Mali Shen, Sunnyvale, CA (US); and Menglong Ye, Mountain View, CA (US)
Filed by Auris Health, Inc., Redwood City, CA (US)
Filed on Mar. 31, 2021, as Appl. No. 17/219,804.
Prior Publication US 2022/0319031 A1, Oct. 6, 2022
Int. Cl. G06T 7/70 (2017.01); A61B 1/267 (2006.01); A61B 6/12 (2006.01); G06N 3/04 (2023.01); G06T 7/33 (2017.01); G06T 7/55 (2017.01); G16H 30/40 (2018.01); G16H 50/50 (2018.01); A61B 90/00 (2016.01)
CPC G06T 7/70 (2017.01) [A61B 1/2676 (2013.01); A61B 6/12 (2013.01); G06N 3/04 (2013.01); G06T 7/33 (2017.01); G06T 7/55 (2017.01); G16H 30/40 (2018.01); G16H 50/50 (2018.01); A61B 2090/3762 (2016.02); G06T 2207/10016 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/10068 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30244 (2013.01)] 29 Claims
OG exemplary drawing
 
1. A method, comprising:
generating a camera pose representative of a spatial location within an internal anatomical structure and capturing video image data of the internal anatomical structure, comprising:
transforming the video image data into a first depth map of the internal anatomical structure, via a mapping function;
receiving a plurality of second depth maps based at least in part on transformed computed tomography (CT) image data, each of the second depth maps representing a virtual model of the internal anatomical structure;
identifying one of the plurality of second depth maps that has a highest similarity of shape to the first depth map; and
generating the camera pose based at least in part on the identified one of the plurality of second depth maps, including estimating camera pose parameters by solving a transformation matrix between a 3D point cloud of the virtual model of the internal anatomical structure and a point cloud inverse projected from the first depth map.