US 12,478,444 B2
Systems and methods for localization based on machine learning
David B. Camarillo, Aptos, CA (US); David Eng, Saratoga, CA (US); and Jake Sganga, Laguna Beach, CA (US)
Assigned to The Board of Trustees of the Leland Stanford Junior University, Palo Alto, CA (US)
Filed by The Board of Trustees of the Leland Stanford Junior University, Palo Alto, CA (US)
Filed on Mar. 20, 2020, as Appl. No. 16/826,114.
Claims priority of provisional application 62/821,993, filed on Mar. 21, 2019.
Prior Publication US 2020/0297444 A1, Sep. 24, 2020
Int. Cl. A61B 34/00 (2016.01); A61B 1/267 (2006.01); A61B 34/10 (2016.01); A61B 34/20 (2016.01); A61B 34/37 (2016.01); G06N 3/02 (2006.01); G16H 30/00 (2018.01); G16H 50/00 (2018.01); A61B 34/30 (2016.01)
CPC A61B 34/70 (2016.02) [A61B 1/2676 (2013.01); A61B 34/10 (2016.02); A61B 34/20 (2016.02); A61B 34/37 (2016.02); G06N 3/02 (2013.01); G16H 30/00 (2018.01); G16H 50/00 (2018.01); A61B 2034/102 (2016.02); A61B 2034/301 (2016.02)] 13 Claims
OG exemplary drawing
 
1. A system for localization within a luminal network, the system comprising:
an instrument comprising:
an elongate body configured to be inserted into the luminal network, and
an imaging device positioned on a distal portion of the elongate body;
at least one computer-readable memory having stored thereon executable instructions; and
one or more processors in communication with the at least one computer-readable memory and configured to execute the instructions to cause the system to at least:
receive, from the imaging device, image data comprising an image captured when the elongate body is within the luminal network, the image depicting one or more branchings of the luminal network;
access a machine learning model configured to:
identify the one or more branchings from the image data;
compare the one or more branchings from the image data with one or more virtual branchings in a repository to determine a match;
determine a location within the luminal network corresponding to the match; and
output a position of the distal portion of the instrument; and
determine, based on the position of the distal portion of the instrument output from the machine learning model, a location of the distal portion of the elongate body within the luminal network.