US 11,657,502 B2
Systems and methods for segmentation of anatomical structures for image-guided surgery
Junning Li, San Jose, CA (US); Pechin Chien Pau Lo, Santa Clara, CA (US); Ahmed Taha, Hyattsville, MD (US); and Tao Zhao, Sunnyvale, CA (US)
Assigned to INTUITIVE SURGICAL OPERATIONS, INC., Sunnyvale, CA (US)
Filed by INTUITIVE SURGICAL OPERATIONS, INC., Sunnyvale, CA (US)
Filed on Dec. 15, 2020, as Appl. No. 17/122,788.
Application 17/122,788 is a continuation of application No. 16/289,103, filed on Feb. 28, 2019, granted, now 10,885,630.
Claims priority of provisional application 62/637,232, filed on Mar. 1, 2018.
Claims priority of provisional application 62/638,831, filed on Mar. 5, 2018.
Prior Publication US 2021/0142475 A1, May 13, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/00 (2017.01); A61B 34/10 (2016.01); G06T 7/12 (2017.01); A61B 34/20 (2016.01)
CPC G06T 7/0012 (2013.01) [A61B 34/10 (2016.02); A61B 34/20 (2016.02); G06T 7/12 (2017.01); A61B 2034/2065 (2016.02); G06T 2207/30101 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for image segmentation, the method comprising:
receiving volumetric image data for an anatomical region;
generating a first volumetric patch from the volumetric image data;
generating a second volumetric patch from the first volumetric patch by weighting a plurality of volumetric units in the first volumetric patch, wherein weighting at least one of the plurality of volumetric units includes applying a weight based on a distance of the at least one of the plurality of volumetric units from a volumetric unit with a foreground structure classification in the first volumetric patch;
receiving the second volumetric patch as an input to a convolutional neural network;
within the convolutional neural network, conducting a down-sampling filter process; and
within the convolutional neural network, conducting an up-sampling filter process.