US 12,224,066 B2
Deep learning models for region of interest determination
Mustafa I. Jaber, Los Angeles, CA (US); Bing Song, La Canada, CA (US); Christopher W. Szeto, Culver City, CA (US); Stephen Charles Benz, Culver City, CA (US); Shahrooz Rabizadeh, Culver City, CA (US); and Liudmila A. Beziaeva, Culver City, CA (US)
Assigned to NantOmics, LLC, Culver City, CA (US); NantHealth, Inc., Culver City, CA (US); and NantCell, Inc., Culver City, CA (US)
Filed by NantOmics, LLC, Culver City, CA (US); NantHealth, Inc., Culver City, CA (US); and NantCell, Inc., Culver City, CA (US)
Filed on Feb. 2, 2024, as Appl. No. 18/431,151.
Application 18/431,151 is a continuation of application No. 17/381,675, filed on Jul. 21, 2021, granted, now 11,948,687.
Claims priority of provisional application 63/192,508, filed on May 24, 2021.
Prior Publication US 2024/0170149 A1, May 23, 2024
Int. Cl. G16H 50/20 (2018.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01)
CPC G16H 50/20 (2018.01) [G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 2207/30096 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An image processing system comprising:
at least one computer readable non-transitory memory storing software instructions, a first description of a structure type of a first region type, and a second description of a structure type of a second region type that is different than the first region type; and
at least one processing circuitry coupled with the memory and that performs, upon execution of the software instructions, operations of:
partitioning a digital image into a set of areas;
identifying a structure type of each area of the digital image;
determining regions of interest in the digital image by applying a classifier able to determine regions of interest based on structure types of the set of areas in the digital image, including determining a first region of interest in the image by matching the set of areas of the image with the first description of the first region type, and determining a second region of interest in the image by matching the set of areas of the image with the second description of the second region type; and
presenting the regions of interest with different visual appearances indicating respective region types.