US 11,869,189 B2
Systems and methods for automated digital image content extraction and analysis
Russell H. Amundson, Merion Station, PA (US); Saurabh Bhargava, Eden Prairie, MN (US); Rama Krishna Singh, Greater Noida (IN); Ravi Pande, Noida (IN); Vishwakant Gupta, Noida (IN); Destiny L. Babjack, Bethel Park, PA (US); Gaurav Mantri, Gurugram (IN); Abhinav Agrawal, Gulabpura (IN); and Sapeksh Suman, Greater Noida West (IN)
Assigned to UnitedHealth Group Incorporated, Minnetonka, MN (US)
Filed by UnitedHealth Group Incorporated, Minnetonka, MN (US)
Filed on Mar. 4, 2021, as Appl. No. 17/191,921.
Claims priority of provisional application 62/991,686, filed on Mar. 19, 2020.
Prior Publication US 2021/0295503 A1, Sep. 23, 2021
Int. Cl. G06T 7/00 (2017.01); G16H 40/67 (2018.01); G16H 30/40 (2018.01); G06T 7/11 (2017.01); G06T 7/33 (2017.01); G06T 7/90 (2017.01); G06T 7/70 (2017.01); G06T 3/60 (2006.01); G06F 18/24 (2023.01); G06F 18/2137 (2023.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01)
CPC G06T 7/0014 (2013.01) [G06F 18/21375 (2023.01); G06F 18/24 (2023.01); G06T 3/60 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/337 (2017.01); G06T 7/70 (2017.01); G06T 7/90 (2017.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G16H 30/40 (2018.01); G16H 40/67 (2018.01); G06T 2207/10024 (2013.01); G06T 2207/20024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30012 (2013.01); G06T 2207/30068 (2013.01); G06T 2207/30088 (2013.01); G06T 2207/30096 (2013.01)] 21 Claims
OG exemplary drawing
 
1. An image analysis system configured for identifying characteristics of features present within an image, the image analysis system comprising:
one or more non-transitory memory storage areas; and
one or more processors collectively configured to:
receive image data comprising at least one embedded image;
identify image analysis criteria stored within the one or more non-transitory memory storage areas, wherein the image analysis criteria comprises at least one feature identification model and at least one scaling model;
apply the at least one feature identification model to the at least one embedded image to identify a plurality of included features represented within the at least one embedded image, wherein the plurality of included features comprises at least one reference feature;
apply the at least one scaling model, based at least in part on the at least one reference feature, to establish an absolute measurement scale for the at least one embedded image;
measure, via the absolute measurement scale, a distance between locations within the at least one embedded image and associated with at least two of the plurality of included features; and
determine, based at least in part on the image analysis criteria and the distance between the at least two of the plurality of included features, image characteristics for the image data.