The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 09, 2024

Filed:

Mar. 04, 2021
Applicant:

Unitedhealth Group Incorporated, Minnetonka, MN (US);

Inventors:

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;

Sapeksh Suman, Greater Noida West, IN;

Assignee:

UnitedHealth Group Incorporated, Minnetonka, MN (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
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);
U.S. Cl.
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);
Abstract

Systems and methods are configured to extract images from provided source data files and to preprocess such images for content-based image analysis. An image analysis system applies one or more machine-learning based models for identifying specific features within analyzed images, and for determining one or more measurements based at least in part on the identified features. Such measurements may be embodied as absolute measurements for determining an absolute distance between features, or relative measurements for determining a relative relationship between features. The determined measurements are input into one or more machine-learning based models for determining a classification for the image.


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