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:
May. 07, 2019

Filed:

Jun. 10, 2016
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Murray A. Reicher, Rancho Santa Fe, CA (US);

Jon T. DeVries, Cary, NC (US);

Michael W. Ferro, Chicago, IL (US);

Marwan Sati, Mississauga, CA;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2017.01); G06F 19/00 (2018.01); G16H 50/50 (2018.01); G16H 15/00 (2018.01); G16H 50/20 (2018.01); A61B 5/00 (2006.01); G06F 3/0488 (2013.01); G06K 9/62 (2006.01); A61B 34/10 (2016.01); G06F 3/0482 (2013.01); G06N 99/00 (2019.01); A61B 10/02 (2006.01); G06T 11/00 (2006.01); G06F 17/24 (2006.01); G06F 17/27 (2006.01); G06K 9/66 (2006.01); A61B 90/00 (2016.01); A61B 5/01 (2006.01); A61B 5/0402 (2006.01); A61B 5/055 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 5/0033 (2013.01); A61B 5/7267 (2013.01); A61B 10/02 (2013.01); A61B 34/10 (2016.02); G06F 3/0482 (2013.01); G06F 3/0488 (2013.01); G06F 17/241 (2013.01); G06F 17/2705 (2013.01); G06F 19/00 (2013.01); G06F 19/321 (2013.01); G06F 19/36 (2013.01); G06K 9/627 (2013.01); G06K 9/6227 (2013.01); G06K 9/6232 (2013.01); G06K 9/6256 (2013.01); G06K 9/6262 (2013.01); G06K 9/6269 (2013.01); G06K 9/66 (2013.01); G06N 99/005 (2013.01); G06T 7/0014 (2013.01); G06T 11/008 (2013.01); G16H 15/00 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); A61B 5/0077 (2013.01); A61B 5/015 (2013.01); A61B 5/0402 (2013.01); A61B 5/055 (2013.01); A61B 5/4312 (2013.01); A61B 5/441 (2013.01); A61B 2034/108 (2016.02); A61B 2090/373 (2016.02); A61B 2090/374 (2016.02); A61B 2090/378 (2016.02); A61B 2090/3762 (2016.02); G06K 2209/051 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30008 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30052 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30068 (2013.01); G06T 2207/30088 (2013.01);
Abstract

Methods and systems for automatically analyzing clinical images using models developed using machine learning. One system includes a server having an electronic processor and an interface for communicating with at least one data source. The electronic processor is configured to receive training information from the at least one data source over the interface. The training information includes a plurality of images and graphical reporting associated with each of the plurality of images. Each graphical reporting includes a graphical marker designating a portion of one of the plurality of images and diagnostic information associated with the portion of the one of the plurality of images. The electronic processor is also configured to perform machine learning to develop a model using the training information. The electronic processor is also configured to receive an image for analysis and automatically process the image using the model to generate a diagnosis for the image.


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