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:
Aug. 24, 2021

Filed:

Jul. 28, 2017
Applicant:

Stryker European Operations Limited, Carrigtwohill, IE;

Inventors:

Lina Gurevich, Vancouver, CA;

Lori Ann Swalm, Dallas, TX (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/0275 (2006.01); G06T 7/557 (2017.01); G06K 9/62 (2006.01); A61B 5/026 (2006.01); A61B 5/00 (2006.01); G06K 9/66 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
A61B 5/0275 (2013.01); A61B 5/0261 (2013.01); A61B 5/7232 (2013.01); A61B 5/7267 (2013.01); A61B 5/743 (2013.01); G06K 9/6218 (2013.01); G06K 9/6219 (2013.01); G06K 9/6223 (2013.01); G06K 9/6274 (2013.01); G06K 9/66 (2013.01); G06T 7/0012 (2013.01); G06T 7/557 (2017.01); A61B 2576/00 (2013.01); G06K 2209/05 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30104 (2013.01);
Abstract

Methods and systems for characterizing tissue of a subject include acquiring and receiving data for a plurality of time series of fluorescence images, identifying one or more attributes of the data relevant to a clinical characterization of the tissue, and categorizing the data into clusters based on the attributes such that the data in the same cluster are more similar to each other than the data in different clusters, wherein the clusters characterize the tissue. The methods and systems further include receiving data for a subject time series of fluorescence images, associating a respective cluster with each of a plurality of subregions in the subject time series of fluorescence images, and generating a subject spatial map based on the clusters for the plurality of subregions in the subject time series of fluorescence images. The generated spatial maps may then be used as input for tissue diagnostics using supervised machine learning.


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