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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.

Patent No.:

US 12019008 B1

PDFFull Text
Date of Patent:
Jun. 25, 2024

Filed:

Dec. 12, 2022

Morphometric detection of malignancy associated change

Applicant:

Visiongate, Inc., Woodinville, WA (US);

Inventors:

Michael G. Meyer, Phoenix, AZ (US);

Laimonas Kelbauskas, Chandler, AZ (US);

Rahul Katdare, Bothell, WA (US);

Daniel J. Sussman, Auburn, CA (US);

Timothy Bell, Phoenix, AZ (US);

Alan C. Nelson, Gig Harbor, WA (US);

Assignee:

VISIONGATE, INC., Woodinville, WA (US);

Attorney:

Seed IP Law Group LLP

Primary Examiner:

Nay A Maung

Assistant Examiner:

Jose M Torres

Int. Cl.
CPC ...
G01N 15/1433 (2024.01); G01N 15/14 (2006.01); G01N 15/1434 (2024.01); G01N 33/483 (2006.01); G06F 18/214 (2023.01); G06F 18/243 (2023.01); G06T 7/00 (2017.01); G06T 11/00 (2006.01); G06V 10/40 (2022.01); G06V 10/762 (2022.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G01N 15/1433 (2024.01); G01N 15/147 (2013.01); G01N 33/4833 (2013.01); G06F 18/2148 (2023.01); G06F 18/24317 (2023.01); G06T 7/0012 (2013.01); G06T 11/003 (2013.01); G06V 10/40 (2022.01); G06V 10/762 (2022.01); G06V 10/7747 (2022.01); G01N 2015/1445 (2013.01); G06T 2207/10101 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/03 (2022.01);
Abstract

A method for a system and method for morphometric detection of malignancy associated change (MAC) is disclosed including the acts of obtaining a sample; imaging cells to produce 3D cell images for each cell; measuring a plurality of different structural biosignatures for each cell from its 3D cell image to produce feature data; analyzing the feature data by first using cancer case status as ground truth to supervise development of a classifier to test the degree to which the features discriminate between cells from normal or cancer patients; using the analyzed feature data to develop classifiers including, a first classifier to discriminate normal squamous cells from normal and cancer patients, a second classifier to discriminate normal macrophages from normal and cancer patients, and a third classifier to discriminate normal bronchial columnar cells from normal and cancer patients.

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