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. 20, 2026

Filed:

Oct. 14, 2021
Applicants:

Life Technologies Corporation, Carlsbad, CA (US);

Cellomics, Inc., Carlsbad, CA (US);

Inventors:

Nicolas Rognin, Bothell, WA (US);

Larry Rystrom, Mill Creek, CA (US);

Ognjen Golub, Eugene, OR (US);

Jonathan Paullin, Kirkland, WA (US);

Nicholas Diliani, Mountlake Terrace, WA (US);

Kim Ippolito, South Park, PA (US);

Assignees:

LIFE TECHNOLOGIES CORPORATION, Carlsbad, CA (US);

CELLOMICS, INC, Waltham, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01N 15/1434 (2024.01); G06N 3/048 (2023.01); G06N 3/08 (2023.01); G06T 3/40 (2006.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01); G01N 15/14 (2006.01);
U.S. Cl.
CPC ...
G01N 15/1434 (2013.01); G06N 3/048 (2023.01); G06N 3/08 (2013.01); G06T 3/40 (2013.01); G06V 10/82 (2022.01); G06V 20/695 (2022.01); G01N 2015/1452 (2013.01); G01N 2015/1486 (2013.01);
Abstract

Systems and methods for autofocus using artificial intelligence include (i) capturing a plurality of monochrome images over a nominal focus range, (ii) identifying one or more connected components within each monochrome image, (iii) sorting the identified connected components based on a number of pixels associated with each connected component, (iv) generating a focus quality estimate of at least a portion of the sorted connected components using a machine learning module, and (iv) calculating a target focus position based on the focus quality estimate of the evaluated connected components. The calculated target focus position can be used to perform cell counting using artificial intelligence, such as by (i) generating a seed likelihood image and a whole cell likelihood image based on output—a convolutional neural network and (ii) generating a mask indicative quantity and/or pixel locations of objects based on the seed likelihood image.


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