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:
Feb. 11, 2025

Filed:

Sep. 30, 2021
Applicant:

Fei Company, Hillsboro, OR (US);

Inventors:

Ondrej Machek, Brno, CZ;

Pavel Potocek, Eindhoven, CZ;

Tereza Konečná, Brno, CZ;

Assignee:

FEI Company, Hillsboro, OR (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/69 (2022.01); G01N 23/04 (2018.01); G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06T 3/4053 (2024.01); G06V 10/22 (2022.01);
U.S. Cl.
CPC ...
G06V 20/695 (2022.01); G06F 18/214 (2023.01); G06N 3/08 (2013.01); G06T 3/4053 (2013.01); G06V 10/235 (2022.01); G06V 20/693 (2022.01); G01N 23/04 (2013.01);
Abstract

Disclosed herein are charged particle microscopy (CPM) support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, a CPM support apparatus may include: first logic to cause a CPM to generate a single image of a first portion of a specimen; second logic to generate a first mask based on one or more regions-of-interest provided by user annotation of the single image; and third logic to train a machine-learning model using the single image and the one or more regions-of-interest. The first logic may cause the CPM to generate multiple images of corresponding multiple additional portions of the specimen, and the second logic may, after the machine-learning model is trained using the single image and the one or more regions-of-interest, generate multiple masks based on the corresponding images of the additional portions of the specimen using the machine-learning model without retraining.


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