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. 25, 2026

Filed:

Apr. 12, 2024
Applicant:

Translational Imaging Innovations, Inc., Hickory, NC (US);

Inventors:

Bhavna Antony, Templestowe Lower, AU;

Eric L. Buckland, Hickory, NC (US);

Alexander E. Salmon, Garner, NC (US);

Robert C. Williams, Durham, NC (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/774 (2022.01); G06F 16/583 (2019.01); G06V 10/26 (2022.01); G06V 10/40 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06F 16/583 (2019.01); G06V 10/26 (2022.01); G06V 10/40 (2022.01); G06V 20/70 (2022.01); G06V 10/82 (2022.01); G06V 2201/03 (2022.01);
Abstract

A system for training and deployment of automated image segmentation algorithms is provided. The system includes a database; one or more user interfaces for curating collections of images and annotating images that are stored in the database; a structured library of annotations that form a dictionary for defining features within an image; a means for training a deep learning model according to a set of annotations applied to a collection of images; a means for deploying a plurality of deep learning models from the set of applied annotations, the plurality of deep learning models including a nested set of annotations such that a first model segments a first set of features within the image and a second model segments the first set of features of the first model and at least one additional feature of the image; and a means for transfer learning, wherein at least one of the plurality of deep learning models deployed for a first collection of images is used to accelerate retraining of the deep learning model for a second class of images defined by the second collection.


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