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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 11908548 B1

PDFFull Text
Date of Patent:
Feb. 20, 2024

Filed:

May. 27, 2022

Training data generation for artificial intelligence-based sequencing

Applicant:

Illumina, Inc., San Diego, CA (US);

Inventors:

Anindita Dutta, San Francisco, CA (US);

Dorna Kashefhaghighi, San Francisco, CA (US);

Amirali Kia, San Mateo, CA (US);

Assignee:

Illumina, Inc., San Diego, CA (US);

Attorney:

Keller Preece PLLC

Primary Examiner:

Juan A Torres

Int. Cl.
CPC ...
G16B 40/20 (2019.01); G06F 16/907 (2019.01); G16B 40/00 (2019.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06N 3/084 (2023.01); G06F 18/23 (2023.01); G06F 18/24 (2023.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 18/21 (2023.01); G06F 18/2415 (2023.01); G06F 18/2431 (2023.01); G06F 18/23211 (2023.01); G06N 7/01 (2023.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01); G06V 10/44 (2022.01); G06V 10/26 (2022.01); G06V 10/98 (2022.01); G06V 20/69 (2022.01); G06V 10/75 (2022.01); G06N 5/046 (2023.01); G06V 20/40 (2022.01);
U.S. Cl.
CPC ...
G16B 40/20 (2019.02); G06F 16/907 (2019.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 18/23 (2023.01); G06F 18/23211 (2023.01); G06F 18/24 (2023.01); G06F 18/2415 (2023.01); G06F 18/2431 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06N 3/084 (2013.01); G06N 7/01 (2023.01); G06V 10/267 (2022.01); G06V 10/454 (2022.01); G06V 10/751 (2022.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/7784 (2022.01); G06V 10/82 (2022.01); G06V 10/993 (2022.01); G06V 20/69 (2022.01); G16B 40/00 (2019.02); G06N 5/046 (2013.01); G06V 20/47 (2022.01);
Abstract

The technology disclosed relates to generating ground truth training data to train a neural network-based template generator for cluster metadata determination task. In particular, it relates to accessing sequencing images, obtaining, from a base caller, a base call classifying each subpixel in the sequencing images as one of four bases (A, C, T, and G), generating a cluster map that identifies clusters as disjointed regions of contiguous subpixels which share a substantially matching base call sequence, determining cluster metadata based on the disjointed regions in the cluster map, and using the cluster metadata to generate the ground truth training data for training the neural network-based template generator for the cluster metadata determination task.

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