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. 30, 2024

Filed:

Jan. 07, 2021
Applicants:

Jason Tyler Smith, Troy, NY (US);

Ruoyang Yao, Elmhurst, NY (US);

Xavier Intes, Schenectady, NY (US);

Pingkun Yan, Clifton Park, NY (US);

Marien Ochoa-mendoza, Troy, NY (US);

Inventors:

Jason Tyler Smith, Troy, NY (US);

Ruoyang Yao, Elmhurst, NY (US);

Xavier Intes, Schenectady, NY (US);

Pingkun Yan, Clifton Park, NY (US);

Marien Ochoa-Mendoza, Troy, NY (US);

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06N 3/088 (2023.01); G06N 3/045 (2023.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06N 3/045 (2023.01); G06N 3/088 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01);
Abstract

One embodiment provides an apparatus for fluorescence lifetime imaging (FLI). The apparatus includes a deep neural network (DNN). The DNN includes a first convolutional layer, a plurality of intermediate layers and an output layer. The first convolutional layer is configured to receive FLI input data. Each intermediate layer is configured to receive a respective intermediate input corresponding to an output of a respective prior layer. Each intermediate layer is further configured to provide a respective intermediate output related to the received respective intermediate input. The output layer is configured to provide estimated FLI output data corresponding to the received FLI input data. The DNN is trained using synthetic data.


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