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:
Dec. 03, 2024

Filed:

Jul. 06, 2022
Applicant:

Purdue Research Foundation, West Lafayette, IN (US);

Inventors:

Zhaxylyk A. Kudyshev, West Lafayette, IN (US);

Demid Sychev, West lafayette, IN (US);

Zachariah Olson Martin, West Lafayette, IN (US);

Simeon I. Bogdanov, West Lafayette, IN (US);

Xiaohui Xu, West Lafayette, IN (US);

Alexander Kildishev, West Lafayette, IN (US);

Alexandra Boltasseva, West Lafayette, IN (US);

Vladimir Shalaev, West Lafayette, IN (US);

Assignee:

Purdue Research Foundation, West Lafayette, IN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 3/40 (2024.01); G02B 21/00 (2006.01); G06T 3/4046 (2024.01); G06T 3/4053 (2024.01);
U.S. Cl.
CPC ...
G06T 3/4053 (2013.01); G02B 21/0072 (2013.01); G06T 3/4046 (2013.01);
Abstract

A method of providing super-resolved images of a photon emitting particle is disclosed, which includes providing a machine-learning (ML) platform, wherein the ML platform is configured to receive pixel-based sparse autocorrelation data and generate a predicted super-resolved image of a photon emitting particle, receiving photons from the photon emitting particle by two or more photon detectors, each generating an electrical pulse associated with receiving an incident photon thereon, generating sparse autocorrelation data from the two or more photon detectors for each pixel within an image area, and inputting the pixel-based sparse autocorrelation data to the ML platform, thereby generating a predicted super-resolved image of the imaging area, wherein the resolution of the super-resolved image is improved by √n as compared to a classical optical microscope limited by Abbe diffraction limit.


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