Deep-learning based structure reconstruction method and apparatus
US11403735B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 2018 |
| Grant date | Aug 2, 2022 |
| Priority date | — |
| Expiry date | Feb 12, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method for structure simulation for super-resolution fluorescence microscopy, the method including receiving a first image having a first resolution, which is indicative of a distribution of fluorophores; applying a Markov model to the fluorophores to indicate an emission state of the fluorophores; generating a plurality of second images, having the first resolution, based on the first image and the Markov model; adding DC background to the plurality of second images to generate a plurality of third images, having the first resolution; downsampling the plurality of third images to obtain a plurality of fourth images, which have a second resolution, lower than the first resolution; and generating a time-series, low-resolution images by adding noise to the plurality of fourth images. The time-series, low-resolution images have the second resolution.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.