Deep learning model for noise reduction in low SNR imaging conditions
US12008737B2 · kind B2 · utility
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20Claims
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Key dates
| Filing date | Aug 5, 2021 |
| Grant date | Jun 11, 2024 |
| Priority date | — |
| Expiry date | Mar 22, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30024
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments disclosed herein are generally related to a system for noise reduction in low signal to noise ratio imaging conditions. A computing system obtains a set of images of a specimen. The set of images includes at least two images of the specimen. The computing system inputs the set of images of the specimen into a trained denoising model. The trained denoising model is configured to output a single denoised image of the specimen. The computing system receives, as output from the trained denoising model, a single denoised image of the specimen.
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