Label-free bio-aerosol sensing using mobile microscopy and deep learning
US11262286B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 24, 2020 |
| Grant date | Mar 1, 2022 |
| Priority date | — |
| Expiry date | Aug 8, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A label-free bio-aerosol sensing platform and method uses a field-portable and cost-effective device based on holographic microscopy and deep-learning, which screens bio-aerosols at a high throughput level. Two different deep neural networks are utilized to rapidly reconstruct the amplitude and phase images of the captured bio-aerosols, and to output particle information for each bio-aerosol that is imaged. This includes, a classification of the type or species of the particle, particle size, particle shape, particle thickness, or spatial feature(s) of the particle. The platform was validated using the label-free sensing of common bio-aerosol types, e.g., Bermuda grass pollen, oak tree pollen, ragweed pollen, Aspergillus spore, and Alternaria spore and achieved >94% classification accuracy. The label-free bio-aerosol platform, with its mobility and cost-effectiveness, will find several applications in indoor and outdoor air quality monitoring.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.