Machine learning assisted adaptive optics for microscopy imaging systems
This new generation machine learning embedded microscope control system ensures outstanding optical performance when imaging deep inside cells and tissues. The adaptive optics removes the optical distortions introduced by the specimen and is applicable to a wide range of microscopes.
Applications: Microscopy, imaging, system improvement
| Features | Benefits |
|---|---|
| Uses hardware (adaptive optics) correction, not data post-processing | Provides a higher level of data integrity, particularly important for scientific research applications |
| Fewer sample exposures than traditional counterparts | Lower risk of photodamage and faster processing |
| Optical feedback optimisation process | Optical correction means that optimal information is retrieved before any image post-processing |
| Bespoke design of data acquisition for better information conditioning | Information is suitably encoded for a more efficient information extraction and thus ensures the method high performance |
| A specially designed neural network uses physical knowledge | The machine learning algorithm can therefore be smaller, for increased ease of training and operation |
Awaiting patent and Available For
- Co-development
- Consulting
- Licensing