The cameras integrated into today’s smartphones can be used to take photos of people or sceneries, but not the microscopic images.

A research team from the University of California, Los Angeles, United States has revealed that deep learning (a form of AI) can distinctively increase microscopic resolutions in photos taken via smartphones.

An attachment has been developed and placed over the smartphone lens to increase the resolution power of the clicked images, up to one-millionth of a meter. The quality is so high that it can match the images taken from lab grade microscopes.

As mentioned in ACS Photonics journal, this technique uses inexpensive add-ons to produce the image with a 3-D printer. This high-end novel diagnostic tool can be used in telemedicine, global health and diagnostics related applications by reaching even resource-poor regions.

Aydogan Ozcan, the professor cum lead investigator of this study said, "Using deep learning, we set out to bridge the gap in image quality between inexpensive mobile phone-based microscopes and gold-standard bench-top microscopes that use high-end lenses; we believe that our approach is broadly applicable to other low-cost microscopy systems that use, for example, inexpensive lenses or cameras, and could facilitate the replacement of high-end bench-top microscopes with cost-effective, mobile alternatives.”