A pixel super-resolution method can increase the sharpness of images produced by digital microscopy. The wavelength scanning approach developed by the California NanoSystems Institute at University of California (Los Angeles) uses a device that captures a stack of digital images of the same specimen, each with a slightly different wavelength of light. A newly devised algorithm divides the pixels in each captured image into a number of smaller pixels, resulting in a higher-resolution digital image of the specimen.

Wavelength scanning super-resolution works on both colorless and dye-stained samples.“These results mean we can see and inspect large samples with finer details at the sub-micron level,” says Aydogan Ozcan , lead researcher and Chancellor’s Professor of Electrical Engineering and Bioengineering at the UCLA Henry Samueli School of Engineering and Applied Science. “We have applied this method to lens-based conventional microscopes, as well as our lensless on-chip microscopy systems that create microscopic images using holograms, and it works across all these platforms.”

The benefits of this method may be significant in pathology, where rapid microscopic imaging of large numbers of tissue or blood cells is key to diagnosing diseases such as cancer. The specimens used in the study were blood samples, used to screen for various diseases, and Papanicolaou tests, which are used to screen for cervical cancer.

Ozcan said that wavelength scanning super-resolution works on both colorless and dye-stained samples. The entire apparatus fits on a desktop, so its size and convenience could be of great benefit to doctors and scientists using microscopes in resource-limited settings such as clinics in developing countries.