A team of researchers from the Centre for Nanoscale BioPhotonics (CNBP) in Australia has developed a new automated non-invasive technique for diagnosing eye surface cancer (ocular surface squamous neoplasia or OSSN). The technique has the potential to reduce the need for biopsies, prevent therapy delays and make treatment far more effective for patients.

Reported in a clinical journal ‘The Ocular Surface’, the innovative method comprises the custom-building of an advanced imaging microscope in association with state-of-the-art computing and artificial intelligence operation. The result is an automated system that is able to successfully identify between diseased and non-diseased eye tissue, in real-time, through a simple scanning process.

Next steps are to make this system practical and workable in a clinical setting. The researchers hope to do this by incorporating the system into a standard retinal camera setup, similar to that used by opticians and optometrists when undertaking regular eye examinations.