New Automation Technique That Could Detect Eye Cancer

Recently, researchers have succeeded in developing a non-invasive and automated technique that could help doctors diagnose cancer in the eye surface. This new technique will help reduce the need for biopsies and delays of therapy. It will also make that treatment much more effective for patients.

The combined power

Appeared in the Journal of  The Ocular Surface, the method is a combination of high-end computing, AI operation, and customized advanced image microscope. The end result is an automation system that is capable of identifying the difference between non-diseased eye tissues and diseased ones, just through a simple scan.

Abbas Habibalahi is a researcher as ARC (Australian Research Council) and the leader of this project. He has said:

According to Habibalahi, it is very important to detect OSSN early. The sooner the detection is the more curative and simple the treatment will be. For example, they could apply topical therapies where the old method will go for risky eye surgery or removal of the eye.
This group of researchers has combined the power of machine learning and microscopy to develop this technology.

How does it work?

Habibalahi said:

During this test, they have tested the tissue samples from more than 18 OSSN patients.

Follow Habibalahi, we also know that the team has succeeded in identifying diseased cells on all of the 18 patient's cases. All they needed to do is perform a quick scanning and the system will automatically identify all the OSSN warning signs.

A major plus point of this new technique is that it will make up for the need for expensive biopsy therapy. More than non-invasive and early detection, this technique is also capable of mapping and locate precisely the location of abnormal tissues on the patient's eyes.