The Dry Eye Zone

Rebecca's Blog


Study: Another dry eye diagnostic

No comment. I'm permanently jaded and confused after reading about so many new and exciting dry eye diagnostics that I can't keep them straight. Somebody wake me up when one gets adopted for use in a major clinical trial.

Y'all know that one of my hangups is differentiation between aqueous tear deficiency, meibomian gland dysfunction and other ocular surface disease. So from my perspective, how dry your surface is at 2:38pm on December 10th, 2007 does not tell ME a whole heck of a lot except that, if it's awfully dry, it ought to add something to the urgency of finding out WHY in order to treat it appropriately.

On the other hand, a key use of a standardized, reliable dry eye diagnostic would be for what I really, really, really want to see: a really, really good epidemiological study of dry eye. So my first question about these diagnostics is, how long does it take, how much does it cost and how much training does it take to perform reliably?

Automatic dry eye detection.
Yedidya T, Hartley R, Guillon JP, Kanagasingam Y.
Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv. 2007;10(Pt 1):792-9.

Dry Eye Syndrome is a common disease in the western world, with effects from uncomfortable itchiness to permanent damage to the ocular surface. Nevertheless, there is still no objective test that provides reliable results. We have developed a new method for the automated detection of dry areas in videos taken after instilling fluorescein in the tear film. The method consists of a multi-step algorithm to first locate the iris in each image, then align the images and finally analyze the aligned sequence in order to find the regions of interest. Since the fluorescein spreads on the ocular surface of the eye the edges of the iris are fuzzy making the detection of the iris challenging. We use RANSAC to first detect the upper and lower eyelids and then the iris. Then we align the images by finding differences in intensities at different scales and using a least squares optimization method (Levenberg-Marquardt), to overcome the movement of the iris and the camera. The method has been tested on videos taken from different patients. It is demonstrated to find the dry areas accurately and to provide a measure of the extent of the disease.