Automatic tear film segmentation based on texture analysis and region growing

Abstract

Dry eye syndrome is a prevalent disease characterized by symptoms of discomfort and ocular surface damage. It can be identified by several types of diagnostic tests, one of which consists in capturing the appearance of the tear film by means of the Doane interferometer. Previous research has demonstrated that this manual test can be automated, with the benefits of saving time for experts and providing unbiased results. However, most images are made up of a combination of different patterns which makes their classification into one single category per eye not always possible. In this sense, this paper presents a first attempt to segment tear film images based on the interference patterns, and so to detect multiple categories in each individual subject. The adequacy of the proposed methodology was demonstrated since it provides reliable results in comparison with the practitioners’ annotations.