Interferential Tear Film Lipid Layer Classification: An Automatic Dry Eye Test

Dry eye is a symptomatic disease which affects a wide range of population and has a negative impact on their daily activities, such as driving or working with computers. Its diagnosis can be achieved by several clinical tests, one of which is the analysis of the interference pattern and its classification into one of the Guillon's categories. The methodologies for automatic classification obtain promising results but at the expense of requiring a long processing time. In this research, feature selection techniques are used to reduce time whilst maintaining performance, paving the way for the development of a novel tool for automatic classification of tear film lipid layer. This tool produces significant classification rates over 96% compared with the annotations of the optometrists and provides unbiased results. Also, it works in real-time and so allows important time savings for the experts.

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