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Presenter: Alia Alabdulkarim, MSc | Lecturer, Information Technology Department, CCIS
Abstract: In this presentation, we present a tool developed for Classifying Strabismus Cases. Strabismus is an eye condition in which both eyes do not point in the same direction. When detected at an early age, the chances for curing it becomes higher. Moreover, the methods used to detect strabismus and measure its degree of deviation are complex and time consuming, and they always require the presence of a physician, in addition to the fact that children are not easy to work with. In this work, we are presenting a method for detecting strabismus and measuring its degree of deviation with using only an image of the patient‘s eye region. Our method is based on extracting features from a set of training images (training corpora) and using them to build our classifier. The classifier is built using data mining approaches, decision tree (ID3) and probabilistic neural network (PNN). Finally, the built classifier was tested using a set of testing images (testing corpora).
Date: May 6, 2013
Time: 12:00 - 1:00 pm
Location: Research Center Auditorium in Building #2