Classifying Glaucoma with Image-Based Features from Fundus Photographs

Glaucoma is one of the most common causes of blindness and it is becoming even more important considering the ageing society. Because healing of died retinal nerve fibers is not possible early detection and prevention is essential. Robust, automated mass-screening will help to extend the symptom-free life of affected patients. We devised a novel, automated, appearance based glaucoma classification system that does not depend on segmentation based measurements. Our purely data-driven approach is applicable in large-scale screening examinations. It applies a standard pattern recognition pipeline with a 2-stage classification step. Several types of image-based features were analyzed and are combined to capture glaucomatous structures. Certain disease independent variations such as illumination inhomogeneities, size differences, and vessel structures are eliminated in the preprocessing phase. The “vesselfree” images and intermediate results of the methods are novel representations...

• Type: Conference
• Year: 2007
• Where: DAGM
• Authors: Rüdiger Bock, Jörg Meier, Georg Michelson, László G. Nyúl, Joachim Hornegger
• Keywords: Appearance Based Glaucoma, DAGM 2007, Possible Early Detection, Retinal Nerve fibers