Computer-Aided Diagnostics and Pattern Recognition: Automated Glaucoma Detection [chapter]

Thomas Köhler, Rüdiger Bock, Joachim Hornegger, Georg Michelson
2014 Teleophthalmology in Preventive Medicine  
Glaucoma is one of the major causes for blindness with a high rate of unreported cases. To reduce this number, screening programs are performed. However, these are characterized by a high workload for manual and cost-intensive assessment. Computer-aided diagnostics (CAD) to perform an automated pre-exclusion of normals might help to improve program's efficiency. This chapter reviews and discusses recent advances in the development of pattern recognition algorithms for automated glaucoma
more » ... n based on structural retinal image data. Two main methodologies for glaucoma detection are introduced: (i) structuredriven approaches that mainly rely on the automated extraction of specific medically relevant indicators, while (ii) data-driven techniques perform a generic machine-learning approach on entire image data blobs. Both approaches show a reasonable and comparable performance although they rely on different basic assumptions. A combination of these might further improve CAD for a more efficient and cost-sensitive workflow as a major proportion of normals will be excluded from unnecessary detailed investigations.
doi:10.1007/978-3-662-44975-2_9 fatcat:dawhtu7gsvasrmyeg4j3h3crna