01933nas a2200193   4500008004100000020001400041245007900055210006900134260000900203300001400212490000700226520127600233100001901509700001701528700002801545700002301573700002101596856012201617       2010                        eng d  a1361-841500aGlaucoma Risk Index: Automated glaucoma detection from color fundus images0 aGlaucoma Risk Index Automated glaucoma detection from color fund  c2010  a471 - 4810 v143 a<p>Glaucoma as a neurodegeneration of the optic nerve is one of themost common causes of blindness. Because revitalization of the degenerated nerve fibers of the optic nerve is impossible early detection of the disease is essential. This can be supported by a robust and automated mass-screening. We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. After a glaucoma specific preprocessing, different generic feature types are compressed by an appearance-based dimension reduction technique. Subsequently, a probabilistic two-stage classification scheme combines these features types to extract the novel Glaucoma Risk Index (GRI) that shows a reasonable glaucoma detection performance. On a sample set of 575 fundus images a classification accuracy of 80% has been achieved in a 5-fold cross-validation setup. The GRI gains a competitive area under ROC (AUC) of 88% compared to the established topography- based glaucoma probability score of scanning laser tomography with AUC of 87%. The proposed color fundus image-based GRI achieves a competitive and reliable detection performance on a low-priced modality by the statistical analysis of entire images of the optic nerve head.</p>1 aBock, Rudriger1 aMeier, Jörg1 aNyúl, László, Gábor1 aHornegger, Joachim1 aMichelson, Georg  uhttps://home.inf.u-szeged.hu/en/publication/glaucoma-risk-index-automated-glaucoma-detection-from-color-fundus-images