01870nas a2200229   4500008004100000020002200041022001400063245009100077210006900168260005000237300001400287520104100301100001701342700001901359700002101378700002801399700002301427700002501450700001901475700001901494856012701513       2007                        eng d  a978-3-540-74271-5  a0302-974300aEffects of Preprocessing Eye Fundus Images on Appearance Based Glaucoma Classification0 aEffects of Preprocessing Eye Fundus Images on Appearance Based G  aBerlin; HeidelbergbSpringer VerlagcAug 2007  a165 - 1723 a<p>Early detection of glaucoma is essential for preventing one ofthe most common causes of blindness. Our research is focused on a novel automated classification system based on image features from fundus photographs which does not depend on structure segmentation or prior expert knowledge. Our new data driven approach that needs no manual assistance achieves an accuracy of detecting glaucomatous retina fundus images compareable to human experts. In this paper, we study image preprocessing methods to provide better input for more reliable automated glaucoma detection. We reduce disease independent variations without removing information that discriminates between images of healthy and glaucomatous eyes. In particular, nonuniform illumination is corrected, blood vessels are inpainted and the region of interest is normalized before feature extraction and subsequent classification. The effect of these steps was evaluated using principal component analysis for dimension reduction and support vector machine as classifier.</p>1 aMeier, Jörg1 aBock, Rudriger1 aMichelson, Georg1 aNyúl, László, Gábor1 aHornegger, Joachim1 aKropatsch, Walter, G1 aKampel, Martin1 aHanbury, Allan  uhttps://inf.u-szeged.hu/publication/effects-of-preprocessing-eye-fundus-images-on-appearance-based-glaucoma-classification