A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images.
The detection of exudates is a prerequisite for detecting and grading severe retinal lesions, like the diabetic macular edema. In this work, we present a new method based on mathematical morphology for detecting exudates in color eye fundus images. A preliminary evaluation of the proposed method performance on a known public database, namely DIARETDB1, indicates that it can achieve an average sensitivity of 70.48%, and an average specificity of 98.84%. Comparing to other recent automatic methods available in the literature, our proposed approach potentially can obtain better exudate detection results in terms of sensitivity and specificity.
Welfer
Daniel
D
Instituto de Informática, Universidade Federal do Rio Grande do Sul, Av. Bento Gonalves 9500, Porto Alegre, RS, Brazil. daniel.welfer@inf.ufrgs.br
Scharcanski
Jacob
J
Marinho
Diane Ruschel
DR
D000465:Algorithms; D003116:Color; D048909:Diabetes Complications; D003952:Diagnostic Imaging / Q000379:methods*; D005122:Exudates and Transudates / Q000000981:diagnostic imaging*; D005654:Fundus Oculi; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008269:Macular Edema / Q000175:diagnosis; D011859:Radiography