Automated analysis of retinal images for detection of age-related macular degeneration and diabetic retinopathy

M. van Grinsven

Promotor: B. van Ginneken and C. Hoyng
Copromotor: C.I. Sánchez-Gutiérrez and T. Theelen
Radboud University, Nijmegen


In this thesis, an effort is made to pursue the VISION 2020 goals of eliminating avoidable blindness and visual impairment worldwide. It describes and validates new automatic methods to detect Diabetic Retinopathy (DR) and Age-related Macular Degeneration (AMD), two of the most common retinal diseases worldwide. Achieving automatic detection of these diseases will facilitate and accelerate implementation of screening programs for retinal diseases worldwide. It is estimated that 80% of blindness is preventable if timely awareness of presence of these diseases is achieved.

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