A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screening
This is an incremental survey aimed at students and researchers in ophthalmology and computer vision to understand current capabilities and future directions in CAD systems.
The paper surveys computer-aided diagnostic systems for diabetic retinopathy screening, addressing the shortage of ophthalmologists and the need for early detection to prevent vision loss, by reviewing recent algorithms and databases in retinal image processing.
Diabetes Mellitus (DM) can lead to significant microvasculature disruptions that eventually causes diabetic retinopathy (DR), or complications in the eye due to diabetes. If left unchecked, this disease can increase over time and eventually cause complete vision loss. The general method to detect such optical developments is through examining the vessels, optic nerve head, microaneurysms, haemorrhage, exudates, etc. from retinal images. Ultimately this is limited by the number of experienced ophthalmologists and the vastly growing number of DM cases. To enable earlier and efficient DR diagnosis, the field of ophthalmology requires robust computer aided diagnosis (CAD) systems. Our review is intended for anyone, from student to established researcher, who wants to understand what can be accomplished with CAD systems and their algorithms to modeling and where the field of retinal image processing in computer vision and pattern recognition is headed. For someone just getting started, we place a special emphasis on the logic, strengths and shortcomings of different databases and algorithms frameworks with a focus on very recent approaches.