  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.
