Diabetic Maculopathy Detection Using Fundus Fluorescein Angiogram Images - A Review

Abstract

Computational retinal imaging and vision based techniques have been assisting ophthalmologists for efficient and rapid screening and diagnostics, like other healthcare areas. Human retina is the only place in the human circulatory systems that can be seen using non-invasive techniques like fundus imaging, Optical Coherence Tomography (OCT) and invasive technique like Fluorescein angiograms. Attempts have been progressing towards developing an automatic detection and analysis of many eye related complications like diabetic retinopathy; age-related macular degeneration and glaucoma. There have been many survey papers of algorithms for pre-processing, segmentation and classification involving Fundus and OCT images. It has been observed that fundus fluorescein angiograms (FFA) play an important role in the detection and analysis of diabetic maculopathy which has become one of the major complications arising due to prolonged diabetes. It is also considered as severe as it affects the central vision of the human eye. Here we propose to perform a systematic review of the developed algorithms for processing FFA images of patients suffering from diabetic maculopathy.