Automatic Detection and Segmentation of Optic Disc (ADSO) of Retinal Fundus Images Based on Mathematical Morphology

The main objective of medical image processing field is to design computational tools which will assist quantification and visualization of remarkable pathology and anatomical structure. Diabetic retinopathy is a medical disorder where the retina is damaged due to fluids leak from the blood vessels into the retina of human eye. The identification of optic disk in retinal fundus images and quantitative study of the evolution of its shape and size plays an important role in diagnosing different pathologies, and the abnormalities related to the retina of human eye. Most of the abnormalities which are related to optic disc may leads to a structural changes in the inner and the outer area of the optic disc. Optic disc identification and segmentation on the level of the whole retinal image reduces the detection sensitivity for those parts. In this research, an advanced classification based on hierarchical process for the detection and segmentation of optic disc has been proposed. The exact boundary of optic disc is obtained by calculating the region of interest and applying an innovative morphological transformation based adaptive thresholding. The presented technique helps to reduce the process area needed for segmentation techniques leading to a distinguished performance enhancement and reducing the amount of the needed computational cost for each retinal fundus image. The proposed technique has been evaluated on publicly available data sets of retinal images which are DIARETDB1, DRIVE, HRF, DRIONS-DB, IDRiD and STARE, and a remarkable improvement has been found over the existing techniques in terms of accuracy and processing time.