A new combined method based on curvelet transform and morphological operators for automatic detection of foveal avascular zone

In order to achieve early detection of diabetic retinopathy (DR) for the sake of preventing from blindness, regular screening using retinal photography is necessary. Abnormalities of DR do not have uniform distribution over the retina. Certain types of abnormalities usually occur in specific areas on the retina. The distance between lesions, such as micro-aneurysms, and the foveal avascular zone (FAZ) is a useful feature for later analysis and grading of DR. In this paper, a new fully automatic system is presented to find the location of FAZ in fundus fluorescein angiogram photographs. The method is based on two procedures: digital curvelet transform (DCUT) and morphological operations. Firstly, end points of vessels are detected based on vessel segmentation using DCUT. By connecting these points in the selected region of interest, FAZ region is extracted. Secondly, vessels are subtracted from the retinal image, and morphological dilatation and erosion are applied on the resulted image. By choosing an appropriate threshold, FAZ region is detected. The final FAZ region is extracted by performing logical AND between two segmented FAZ. Our experiments show that the system achieves, respectively, the specificity and sensitivity of (> 98 and > 96 %) for normal stage, for mild/moderate non-proliferative DR (NPDR) (> 98, and > 95 %) and for Sever NPDR + PDR (> 97 and > 93 %).