Automated detection of kinks from blood vessels for optic cup segmentation in retinal images

The accurate localization of the optic cup in retinal images is important to assess the cup to disc ratio (CDR) for glaucoma screening and management. Glaucoma is physiologically assessed by the increased excavation of the optic cup within the optic nerve head, also known as the optic disc. The CDR is thus an important indicator of risk and severity of glaucoma. In this paper, we propose a method of determining the cup boundary using non-stereographic retinal images by the automatic detection of a morphological feature within the optic disc known as kinks. Kinks are defined as the bendings of small vessels as they traverse from the disc to the cup, providing physiological validation for the cup boundary. To detect kinks, localized patches are first generated from a preliminary cup boundary obtained via level set. Features obtained using edge detection and wavelet transform are combined using a statistical approach rule to identify likely vessel edges. The kinks are then obtained automatically by analyzing the detected vessel edges for angular changes, and these kinks are subsequently used to obtain the cup boundary. A set of retinal images from the Singapore Eye Research Institute was obtained to assess the performance of the method, with each image being clinically graded for the CDR. From experiments, when kinks were used, the error on the CDR was reduced to less than 0.1 CDR units relative to the clinical CDR, which is within the intra-observer variability of 0.2 CDR units.