Localisation and segmentation of optic disc with the fractional‐order Darwinian particle swarm optimisation algorithm

Abstract

Automatic optic disc (OD) localisation and segmentation is still a great challenge in computer-aided diagnosis and screening system. Here, a new OD segmentation algorithm is proposed based on the distinct features of OD in terms of its intensity and shape. The algorithm includes four stages: image preprocessing, image segmentation, ellipse fitting, and OD localisation and segmentation. In the preprocessing stage, the blood vessel in the input retinal image is removed by using the morphological operation and median filtering in HSL (hue–saturation–lightness) colour space. In the image segmentation and ellipse fitting stages, the fractional-order Darwinian particle swarm optimisation algorithm is used to extract the brightest region, and the least-squares optimisation is adopted to detect elliptical OD shape. Finally, the smooth OD borders are generated in the last stage. The proposed method is evaluated by the centroid difference, overlapping ratio, overlap score, and success indexes. Experimental results on the retinal images from DRION, MESSIDOR, ORIGA, and many other public databases demonstrate that the proposed method has superior performance, and may be a suitable tool for automated retinal image analysis.