A fast approach to human retina optic disc segmentation using fuzzy c-means level set evolution

Abstract

The process of localization and segmentation of the optic disc (OD) plays a crucial role in automatic screening for eye disease. This paper presents a novel and simple iterative method for rapid, fully automatic localization and segmentation of the OD in retinal fundus images. Furthermore, this new method can find the boundary of the OD using the initial fuzzy clustering means algorithm. The proposed method employs a new level set evolution based on the fuzzy clustering algorithm. The proposed technique was compared, in terms of performance, with various methods in the literature, and the results were found to be conclusive and effective. The obtained results suggest that this OD segmentation technique is accurate in addition to being computationally inexpensive.