Published on April 2019 | Image processing, Soft computing

A Bayesian Set Approach (BSM) for Segmentation of Retinal Fundus Images for Retinal Disorder Detection

Research in medical image processing has been aggregating significant contributions and findings aided by the advent of state of the art image acquisition systems and processing algorithms. One such field of interest is the processing of retinal fundus image for detection of a series of disorders related to eye as well as diabetes prone patients. Segmentation forms the backbone behind retinal image processing as the segmentation of blood vessels in the retinal image brings out key findings about the condition of the eye. A novel Bayesian set approach/model is proposed in this research article for segmentation of blood vessels and compared with learning based model for the accuracy as well as computation time. Experimental results justify the simplicity of the proposed model with a high degree of observed precision