Retinal Layer Segmentation in Pathological SD-OCT Images Using Boisterous Obscure Ratio Approach and its Limitation
G. Mohandass1, R. Ananda Natarajan2 and S. Sendilvelan31Biomedical Department, Sathyabama University, Chennai- 600119.
2Department of Electronic and Instrumentation Engineering, Pondicherry Engineering College, Puducherry.
3Department of Mechanical Engineering, Dr.M.G.R. Educational and Research Institute, University, Chennai-600095.
Corresponding Author E-mail: sendilvelan.mech@drmgrdu.ac.in
Abstract: Optical Coherence Tomography (OCT) imaging technique is a precise and prominent approach in retinal diagnosis on layers level. The pathological effect in retina, challenges a computational segmented approach in the boundary layer level for evaluating and identification of defect. The segmentation of layers and boundary edging process is misguided by the noise in the computation method. In these criteria, a novel algorithm of segmentation with the base of denoising techniques is required. In this work, Robust Outlyingness Ratio (ROR) algorithm is a noise detective operation which is applied in edge direction with gradient deformable contour model for layers detection. This Boisterous Obscure Ratio (BOR) computation procedure is derived. BOR is an image segmentation process with connectivity of eight formed layers in retinal SD-OCT images. The validation is done by comparing with the prior demonstration method. The highlighting feature of the BOR method is that it is time consuming and the results produced are highly substantial and effective.
Keywords: Image Analysis; Image Detection Systems; Noise in Imaging Systems; Optical Coherence Tomography; Ophthalmology Transforms; Back to TOC