A Framework for Extraction of Inner Limiting Membrane in High Speckle Noisy Images

Optical coherence tomography imaging modality mostly used in biomedical imaging, technique for the examination of retina, and becoming an essential tool for having a 3-D image of retina. Retinal layers analysis of an SD-OCT image facilities the diagnosis and monitoring of various ocular diseases such as Age related Degeneration, Macular Edema, Diabetic Retinopathy and glaucoma. Segmentation of retinal layers in an OCT Images has been a rigorous task due to speckle noise in an image. This paper presents a methods for the extraction of Inner Limiting Membrane (ILM) layer in extremely noisy OCT images. Compared with existing algorithms for the extraction of Inner Limiting Membrane layer (ILM). We also compared diagnostic accuracy of interpolating algorithms and aimed to suggest best interpolating algorithm for delineation of retinal layers focusing glaucoma detection for extremely noisy images. The ILM Layer and Retinal Epithelium Layer will determine the Cup to disc ratio (CDR) that is significant investigating factor for glaucoma diagnosis. The data set having 79 images, including normal, suspect and glaucoma subjects.