Abstract
This paper presents optical coherence tomography (OCT) signal intensity variation based segmentation algorithms for retinal layer identification. Its main ambition is to reduce the calculation time required by layer identification algorithms. Two algorithms, one for the identification of the internal limiting membrane (ILM) and the other for retinal pigment epithelium (RPE) identification are implemented to evaluate structural features of the retina. Using a 830 nm spectral domain OCT device, this paper demonstrates a segmentation method for the study of healthy and diseased eyes.
Highlights
An established method in ophthalmic imaging, optical coherence tomography (OCT) has the great advantage that it provides high-resolution three dimensional (3D) images of the human eye noninvasively
This paper presents optical coherence tomography (OCT)
Signal intensity variation based segmentation algorithms for retinal layer identification
Summary
An established method in ophthalmic imaging, optical coherence tomography (OCT) has the great advantage that it provides high-resolution three dimensional (3D) images of the human eye noninvasively. A number of severe eye diseases (age-related macular degeneration (ARMD), choroidal neovascularisation (CNV), glaucoma, etc.) cause structural changes in the retina and the choroid To evaluate these changes quantitatively requires a segmentation-based determination of the thicknesses of the different tissue layers. Several different methods are available for identifying the internal layers of posterior human eye [1, 2, 3, 4, 5, 6, 7] Most of these are based on intensity variations in backscattered signal [1, 2, 3, 4, 5, 6]. The main ambition is to decrease the necessary calculation time, while still obtaining reliable segmentation results
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