Novel interactive approach to intra-retinal layer segmentation from optical coherence tomography images

Retinal layer thickness, evaluated as a function of spatial position from optical coherence tomography (OCT) images is an important diagnostics marker for many retinal diseases. However, due to factors such as speckle noise, low image contrast, irregularly shaped morphological features such as retinal detachments, macular holes, and drusen, accurate segmentation of individual retinal layers is difficult. To address this issue, a novel interactive computer method for retinal layer segmentation from OCT images is presented. Based on rough initial points selected near the individual retinal layers by the operator, an efficient two-step kernel-based optimization scheme is employed to obtain accurate segmentation results for the individual layers. The performance of the novel algorithm was tested on a set of retinal images acquired in-vivo from healthy and diseased rodent models with a high speed, high resolution OCT system. Experimental results show that the proposed interactive approach provides accurate segmentation for OCT images affected by speckle noise, even in sub-optimal conditions of low image contrast and presence of irregularly shaped structural features in the OCT images. © 2009 Optical Society of America OCIS codes: (170.4500) Optical coherence tomography; (100.0100) Image processing; (100.3008) Image recognition, algorithms and filters. (170.4580) Optical diagnostics for medicine References and links 1. D. Huang, E. Swanson, C. Lin, J. Schuman, W. Stinson, W. Chang, M. Hee, T. Flotte, K. Gregory, C. Puliafito, and J. Fujimoto, “Optical coherence tomography,” Science, 254: 1178-1181 (1991). 2. A.F. Fercher, “Optical coherence tomography,” J. Biomed. Opt., 1: 157 (1996). 3. J. Fujimoto, W. Drexler, J. Schuman, and C. Hitzenberger, “Optical Coherence Tomography (OCT) in ophthalmology: introduction,” Opt Express. 2009 17: 5, 3978-3979 (2009). 4. C. Leung, C. Cheung, R. Weinreb, K. Qiu, S. 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