Abstract
At the present, Optical Coherence Tomography (OCT) is a very promising imaging technique used by ophthalmologists for diagnosing because it provides more information than other classical modalities. Retinal structures can be studied on these images, so image processing-based methods are emerging to extract their information. Previously to any automatic feature extraction process, delimitation of retinal layers must be automated. With that purpose, this paper presents an active contour-based method to segment retinal layer boundaries. Regarding previous work, it is remarkable that this proposal includes processes of refinement for segmented layers. Thus, validation done by an opthalmologic expert shows that the method obtains accurate results even when some of these layers present alterations or low definition, making it robust, which is a very important feat.
This paper has been partly funded by the Secretaría de Estado de Investigación, Desarrollo e Innovación of the Spanish Government (A. González-López acknowledges its support under FPI Grant Program).
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González-López, A., Ortega, M., Penedo, M.G., Charlón, P. (2014). Automatic Robust Segmentation of Retinal Layers in OCT Images with Refinement Stages. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_38
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DOI: https://doi.org/10.1007/978-3-319-11755-3_38
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