Abstract
Retinal layers can be identified by ophthalmologists using OCT images, which is useful for the diagnosis of different diseases. Recent EDI-OCT technique allows to explore the choroid layer, whose segmentation has become one of the hottest topics in the field of retinal imaging. In this sense, and taking into account that the choroid layer has different visual properties than the other retinal layers, a methodology based on textural information is presented in this paper to segment the choroid. From a retinal EDI-OCT image, a region of interest is detected and its low-level features are extracted, generating a feature vector that describes it, to finally segment the choroid. This paper includes several texture analysis methods to calculate the feature vectors. Results provided by the proposed methodology showed that the approach is adequate for the problem at hand, since it allows to segment the choroid layer with promising results.
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Acknowledgements
This research has been partially funded by the Secretaría de Estado de Investigación of the Spanish Government and FEDER funds of the European Union through the research project PI14/02161, and by the Consellería de Cultura, Educación e Ordenación Universitaria of the Xunta de Galicia through the research project GPC2013/065. A. González-López acknowledges the support of the Spanish Government under the FPI Grant Program.
We would like to thank the Hospital do Barbanza, Ribeira (Spain) for providing us with the image dataset.
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González-López, A., Remeseiro, B., Ortega, M., Penedo, M.G., Charlón, P. (2015). A Texture-Based Method for Choroid Segmentation in Retinal EDI-OCT Images. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_61
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