Abstract
This paper is based on a methodology for segmentation of the main retinal layers in Optical Coherence Tomography (OCT) images. The input image is transformed into a geometric graph and the layers to be detected will be given by its minimum-cost closed set. The main problem in this method is the selection of the appropriate cost functions associated to the graph, because of the variety of anomalies that images from patients might have.
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References
Sanchez-Tocino, H., Alvarez-Vidal, A., Maldonado, M.J., Moreno-Montaes, J., Garcia-Layana, A.: Retinal thickness study with optical coherence tomography in patients with diabetes. Investigative Ophthalmology & Visual Science 43(5), 1588–1594 (2002)
Albrecht, P., Ringelstein, M., Mueller, A., Keser, N., Dietlein, T., Lappas, A., Foerster, A., Hartung, H., Aktas, O., Methner, A.: Degeneration of retinal layers in multiple sclerosis subtypes quantified by optical coherence tomography. Multiple Sclerosis Journal (2012)
Puzyeyeva, O., Wai Ching Lam, J.G.F.E.A.: High-resolution optical coherence tomography retinal imaging: A case series illustrating potential and limitations. Journal of Ophthalmology (2011)
Haeker, M., Sonka, M., Kardonc, R., Shah, V.A., Wu, X., Abrámoff, M.: Automated segmentation of intraretinal layers from macular optical coherence tomography images. In: Proceedings of the SPIE: Medical Imaging, vol. 6512 (2007)
Li, K., Wu, X., Chen, D.Z., Sonka, M.: Optimal surface segmentation in volumetric images – a graph-theoretic approach. Proceedings of the IEEE Transactions on Pattern Analysis and Machine Intelligence 28(1), 119–134 (2006)
CSE-2320-Lab-4 (2002), http://ranger.uta.edu/~weems/notes5311/fflab.c
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González, A., Penedo, M.G., Vázquez, S.G., Novo, J., Charlón, P. (2013). Cost Function Selection for a Graph-Based Segmentation in OCT Retinal Images. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2013. EUROCAST 2013. Lecture Notes in Computer Science, vol 8112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53862-9_17
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DOI: https://doi.org/10.1007/978-3-642-53862-9_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53861-2
Online ISBN: 978-3-642-53862-9
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