Abstract
Cup-to-disc ratio is an important measure to diagnose glaucoma. This measure can be automatically computed from the segmentation of the optic disc and cup in eye-fundus image. In this paper, a novel segmentation algorithm based on Soft Computing techniques is presented. This theory is able to handle the imprecision and uncertainty present in the determination of the boundaries of these structures. The algorithm is composed of three main steps: vessel segmentation and removal, inpainting and optic disc and cup boundaries localisation. The preliminary results show the potential of this approach which obtains a visual accurate segmentation of both structures in the images of the DRIVE database.
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Acknowledgments
The Spanish grant TIN 2016-75404-P AEI/FEDER, UE supported this work. P. Bibiloni also benefited from the fellowship FPI/1645/2014 of the Conselleria d’Educació, Cultura i Universitats of Govern de les Illes Balears under an operational program co-financed by the European Social Fund.
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Bibiloni, P., González-Hidalgo, M., Massanet, S., Mir, A., Ruiz-Aguilera, D. (2018). Soft Computing Based Technique for Optic Disc and Cup Detection in Digital Fundus Images. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_9
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