Abstract
This paper describes a fast and efficient method to automatically measure the ISNT and CDR in retinal images. The method is based on a robust detection of the optic disk and excavation in a enhanced retinal image by means of morphological operators. Using this coarse segmentation as initialization, two parametric active contours implemented in the frequency domain perform a fine segmentation of the optic disk and excavation. The resulting curves allow the automatic calculation of the ISNT and CDR values, which are important features to consider in the early detection of glaucoma. The accuracy and precision of the method has been tested and compared with the evaluation of two ophthalmologists in a preliminary set of images.
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Acknowledgments
This work has been partially supported by Spanish National projects AES2017-PI17/00771 and AES2017-PI17-00821 (Instituto de Salud Carlos III).
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Verdú-Monedero, R., Morales-Sánchez, J., Berenguer-Vidal, R., Sellés-Navarro, I., Palazón-Cabanes, A. (2019). Automatic Measurement of ISNT and CDR on Retinal Images by Means of a Fast and Efficient Method Based on Mathematical Morphology and Active Contours. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science(), vol 11487. Springer, Cham. https://doi.org/10.1007/978-3-030-19651-6_35
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