Abstract
Retinal vessel segmentation plays a significant role for accurate diagnostics of ophthalmic diseases. In this paper, a novel preprocessing step for retinal vessel segmentation via optic nerve head exclusion is proposed. The idea relies in the fact that the exclusion of brighter optic nerve head prior to contrast enhancement process can better enhance the blood vessels for accurate segmentation. A histogram based intensity thresholding scheme is introduced in order to extract the optic nerve head which is then replaced by its surrounding background pixels. The efficacy of the proposed preprocessing step is established by segmenting the retinal vessels from the optic nerve head excluded image enhanced using CLAHE algorithm. Experimental works are carried out with fundus images from DRIVE database. It shows that 1%–3% of improvement in terms of TPR measure is achieved.
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The authors would like to acknowledge the University Grants Commission (UGC), New Delhi, India for the financial support extended under Maulana Azad National Fellowship (MANF) scheme.
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Wahid, F.F., Raju, G. (2019). An Efficient Preprocessing Step for Retinal Vessel Segmentation via Optic Nerve Head Exclusion. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1046. Springer, Singapore. https://doi.org/10.1007/978-981-13-9942-8_22
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DOI: https://doi.org/10.1007/978-981-13-9942-8_22
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