Neovascularization Detection on Retinal Images
Proliferative Diabetic Retinopathy (PDR) is characterized by the growth of new abnormal, thin blood vessels called neovascularzation that spread along the retinal surface. An automated computer aided diagnosis system needs to identify neovasculars for PDR screening. Retinal images are often noisy and poorly illuminated. The thin vessels mostly appear to be disconnected and are inseparable from the background. This paper proposes a new method for neovascularization detection on retinal images. Blood vessels are extracted as thick, medium and thin types using multilevel thresholding on matched filter response. The total mutual information between the vessel density and the tortuosity of the thin vessel class is maximized to obtain the optimal thresholds to classify the normal and the abnormal vessels. Simulation results demonstrate that the proposed method outperforms the existing ones for neovascularization detection with an average accuracy of \(97.54\%\).
KeywordsNeovascularization Proliferative diabetic retinopathy Mutual information Compactness Tortuosity
- 1.Messidor. http://messidor.crihan.fr/index-en.php
- 2.Agurto, C., Yu, H., Murray, V., Pattichis, M.S., Barriga, S., Bauman, W., Soliz, P.: Detection of neovascularization in the optic disc using an AM-FM representation, granulometry, and vessel segmentation. In: 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4946–4949, August 2012Google Scholar
- 4.Ding, S., Shi, Z., Jin, F.: Studies on fuzzy information measures. In: 5th IEEE International Conference on Cognitive Informatics, vol. 1, pp. 292–296, July 2006Google Scholar
- 8.Kalesnykiene, V., Kamarainen, J.K., Voutilainen, R., Pietilä, J., Kälviäinen, H., Uusitalo, H.: DiaRetDB1 diabetic retinopathy database and evaluation protocol. http://www.it.lut.fi/project/imageret/diaretdb1