Quantification of Global Tortuosity in Retinal Blood Vessels
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M. B. Sasongko, T.Y. Wong, T.T. Nguyen, C.Y. Cheung, J.E. Shaw, R. Kawasaki, E.L. Lamoureux, and J.J. Wang. “Retinal vessel tortuosity and its relation to traditional and novel vascular risk markers in persons with diabetesâ€. Curr Eye Res, vol.41(4), pp.551-557, 2016.
M. Cavallari, C. Stamile, R. Umeton, F. Calimeri, and F. Orzi. “Novel method for automated analysis of retinal images: results in subjects with hypertensive retinopathy and CADASILâ€. Biom Res Intl, 2015.
F. Oloumi, R. M. Rangayyan, and A. L. Ells. “Computer-aided diagnosis of retinopathy in retinal fundus images of preterm infants via quantification of vascular tortuosityâ€. J of Med Img, vol.3(4), pp. 044.505, 2016.
F. Oloumi, R. M. Rangayyan, P. Casti, and A. L. Ells. “Computer-aided diagnosis of plus disease via measurement of vessel thickness in retinal fundus images of preterm infantsâ€. Comp in Biol and Med, vol.66, pp.316-329, 2015.
J.C. Zenteno, J. CrespÃ, B. Buentello-Volante, J.A. Buil, F. Bassaganyas, J.L. Vela-Segarra, and M.T. Marieges. “Next generation sequencing uncovers a missense mutation in COL4A1 as the cause of familial retinal arteriolar tortuosityâ€. Graefe’s Arch. Clin. Exp. Ophthalmol, vol.252(11), pp. 1789-1794, 2015.
W. Lotmar, A. Freiburghaus, and D. Bracher, “Measurement of vessel tortuosity on fundus photographs,†Graefe’s Arch. Clin. Exp. Ophthalmol, vol. 211, pp. 49–57, 1979.
T. Mapayi, J. R. Tapamo, S. Viriri, and A. O. Adio, “Automatic retinal vessel detection and tortuosity measurement,†Image Anal Stereol, 35:117-135, 2016.
M. A. Sharbaf, H. R. Pourreza, T. Banaee. “A novel curvature based algorithm for automatic grading of retinal blood vessel tortuosity,†IEEE J of Biomed and Health Inform. 2015.
W. E. Hart, M. Goldbaum, P. Kube, and M.R. Nelson, “Automated measurement of retinal vascular tortuosity,†AMIA Annual Fall Symposium Proceedings, 1997.
W. E. Hart, M. Goldbaum, B. Cote, and P. Kube, “Measurement and classification of retinal vascular tortuosity,†Int. J. Med. Informatics, vol.53, no. 23, pp. 239-52, Feb. 1999.
E. Grisan, M. Foracchia, and A. Ruggeri, “A novel method for the automatic grading of retinal vessel tortuosity,†IEEE Trans. on Med Img, vol.27, no.3, pp.310-319, 2008.
M. Patasius, V. Marozas, D. Jegelevicius, and A. Lukosevicius, “Eval-uation of tortuosity of eye blood vessels using the integral of square of derivative of curvature,†IFMBE Proc. 3rd Eur. Med. Biol. Eng. Conf. (EMBEC05), vol. 11. 2005.
K. V. Chandrinos, M. Pilu, R. B. Fisher, and P. Trahanias, “Image processing techniques for the quantification of atherosclerotic changes,†DAI Research paper, 1998.
K. G. Goh, H. Wynne, M. L. Lee, and H. Wang, K. Cios, Ed., “Adris: an automatic diabetic retinal image screening system,†Med. Data Min. Knowledge Discovery, pp. 181-21, 2001.
E. Bullitt, G. Gerig, S. M. Pizer, W. Lin, and S.R. Aylward, â€Measuring tortuosity of the intracerebral vasculature from MRA image,†Med. Image Anal., vol. 9, pp. 1163-1171, Sep. 2003.
DOI: http://dx.doi.org/10.18517/ijaseit.8.4.6509
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