
Asian Journal of Engineering and Applied Technology (AJEAT)
Boundary Extraction and Vessel Width Calculation in Retinal Fundus Images
Author : R. Manjunatha and H. S. SheshadriVolume 8 No.2 April-June 2019 pp 63-70
Abstract
A retinal vessel width measurement algorithm is presented towards ROP (Retinopathy of Prematurity) plus diagnostic automation. The algorithm involving geometrical feature extraction with the image processing is used to compute the effective width of the major vessels in a retinal image. Width measurement is shown to be a statistical parameter estimation related to the statistics of the retinal information. The algorithm is applied to the generic data bases available and the results are found to be satisfactory with ophthalmologist opinion. The effectiveness of the algorithm depends on the fundus image capturing settings.
Keywords
OD, OPBA, RI, ROP, Tortuosity, Vascular Network
References
[1] Giedrius Stabingis, Jolita Bernataviciene, Gintautas Dzemyda, Alvydas Paunksnis, Povilas Treigys, Ramute Vaicaitiene, and Lijana Stabingien “Automatization of Eye Fundus Vessel Width Measurements”, vipimage-2017, Springer International Publishing, published in 2018, DOI: 10.1007/978-3-319-68195-5_85.
[2] Meindert Niemeijer, Xiayu Xu, Alina V. Dumitrescu, Priya Gupta, Bram van Ginneken, James C. Folk, and Michael D. Abrámoff, “Automated Measurement of the Arteriolar-to- Venular Width Ratio in Digital Color Fundus Photographs”, IEEE Transactions on Medical Imaging, Vol. 30, No. 11, Nov. 2011.
[3] G D. arway-Heath, A. Rudnicka, T. Lowe, P. Foster, F. Fitzke and R. Hitchings, “Measurement of optic disc size: equivalence of methods to correct for ocular magnification”, Br. J. Ophthalmol, Vol. 82, 643–649, 1998.
[4] Faraz Oloumi, Rangaraj M. Rangayyan, Anna L. Ells “Measurement of Vessel Width in Retinal Fundus Images of Preterm Infants with Plus Disease”, IEEE International Symposium on Medical Measurements and Applications, MeMeA, 2014.
[5] Chisako Muramatsu, Yuji Hatanaka, Tatsuhiko Iwase, Takeshi Hara and Hiroshi Fujita “Automated detection and classification of major retinal vessels for determination of diameter ratio of arteries and veins”, Medical Imaging 2010: Computer-Aided Diagnosis, edited by Nico Karssemeijer, Ronald M. Summers, Proc. of SPIE, Vol. 7624,76240J.
[6] J. Lowell, A. Hunter, D. Steel, A. Basu, R. Ryder and R. L. Kennedy, “Measurement of retinal vessel widths from fundus images based on 2-D modeling”, IEEE Transactions on Medical Imaging, Vol. 23, No. 10, pp. 1196–1204, 2004.
[7] C. Heneghan, J. Flynn, M. O’Keefe and M. Cahill, “Characterization of changes in blood vessels width and tortuosity in retinopathy of prematurity using image analysis”, Medical Image Analysis, Vol. 6, No. 1, pp. 407–429, 2002.
[8] Liang Zhou, Mark S. Rzeszotarski, Lawrence J. Singerman and Jeanne M. Chokreff “The Detection and Quantification of Retinopathy Using Digital Angiograms”, IEEE Transactions on Medical Imaging, Vol. 13, No. 4, Dec. 1994.
[9] Ana Maria Mendonça and Aurélio Campilho, “Segmentation of Retinal Blood Vessels by Combining the Detection of Centerlines and Morphological Reconstruction”, IEEE Transactions on Medical Imaging, Vol. 25, No. 9, Sept. 2006.
[10] Reza Pourreza, Touka Banaee et al., “A Radon Transform Based Approach for Extraction of Blood Vessels in Conjunctival Images”, © Springer-Verlag Berlin Heidelberg, pp. 948 – 956, 2008.
[11] R Manjunatha, Mahesh Koti and Dr. H.S. Sheshadri “Boundary Extraction and Tortuosity Calculation in Retinal Fundus Images”, Springer, pp. 1119-1130, PESCE, Mandya, published in April-2019.Doi: https://doi.org/10.1007/978-981-13-5802-9_96.ICERECT-2018,