Abstract
Neovascularization is a serious sight-threatening complication of proliferative diabetic retinopathy (PDR) occurring in the diabetes mellitus persons, which causes progressive damage to the retina through the growth of new abnormal blood vessels. Preprocessing technique primarily extracts and normalizes the green plane of fundus image used to increase the level of contrast, the change in contrast level has been analyzed using Pair-wise Euclidean distance method. Normalized green plane image is subjected into the two-stage approach: detecting neovascularization region using compactness classifier and classifying neovascularization vessels using neural network. Compactness classifier with morphology-based operator and thresholding techniques are used to detect the neovascularization region. A function matrix box is added to categorize the neovascularization from normal blood vessels. Then, the feed-forward back-propagation neural network for the extracted features like number of segments, gray level, gradient, gradient variation, gray-level coefficient is attempted in Neovascularization region to get an indicative accuracy of classification. The proposed method is tested on images from online datasets and from two hospital eye clinic real-time images with varying quality and image resolution, achieves sensitivity and specificity of 80 and 100% respectively and with an accuracy of 90% gives encouraging abnormal blood vessels classification.
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References
Teena Thacker New Delhi (2009) India has largest number of Diabetes Patients: Report. The Indian Express, Wed Oct 21 2009, 03:34 hrs, Updated: Thu 20, Nov 2014, 11:15 Sun, 28 Apr 2013, 2:56 IST. Available online: http://archive.indianexpress.com/news/india-has-largest-number-of-diabetes-patients-report/531240/
Research letters (2012) A prescription survey in diabetes assessing metformin use in a tertiary care hospital in Eastern India. J Pharmacol Pharmacotherapeutics 3(3):273–275, July–Sept 2012. Available online: http://www.jpharmacol.com
Boyd K (2013) What is diabetic retinopathy. Eye Smart, Eye health information from the American Academy of Opthalmology, The Eye M.D Association, prohibited by US and international copyright law, 1 Sept 2013. Available online: http://www.geteyesmart.org/eyesmart/diseases/diabetic-retinopathy/
Cheriyan J, Menon HP, Dr. Narayanankutty KA (2012) 3D Reconstruction of human retina from fundus image—a survey. Int J Modern Eng Res (IJMER) 2(5):3089–3092. ISSN: 2249-6645, Sep–Oct 2012
Vislisel J, Oetting TA (2016) Diabetic retinopathy: from one medical student to another. EyeRounds.org, 1 Sept 2010. Available from: http://www.EyeRounds.org/tutorials/diabetic-retinopathy-med-students/
Goatman KA, Fleming AD, Philip S, Williams GJ, Olson JA, Sharp PF (2011) Detection of new vessels on the optic disc using retinal photographs. IEEE Trans Med Imaging 30(4):972–979
Hassan SSA, Bong DBL, Premsenthil M (2012) Detection of neovascularization in diabetic retinopathy. J Digit Imaging 25:436–444. Springer, Published online: 7 Sept 2011, Society for Imaging Informatics in Medicine 2011
DIARETDB0 database. Available online: http://www2.it.lut.fi/project/imageret/diaretdb0/
DIARETDB1 database. Available online: http://www2.it.lut.fi/project/imageret/diaretdb1/
MESSIDOR database. Available online: http://messidor.crihan.fr/
Acknowledgements
The authors would like to thank Dr. M. Pratap, Ophthalmologist of Vasan Eye Care, Nagercoil, India, and Dr. Bejan Singh, Ophthalmologist, Bejan Singh Eye Hospital, Nagercoil, India, for their help in collecting the images.
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Suma, K.G., Kumar, V.S. (2019). Classification of Abnormal Blood Vessels in Diabetic Retinopathy Using Neural Network. In: Soft Computing and Medical Bioinformatics. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-0059-2_4
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DOI: https://doi.org/10.1007/978-981-13-0059-2_4
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