{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:25:50Z","timestamp":1781105150366,"version":"3.54.1"},"reference-count":15,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p>Retinal image analysis plays an important part in identifying various eye related diseases such as diabetic retinopathy (DR), glaucoma and many others. Accurate segmentation of blood vessels plays an important part in identifying the retinal diseases at an early stage. In this article, an unsupervised approach based on contour detection has been proposed for effective segmentation of retinal blood vessels. The proposed morphological contour-based blood vessel segmentation (MCBVS) method performs preprocessing using contrast limited adaptive histogram equalization followed by alternate sequential filtering to generate a noise-free image. The resultant image undergoes Otsu thresholding for candidate extraction followed by contour detection to properly segment the blood vessels. The MCBVS method has been tested on the DRIVE dataset and the experimental result shows that the proposed method achieved a sensitivity, specificity and accuracy of 58.79%, 90.77% and 86.7%, respectively. The MCBVS method performs better than the existing methods Sobel, Prewitt and Modified U-Net in terms of accuracy.<\/jats:p>","DOI":"10.4018\/ijaec.2018100104","type":"journal-article","created":{"date-parts":[[2018,9,20]],"date-time":"2018-09-20T09:38:25Z","timestamp":1537436305000},"page":"48-63","source":"Crossref","is-referenced-by-count":6,"title":["Morphological Contour Based Blood Vessel Segmentation in Retinal Images Using Otsu Thresholding"],"prefix":"10.4018","volume":"9","author":[{"given":"S. Saranya","family":"Rubini","sequence":"first","affiliation":[{"name":"Coimbatore institute of technology, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Kunthavai","sequence":"additional","affiliation":[{"name":"Coimbatore Institute of Technology, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.B.","family":"Sachin","sequence":"additional","affiliation":[{"name":"Coimbatore Institute of Technology, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. Deepak","family":"Venkatesh","sequence":"additional","affiliation":[{"name":"Coimbatore Institute of Technology, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"issue":"7","key":"IJAEC.2018100104-0","article-title":"A morphological hessian based approach for retinal blood vessels segmentation and denoising using region based otsu thresholding.","volume":"11","year":"2016","journal-title":"PLoS One"},{"key":"IJAEC.2018100104-1","doi-asserted-by":"publisher","DOI":"10.1109\/UPCON.2017.8251120"},{"key":"IJAEC.2018100104-2","doi-asserted-by":"crossref","unstructured":"Chauhan, R., Uniyal, A., & Dubey, V. P. (2016, November). Detection of retinal blood vessels and reduction of false microaneurysms for diagnosis of diabetic retinopathy. In International Conference on Emerging Trends in Communication Technologies (ETCT) (pp. 1-6). IEEE.","DOI":"10.1109\/ETCT.2016.7882953"},{"key":"IJAEC.2018100104-3","doi-asserted-by":"publisher","DOI":"10.1109\/CGiV.2016.69"},{"key":"IJAEC.2018100104-4","unstructured":"Glycosmedia. (n.d.). Features of Diabetic Retinopathy. Retrieved from http:\/\/www.glycosmedia.com\/education\/diabetic-retinopathy\/diabetic-retinopathy-features-of-diabetes-microaneurysms\/"},{"key":"IJAEC.2018100104-5","doi-asserted-by":"crossref","DOI":"10.1109\/CCDC.2018.8407435","article-title":"Retinal blood vessels semantic segmentation method based on modified U-Net.","author":"L.Luo","year":"2018","journal-title":"2018 Chinese Control And Decision Conference (CCDC)"},{"key":"IJAEC.2018100104-6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2006.879955"},{"key":"IJAEC.2018100104-7","unstructured":"OpenCV. (n.d.). Structural Analysis and Shape Descriptors. Retrieved from https:\/\/docs.opencv.org\/2.4\/modules\/imgproc\/doc\/structural_analysis_and_shape_descriptors.html"},{"issue":"1","key":"IJAEC.2018100104-8","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms.","volume":"9","author":"N.Otsu","year":"1979","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics"},{"key":"IJAEC.2018100104-9","doi-asserted-by":"publisher","DOI":"10.1016\/S0734-189X(87)80186-X"},{"key":"IJAEC.2018100104-10","unstructured":"Diabeticretinopathy.org. (n.d.). Mechanism of diabetic retinopathy. Retrieved from www.diabeticretinopathy.org.uk\/diabetic_retinopathy_mech.html"},{"key":"IJAEC.2018100104-11","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2015.04.001"},{"key":"IJAEC.2018100104-12","first-page":"1","article-title":"Automatic retinal vessel extraction algorithm.","author":"T. A.Soomro","year":"2016","journal-title":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)"},{"key":"IJAEC.2018100104-13","unstructured":"Wikipedia. (n.d.). Ramer\u2013Douglas\u2013Peucker algorithm. Retrieved October 13, 2016 from https:\/\/ipfs.io\/ipfs\/QmXoypizjW3WknFiJnKLwHCnL72vedxjQkDDP1mXWo6uco\/wiki\/Ramer%E2%80%93Douglas%E2%80%93Peucker_algorithm.html"},{"issue":"7","key":"IJAEC.2018100104-14","first-page":"1010","article-title":"Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation.","volume":"10","author":"F.Zana","year":"2001","journal-title":"IEEE Transactions on"}],"container-title":["International Journal of Applied Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=214896","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T10:04:49Z","timestamp":1651831489000},"score":1,"resource":{"primary":{"URL":"http:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJAEC.2018100104"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2018,10]]},"references-count":15,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.4018\/ijaec.2018100104","relation":{},"ISSN":["1942-3594","1942-3608"],"issn-type":[{"value":"1942-3594","type":"print"},{"value":"1942-3608","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10]]}}}