{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T09:49:44Z","timestamp":1778320184889,"version":"3.51.4"},"reference-count":24,"publisher":"University of Zielona G\u00f3ra, Poland","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,9,1]]},"abstract":"<jats:title>An Automatic Hybrid Method for Retinal Blood Vessel Extraction<\/jats:title><jats:p>The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper presents a novel hybrid automatic approach for the extraction of retinal image vessels. The method consists in the application of mathematical morphology and a fuzzy clustering algorithm followed by a purification procedure. In mathematical morphology, the retinal image is smoothed and strengthened so that the blood vessels are enhanced and the background information is suppressed. The fuzzy clustering algorithm is then employed to the previous enhanced image for segmentation. After the fuzzy segmentation, a purification procedure is used to reduce the weak edges and noise, and the final results of the blood vessels are consequently achieved. The performance of the proposed method is compared with some existing segmentation methods and hand-labeled segmentations. The approach has been tested on a series of retinal images, and experimental results show that our technique is promising and effective.<\/jats:p>","DOI":"10.2478\/v10006-008-0036-5","type":"journal-article","created":{"date-parts":[[2008,10,7]],"date-time":"2008-10-07T16:00:58Z","timestamp":1223395258000},"page":"399-407","source":"Crossref","is-referenced-by-count":74,"title":["An Automatic Hybrid Method for Retinal Blood Vessel Extraction"],"prefix":"10.61822","volume":"18","author":[{"given":"Yong","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuying","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nini","family":"Rao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"37438","reference":[{"key":"1","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1109\/TFUZZ.2004.839667","article-title":"Different averages of a fuzzy set with an application to vessel segmentation","volume":"3","author":"G. 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(1994). <i>Classification of blood vessels in ocular fundus images<\/i>, Technical report, University of California, San Diego, CA."},{"key":"9","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1080\/01969727308546046","article-title":"A fuzzy relative of the ISODATA process and its use in detecting compact well separated clusters","volume":"3","author":"J. Dunn","year":"1973","journal-title":"Journal of Cybernetics"},{"key":"10","first-page":"498","article-title":"Fuzzy edge detection with minimum fuzzy entropy criterion","volume":"1","author":"S. EI-Khamy","year":"2002"},{"key":"11","first-page":"881","article-title":"A method of vessel tracking for vessel diameter measurement on retinal images","volume":"2","author":"X. Gao","year":"2001"},{"key":"12","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1109\/42.845178","article-title":"Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response","volume":"3","author":"A. 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