Blood Vessel Extraction From Retinal Images Using Complex Wavelet Transform and Complex-Valued Artificial Neural Network

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dc.contributor.authorCeylan, Murat
dc.contributor.authorYasar, Huseyin
dc.date.accessioned2020-03-26T18:41:13Z
dc.date.available2020-03-26T18:41:13Z
dc.date.issued2013
dc.departmentSelçuk Üniversitesien_US
dc.description36th International Conference on Telecommunications and Signal Processing (TSP) -- JUL 02-04, 2013 -- Rome, ITALYen_US
dc.description.abstractRetinal imaging in ophthalmology plays an important role for the diagnosis of diabetes, cardiovascular disease, etc. In retina images, changes of blood vessels can help the expert to detection of diseases. Manually extraction of blood vessels from retinal images is usually difficult process due to depending on the experience of physician, back-ground artifacts, different acquisition process. Therefore, the aim of this study is to purpose a novel method for automatic blood vessel extraction from retinal image. This study presents a combined structure. This structure is realized with two cascade stages: feature extraction with 4th level Complex Wavelet Transform (CWT) and Complex-Valued Artificial Neural Networks (CVANN) for the blood vessels segmentation. To check the validation of proposed method, public DRIVE database is used. Result of this study has a higher accuracy (98.56 %) than previously studies in the literature.en_US
dc.description.sponsorshipIEEE, Czechoslovakia Sect, Investment & Business Dev Agcy Czech Republ, Brno Univ Technol, Dept Telecommunicat, Budapest Univ Technol & Econ, Dept Telecommunicat, Karadeniz Tech Univ, Dept Elect & Elect Engn, W Pomeranian Univ Technol, Fac Elect Engn, Tech Univ Ostrava, Dept Telecommunicat, Slovak Univ Technol, Inst Telecommunicat, Univ Ljubljana, Lab Telecommunicat, Czech Tech Univ, Dept Telecommunicat Engn, Adv Elect & Elect Engn Journal, Int Journal Adv Telecommunicat, Electrotechn, Signals & Systen_US
dc.description.sponsorshipCoordinatorship Selcuk University's Scientific Researchen_US
dc.description.sponsorshipThis work was supported by the Coordinatorship Selcuk Universitys Scientific Research Projectsen_US
dc.identifier.endpage825en_US
dc.identifier.isbn978-1-4799-0402-0; 978-1-4799-0403-7
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage822en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/29272
dc.identifier.wosWOS:000333968000166en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2013 36TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectBlood vessel extractionen_US
dc.subjectretinal imageen_US
dc.subjectcomplex wavelet transformen_US
dc.subjectcomplex-valued artificial neural networken_US
dc.titleBlood Vessel Extraction From Retinal Images Using Complex Wavelet Transform and Complex-Valued Artificial Neural Networken_US
dc.typeConference Objecten_US

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