A New Blood Vessel Extraction Technique Using Edge Enhancement and Object Classification.
Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic meth...
| Publicado en: | Journal of Digital Imaging Vol. 26; no. 6; pp. 1107 - 1116 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104153853&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104153853 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Dec2013 vid: 26 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104153853 91842815 10.1007/s10278-013-9585-8 NLM23515843 104153853 ppf: 1107 ppct: 9 formats: fmt: @attributes: type: P tig: atl: A New Blood Vessel Extraction Technique Using Edge Enhancement and Object Classification. aug: au: Badsha, Shahriar Reza, Ahmed Tan, Kim Dimyati, Kaharudin affil: Faculty of Engineering, Department of Electrical Engineering, University of Malaya, 50603 Kuala Lumpur Malaysia sug: subj: Blood Vessels Radiography Diabetic Retinopathy Radiography Image Processing, Computer Assisted Evaluation Human Research Methodology Radiology Service ab: Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic method to extract the retinal blood vessel. The proposed method comprises several basic image processing techniques, namely edge enhancement by standard template, noise removal, thresholding, morphological operation, and object classification. The proposed method has been tested on a set of retinal images. The retinal images were collected from the DRIVE database and we have employed robust performance analysis to evaluate the accuracy. The results obtained from this study reveal that the proposed method offers an average accuracy of about 97 %, sensitivity of 99 %, specificity of 86 %, and predictive value of 98 %, which is superior to various well-known techniques. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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