Application of Morphological Bit Planes in Retinal Blood Vessel Extraction.
The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This p...
| Publicado en: | Journal of Digital Imaging Vol. 26; no. 2; pp. 274 - 287 |
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| Autores principales: | , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2013
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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=104249470&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104249470 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2013 vid: 26 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104249470 86060003 10.1007/s10278-012-9513-3 NLM22832895 PMC3597947 104249470 ppf: 274 ppct: 13 formats: fmt: @attributes: type: P tig: atl: Application of Morphological Bit Planes in Retinal Blood Vessel Extraction. aug: au: Fraz, M. Basit, A. Barman, S. affil: Digital Imaging Research Centre, Faculty of Science Engineering and Computing, Kingston University London, Penrhyn Road Kingston upon Thames KT12EE UK sug: subj: Retinal Vein Radiography Retina Radiography Retinal Artery Radiography Radiographic Image Interpretation, Computer-Assisted Algorithms Retinal Diseases Diagnosis False Positive Results False Negative Results Evaluation Research Predictive Value of Tests Sensitivity and Specificity Human ab: The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This paper reports the development for an automated method for segmentation of blood vessels in retinal images. A unique combination of methods for retinal blood vessel skeleton detection and multidirectional morphological bit plane slicing is presented to extract the blood vessels from the color retinal images. The skeleton of main vessels is extracted by the application of directional differential operators and then evaluation of combination of derivative signs and average derivative values. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. A multidirectional top-hat operator with rotating structuring elements is used to emphasize the vessels in a particular direction, and information is extracted using bit plane slicing. An iterative region growing method is applied to integrate the main skeleton and the images resulting from bit plane slicing of vessel direction-dependent morphological filters. The approach is tested on two publicly available databases DRIVE and STARE. Average accuracy achieved by the proposed method is 0.9423 for both the databases with significant values of sensitivity and specificity also; the algorithm outperforms the second human observer in terms of precision of segmented vessel tree. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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