Automatic retinal vessel extraction algorithm based on contrast-sensitive schemes

Mohammad A. U. Khan, Toufique A. Soomro, Tariq M. Khan, Donald G. Bailey, Junbin Gao, Nighat Mir

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

21 Citations (Scopus)

Abstract

Retinal vessel segmentation plays a key role in the detection of numerous eye diseases, and its reliable computerised implementation becomes important for automatic retinal disease screening systems. A large number of retinal vessel segmentation algorithms have been reported, primarily based on three main steps including making the background uniform, second-order Gaussian detector application and finally the region-grown bi-narization. Although these methods improve the accuracy levels, their sensitivity to low-contrast vessels still needs attention. In this paper, some contrast-sensitive approaches are discussed that once embedded in the conventional algorithm results in improved sensitivity for a given retinal vessel extraction technique. The impact of these add-on modules is assessed on publicly available databases like DRIVE and STARE and found to provide promising results.
Original languageEnglish
Title of host publicationProceedings of the 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ)
EditorsDonald Bailey, Gourab Sen Gupta, Stephen Marsland
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers
Pages1-5
Number of pages5
ISBN (Electronic)9781509027484, 9781509027477
ISBN (Print)9781509027491
DOIs
Publication statusPublished - 2016
EventInternational Conference on Image and Vision Computing New Zealand (2016) - Palmerston North, New Zealand
Duration: 21 Nov 201622 Nov 2016

Conference

ConferenceInternational Conference on Image and Vision Computing New Zealand (2016)
CityPalmerston North, New Zealand
Period21/11/1622/11/16

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