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dc.contributor.authorAl-Fahdawi, Shumoos
dc.contributor.authorQahwaji, Rami S.R.
dc.contributor.authorAl-Waisy, Alaa S.
dc.contributor.authorIpson, Stanley S.
dc.date.accessioned2018-10-11T13:00:52Z
dc.date.available2018-10-11T13:00:52Z
dc.date.issued2015
dc.identifier.citationAl-Fahdawi S, Qahwaji R, Al-Waisy AS and Ipson S (2015) An Automatic Corneal Subbasal Nerve Registration System Using FFT and Phase Correlation Techniques for an Accurate DPN diagnosis. 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 26-28 Oct. IEEE. pp 1035-1041.en_US
dc.identifier.urihttp://hdl.handle.net/10454/16601
dc.descriptionyesen_US
dc.description.abstractConfocal microscopy is employed as a fast and non-invasive way to capture a sequence of images from different layers and membranes of the cornea. The captured images are used to extract useful and helpful clinical information for early diagnosis of corneal diseases such as, Diabetic Peripheral Neuropathy (DPN). In this paper, an automatic corneal subbasal nerve registration system is proposed. The main aim of the proposed system is to produce a new informative corneal image that contains structural and functional information. In addition a colour coded corneal image map is produced by overlaying a sequence of Cornea Confocal Microscopy (CCM) images that differ in their displacement, illumination, scaling, and rotation to each other. An automatic image registration method is proposed based on combining the advantages of Fast Fourier Transform (FFT) and phase correlation techniques. The proposed registration algorithm searches for the best common features between a number of sequenced CCM images in the frequency domain to produce the formative image map. In this generated image map, each colour represents the severity level of a specific clinical feature that can be used to give ophthalmologists a clear and precise representation of the extracted clinical features from each nerve in the image map. Moreover, successful implementation of the proposed system and the availability of the required datasets opens the door for other interesting ideas; for instance, it can be used to give ophthalmologists a summarized and objective description about a diabetic patient’s health status using a sequence of CCM images that have been captured from different imaging devices and/or at different timesen_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.157en_US
dc.rights© 2015 IEEE. Reproduced in accordance with the publisher's self-archiving policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subjectDiabeticen_US
dc.subjectDiabetic peripheral neuropathyen_US
dc.subjectImage registrationen_US
dc.subjectFast Fourier Transformen_US
dc.subjectPhase correlationen_US
dc.subjectAutomatic nerve segmentationen_US
dc.subjectCorneal confocal microscopyen_US
dc.titleAn automatic corneal subbasal nerve registration system using FFT and phase correlation techniques for an accurate DPN diagnosisen_US
dc.status.refereedn/aen_US
dc.typeConference paperen_US
dc.type.versionAccepted Manuscripten_US
refterms.dateFOA2018-10-11T13:00:52Z


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