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    An automatic corneal subbasal nerve registration system using FFT and phase correlation techniques for an accurate DPN diagnosis

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    Conference paper (636.7Kb)
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    Publication date
    2015
    Author
    Al-Fahdawi, Shumoos
    Qahwaji, Rami S.R.
    Al-Waisy, Alaa S.
    Ipson, Stanley S.
    Keyword
    Diabetic
    Diabetic peripheral neuropathy
    Image registration
    Fast Fourier Transform
    Phase correlation
    Automatic nerve segmentation
    Corneal confocal microscopy
    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.
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    Abstract
    Confocal 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 times
    URI
    http://hdl.handle.net/10454/16601
    Version
    Accepted Manuscript
    Citation
    Al-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.
    Link to publisher’s version
    https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.157
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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