BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    Main article (2.023Mb)
    Download
    Publication date
    2018-07
    Author
    Al-Fahdawi, Shumoos
    Qahwaji, Rami S.R.
    Al-Waisy, Alaa S.
    Ipson, Stanley S.
    Ferdousi, M.
    Malik, R.A.
    Brahma, A.
    Keyword
    Corneal endothelial cells; Automatic cell segmentation; Corneal Confocal Microscopy; Fast Fourier Transform; Watershed transformation; Voronoi Tessellation
    Rights
    © 2018 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    Background and Objective Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. Methods First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). Results The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p < 0.0001) and a Bland–Altman plot shows that 95% of the data are between the 2SD agreement lines. Conclusions We demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image.
    URI
    http://hdl.handle.net/10454/15684
    Version
    Accepted manuscript
    Citation
    Al-Fahdawi S, Qahwaji R, Al-Waisy AS et al (2018) A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology. Computer Methods and Programs in Biomedicine. 160: 11-23.
    Link to publisher’s version
    https://doi.org/10.1016/j.cmpb.2018.03.015
    Type
    Article
    Collections
    Engineering and Informatics Publications

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.