Validating retinal fundus image analysis algorithms: issues and a proposal

Emanuele Trucco, Alfredo Ruggeri, Thomas Karnowski, Luca Giancardo, Edward Chaum, Jean Pierre Hubschman, Bashir al-Diri, Carol Y. Cheung, Damon Wong, Michael Abramoff, Gilbert Lim, Dinesh Kumar, Philippe Burlina, Neil M. Bressler, Herbert F. Jelinek, Fabrice Meriaudeau, Gwenole Quellec, Tom MacGillivray, Bal Dhillon

    Research output: Contribution to journalArticlepeer-review

    105 Citations (Scopus)

    Abstract

    This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms. For reasons of space and consistency, we concentrate on the validation of algorithms processing color fundus camera images, currently the largest section of the ARIA literature. We sketch the context (imaging instruments and target tasks) of ARIA validation, summarizing the main image analysis and validation techniques. We then present a list of recommendations focusing on the creation of large repositories of test data created by international consortia, easily accessible via moderated Web sites, including multicenter annotations by multiple experts, specific to clinical tasks, and capable of running submitted software automatically on the data stored, with clear and widely agreed-on performance criteria, to provide a fair comparison.

    Original languageEnglish
    Pages (from-to)3546-3559
    Number of pages14
    JournalInvestigative Ophthalmology & Visual Science
    Volume54
    Issue number5
    DOIs
    Publication statusPublished - 24 May 2013

    Keywords

    • AUTOMATED DETECTION
    • VESSEL SEGMENTATION
    • validation
    • GLAUCOMA ANALYSIS
    • fundus image analysis
    • TO-DISC RATIO
    • COST-EFFECTIVENESS
    • MACULAR DEGENERATION
    • CARDIAC CYCLE
    • OPTIC DISC
    • DIABETIC-RETINOPATHY
    • reference standards
    • SCREENING TOOL

    Cite this