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 Jelinek, Fabrice Meriaudeau, Gwenole Quellec, Tom MacGillivray, Bal Dhillon

Research output: Contribution to journalArticle

90 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 - May 2013

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    Trucco, E., Ruggeri, A., Karnowski, T., Giancardo, L., Chaum, E., Hubschman, J. P., al-Diri, B., Cheung, C. Y., Wong, D., Abramoff, M., Lim, G., Kumar, D., Burlina, P., Bressler, N. M., Jelinek, H., Meriaudeau, F., Quellec, G., MacGillivray, T., & Dhillon, B. (2013). Validating Retinal Fundus Image Analysis Algorithms: Issues and a Proposal. Investigative Ophthalmology & Visual Science, 54(5), 3546-3559. https://doi.org/10.1167/iovs.12-10347