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Emanuele Trucco, Alfredo Ruggeri, Thomas Karnowski, Luca Giancardo, Edward Chaum, Jean Pierre Hubschman, Bashir al-Diri, Carol Y. Cheung, Damon Wong, Michael Abràmoff, Gilbert Lim, Dinesh Kumar, Philippe Burlina, Neil M. Bressler, Herbert F. Jelinek, Fabrice Meriaudeau, Gwénolé Quellec, Tom MacGillivray, Bal Dhillon; Validating Retinal Fundus Image Analysis Algorithms: Issues and a Proposal. Invest. Ophthalmol. Vis. Sci. 2013;54(5):3546-3559. doi: https://doi.org/10.1167/iovs.12-10347.
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© ARVO (1962-2015); The Authors (2016-present)
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.
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