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 Abràmoff, Gilbert Lim, Dinesh Kumar, Philippe Burlina, Neil M. Bressler, Herbert F. Jelinek, Fabrice Meriaudeau, Gwénolé Quellec, Tom Macgillivray, Bal Dhillon

Research output: Contribution to journalArticlepeer-review

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 (US)
Pages (from-to)3546-3559
Number of pages14
JournalUnknown Journal
Volume54
Issue number5
DOIs
StatePublished - May 2013
Externally publishedYes

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

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