Validating retinal fundus image analysis algorithms: issues and a proposal
- PMID: 23794433
- PMCID: PMC4597487
- DOI: 10.1167/iovs.12-10347
Validating retinal fundus image analysis algorithms: issues and a proposal
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.
Keywords: fundus image analysis; reference standards; validation.
References
-
- Chabouis A, Berdugo M, Meas T, et al. Benefits of Ophdiat, a telemedical network to screen for diabetic retinopathy: a retrospective study in five reference hospital centres. Diabetes Metab. 2009; 35: 228–232. - PubMed
-
- Ding J, Patton N, Deary I, et al. Retinal vascular abnormalities and cognitive dysfunction: a systematic review. Br J Ophthalmol. 2008; 92: 1017–2005. - PubMed
-
- Patton N, Aslam T, McGillivray T, et al. Retinal image analysis: concepts, application and potential. Progr Retin Eye Res. 2006; 25: 99–127. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
