title: An automated retinal image quality grading algorithm.
abstract: This paper introduces an algorithm for the automated assessment of retinal fundus image quality grade. Retinal image quality grading assesses whether the quality of the image is sufficient to allow diagnostic procedures to be applied. Automated quality analysis is an important preprocessing step in algorithmic diagnosis, as it is necessary to ensure that images are sufficiently clear to allow pathologies to be visible. The algorithm is based on standard recommendations for quality analysis by human screeners, examining the clarity of retinal vessels within the macula region. An evaluation against a reference standard data-set is given; it is shown that the algorithm's performance correlates closely with that of clinicians manually grading image quality.
authors.affiliation: University of Lincoln, UK. ahunter@lincoln.ac.uk
authors.forename: Andrew
authors.initials: A
authors.lastname: Hunter
authors.forename: James A
authors.initials: JA
authors.lastname: Lowell
authors.forename: Maged
authors.initials: M
authors.lastname: Habib
authors.forename: Bob
authors.initials: B
authors.lastname: Ryder
authors.forename: Ansu
authors.initials: A
authors.lastname: Basu
authors.forename: David
authors.initials: D
authors.lastname: Steel
mesh_terms: D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012160:Retina / Q000033:anatomy & histology*; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity