title: An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups.
abstract: Patients without diabetic retinopathy (DR) represent a large proportion of the caseload seen by the DR screening service so reliable recognition of the absence of DR in digital fundus images (DFIs) is a prime focus of automated DR screening research. We investigate the use of a novel automated DR detection algorithm to assess retinal DFIs for absence of DR. A retrospective, masked, and controlled image-based study was undertaken. 17,850 DFIs of patients from six different countries were assessed for DR by the automated system and by human graders. The system's performance was compared across DFIs from the different countries/racial groups. The sensitivities for detection of DR by the automated system were Kenya 92.8%, Botswana 90.1%, Norway 93.5%, Mongolia 91.3%, China 91.9%, and UK 90.1%. The specificities were Kenya 82.7%, Botswana 83.2%, Norway 81.3%, Mongolia 82.5%, China 83.0%, and UK 79%. There was little variability in the calculated sensitivities and specificities across the six different countries involved in the study. These data suggest the possible scalability of an automated DR detection platform that enables rapid identification of patients without DR across a wide range of races.
authors.affiliation: Moorfields Eye Hospital NHS Foundation Trust, London, UK; Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK; National Institute for Health Research Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
authors.forename: George Michael
authors.identifier: 0000-0001-9113-4423
authors.initials: GM
authors.lastname: Saleh
authors.affiliation: Barking, Havering and Redbridge University Hospitals Trust, London, UK.
authors.forename: James
authors.identifier: 0000-0002-8207-2678
authors.initials: J
authors.lastname: Wawrzynski
authors.affiliation: Moorfields Eye Hospital NHS Foundation Trust, London, UK.
authors.forename: Silvestro
authors.identifier: 0000-0002-7624-3880
authors.initials: S
authors.lastname: Caputo
authors.affiliation: Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK; National Institute for Health Research Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
authors.forename: Tunde
authors.identifier: 0000-0001-6265-0381
authors.initials: T
authors.lastname: Peto
authors.affiliation: Statistics Department, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
authors.forename: Lutfiah Ismail
authors.identifier: 0000-0002-0333-6584
authors.initials: LI
authors.lastname: Al Turk
authors.affiliation: Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK.
authors.forename: Su
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK.
authors.forename: Yin
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Moorfields Eye Hospital NHS Foundation Trust, London, UK; National Institute for Health Research Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK; Institute of Ophthalmology, UCL, London, UK.
authors.forename: Lyndon
authors.initials: L
authors.lastname: Da Cruz
authors.affiliation: Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK.
authors.forename: Phil
authors.initials: P
authors.lastname: Smith
authors.affiliation: Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK.
authors.forename: Hongying Lilian
authors.identifier: 0000-0003-2534-737X
authors.initials: HL
authors.lastname: Tang