title: Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.
abstract: Diabetic Retinopathy (DR) is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.
authors.affiliation: Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil.
authors.forename: Ramon
authors.initials: R
authors.lastname: Pires
authors.affiliation: Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil.
authors.forename: Tiago
authors.initials: T
authors.lastname: Carvalho
authors.affiliation: The Southern Queensland Centre of Excellence in Aboriginal and Torres Strait Islander primary health care, Queensland Health, Brisbane, Australia; Discipline for General Practice, School of Medicine, Brisbane, Queensland, Australia.
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Spurling
authors.affiliation: Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil.
authors.forename: Siome
authors.initials: S
authors.lastname: Goldenstein
authors.affiliation: Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil.
authors.forename: Jacques
authors.initials: J
authors.lastname: Wainer
authors.affiliation: Retinal Division, Albury Eye Clinic, Albury, New South Wales, Australia.
authors.forename: Alan
authors.initials: A
authors.lastname: Luckie
authors.affiliation: Australian School of Advanced Medicine, Macquarie University, Sydney, New South Wales, Australia; Centre for Research in Complex Systems and School of Community Health, Charles Sturt University, Albury, New South Wales, Australia.
authors.forename: Herbert F
authors.initials: HF
authors.lastname: Jelinek
authors.affiliation: Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil.
authors.forename: Anderson
authors.initials: A
authors.lastname: Rocha
mesh_terms: D000328:Adult; D000368:Aged; D001331:Automation; D003930:Diabetic Retinopathy / Q000175:diagnosis* / Q000473:pathology; D005260:Female; D006303:Health Services, Indigenous; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011793:Queensland / Q000208:ethnology; D012372:ROC Curve; D012680:Sensitivity and Specificity