DR HAGIS—a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients

Abstract

Abstract. A database of retinal fundus images, the DR HAGIS database, is presented. This database consists of 39 high-resolution color fundus images obtained from a diabetic retinopathy screening program in the UK. The NHS screening program uses service providers that employ different fundus and digital cameras. This results in a range of different image sizes and resolutions. Furthermore, patients enrolled in such programs often display other comorbidities in addition to diabetes. Therefore, in an effort to replicate the normal range of images examined by grading experts during screening, the DR HAGIS database consists of images of varying image sizes and resolutions and four comorbidity subgroups: collectively defined as the diabetic retinopathy, hypertension, age-related macular degeneration, and Glaucoma image set (DR HAGIS). For each image, the vasculature has been manually segmented to provide a realistic set of images on which to test automatic vessel extraction algorithms. Modified versions of two previously published vessel extraction algorithms were applied to this database to provide some baseline measurements. A method based purely on the intensity of images pixels resulted in a mean segmentation accuracy of 95.83% (AE0.67%), whereas an algorithm based on Gabor filters generated an accuracy of 95.71% (AE0.66%).

REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs

“…However, the images correspond to normal subjects and patients with DR and AMD, and no segmentations of the OC are included. DR HAGIS 5 (Holm et al, 2017), HRF 6 (Odstrčilík et al, 2013) CFPs but stereo images. To the best of our knowledge, only DRISHTI-GS and ORIGA include both glaucoma classification labels and OD/OC segmentations.…”

Retinal Image Analysis for Diabetes-Based Eye Disease Detection Using Deep Learning

“…DRHAGIS stands for Diabetic Retinopathy Hypertension Age-related macular degeneration and Glaucoma images database, and was developed by Health Intelligence (Sandback, UK). The database consists of 40 images in which 10 images are affected with glaucoma [53]. ORIGA is the Online Retinal Fundus Image Database for Glaucoma analysis, with 650 data samples, containing 168 glaucomatous and 482 normal images.…”

Recent Techniques and Trends for Retinal Blood Vessel Extraction and Tortuosity Evaluation: A Comprehensive Review

“…All were saved in JPEG format. The dataset also offers a gold standard for comparison [17]. Measurement Platform for Images of the Retina) is a dataset of images from a fundus camera and software for semi-automatic detection of retinal blood vessels.…”

“…Prompt analysis allows physicians to make early diagnoses, evaluate disease, suggest appropriate treatment, and monitor disease progression [4,5,6,7]. Monitored diseases include diabetic retinopathy [5,8,9] and retinopathy of prematurity (ROP) [10,11], while atherosclerotic retinopathy [12], haemorrhages [12,13], age-related macular degeneration (AMD) [14], glaucoma [15,16,17] and hypertension [15,17] are also diagnosed in databases. Table IV clearly lists the databases used with established diagnoses.…”