DR HAGIS

The DR HAGIS database has been created to aid the development of vessel extraction algorithms suitable for retinal screening programmes. Researchers are encouraged to test their segmentation algorithms using this database.

All thirty-nine fundus images were obtained from a diabetic retinopathy screening programme in the UK. Hence, all images were taken from diabetic patients. Since patients attending these screening programmes exhibit other co-morbidities, the DR HAGIS database consists of following four co-morbidity subgroups:

• Images 1-10: Glaucoma subgroup
• Images 11-20: Hypertension subgroup
• Images 21-30: Diabetic retinopathy subgroup
• Images 31-40: Age-related macular degeneration subgroup

Besides the fundus images, the manual segmentation of the retinal surface vessels is provided by an expert grader. These manually segmented images can be used as the ground truth to compare and assess the automatic vessel extraction algorithms. Masks of the FOV are provided as well to quantify the accuracy of vessel extraction within the FOV only.

The images were acquired in different screening centers, therefore reflecting the range of image resolutions, digital cameras and fundus cameras used in the clinic. The fundus images were captured using a Topcon TRC-NW6s, Topcon TRC-NW8 or a Canon CR DGi fundus camera with a horizontal 45 degree field-of-view (FOV). The images are 4752x3168 pixels, 3456x2304 pixels, 3126x2136 pixels, 2896x1944 pixels or 2816x1880 pixels in size.

The fundus images are saved as compressed JPEG files with 8 bits per colour plane. The ground truth and mask images are saved as binary PNG files.

Source: DR HAGIS