OCTID: Optical coherence tomography image database. (January 2020)

• Record Type: Journal Article
• Authors: Gholami, Peyman; Roy, Priyanka; Parthasarathy, Mohana Kuppuswamy; Lakshminarayanan, Vasudevan
• Is Part Of: Computers & electrical engineering. Volume 81(2020)
• Publication Date: 2020-01
• Subjects: Optical coherence tomography -- Image database -- Image processing -- Retinal disease -- Retina -- Macular hole -- Age-related macular degeneration -- Cenrtal serous retinopathy -- Diabetic retinopathy -- Segmentation; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.106532
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Optical coherence tomography (OCT) is a non-invasive imaging modality that is widely used in clinical ophthalmology. OCT images are capable of visualizing deep retinal layers which is crucial for early diagnosis of retinal diseases. In this paper, we describe a comprehensive open-access database containing more than 500 high-resolution images categorized into different pathological conditions. The image classes include Normal (NO), Macular Hole (MH), Age-related Macular Degeneration (AMD), Central Serous Retinopathy (CSR), and Diabetic Retinopathy (DR). The images were obtained from a raster scan protocol with a 2 mm scan length and 512 × 1024 pixel resolution. We have also included 25 normal OCT images with their corresponding ground truth delineations which can be used for an accurate evaluation of OCT image segmentation. In addition, we have provided a user friendly GUI which can be used by clinicians for manual (and semi-automated) segmentation.