OCTA-500

Optical coherence tomography angiography (OCTA) is a novel imaging modality that allows a micron-level resolution to present the three-dimensional structure of the retinal vascular.We propose a new multi-modality dataset, dubbed OCTA-500. It contains 500 subjects with 2 field of view (FOV) types, including OCT and OCTA volumes, 6 types of projections, 4 types of text labels and 2 types of pixel-level labels. This dataset contains more than 360K images with a size of about 80GB. Now, OCTA-500 is publicly available. OCTA-500 includes two subsets: OCTA_6M and OCTA_3M.OCTA_6M(No.10001-No.10300): FOV: 6mm*6mm*2mm Volume: 400pixel*400pixel*640pixelOCTA_3M(No.10301-No.10500): FOV: 3mm*3mm*2mm Volume: 304pixel*304pixel*640pixelBoth subsets contain the following information: OCT volumes OCTA volumes Projection Maps -OCT FULL(average) -OCT ILM_OPL (average) -OCT OPL_BM (average) -OCTA FULL (average) -OCTA ILM_OPL (maximum) -OCTA OPL_BM (maximum) Text Label -Gender -Age -OS/OD -Disease Pixel Label -retinal vessel segmentation -foveal avascular zone segmentation Related Papers:-Mingchao Li, Yerui Chen, Zexuan Ji, Keren Xie, Songtao Yuan, Qiang Chen, and Shuo Li.“Image projection network: 3D to 2D image segmentation in OCTA images,” IEEE Trans. Med. Imaging, vol. 39, no. 11 pp. 3343-3354, 2020.-Mingchao Li, Yuhan Zhang, Zexuan Ji, Keren Xie, Songtao Yuan, Qinghuai Liu and Qiang Chen. "IPN-V2 and OCTA-500: Methodology and Dataset for Retinal Image Segmentation," arXiv:2012.07261. Related Codes:IPN: https://github.com/chaosallen/IPN_tensorflowIPN-V2: https://github.com/chaosallen/IPNV2_pytorch Get Password:To get the password of the compressed package, an application email must be sent to [e-mail] with a specified form like below, otherwise may be ignored.Title of Mail:The string of 'OCTA500' can not be empty. It is the fixed form and a special sign we use to identifying your downloading intention from other disturbers like spams.The contents appending to OCTA500 can help us identifying you more easily.OCTA500: your_organization: your_nameBody of Mail:Organization Detail: Your Organization DetailsMain Works: Your Main WorksUsages: YourUsages About This Data Set