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OCTA-500

Dataset Information

Optical Coherence Tomography Angiography (OCTA) is a retinal imaging method that allows for the three-dimensional structure of retinal blood vessels to be presented with micrometer-level resolution. The OCTA-500 dataset contains three-dimensional data of OCT and OCTA modalities for 500 eyes, six types of projection images, four types of textual labels (age/gender/eye/disease), and seven types of segmentation labels (large vessels/capillaries/arteries/veins/2D FAZ/3D FAZ/retinal layers).

Dataset Meta Information

Dimensions Modality Task Type Anatomical Structures Anatomical Area Number of Categories Data Volume File Format
2D Retinal Image Segmentation Eye Eye 1 300 images PNG

Resolution Details

Dataset Statistics size
min (400, 400)
median (400, 400)
max (400, 400)

Label Information Statistics

Category Retinal Vessel
Number of Images 300
Availability 100%
Small Vessel Count 7364
Medium Vessel Count 20944
Large Vessel Count 148865

Visualization

File Structure

OCTA500 Dataset
|
|-- Label.zip
|-- Code.zip
|-- OCTA_3mm_part1.zip
|-- OCTA_3mm_part2.zip
|-- ......
|-- OCTA_3mm_part8.zip

Authors and Institutions

Mingchao Li (School of Computer Science and Engineering, Nanjing University of Science and Technology)

Yerui Chen (School of Computer Science and Engineering, Nanjing University of Science and Technology)

Zexuan Ji (School of Computer Science and Engineering, Nanjing University of Science and Technology)

Keren Xie (Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University)

Songtao Yuan (Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University)

Qiang Chen (School of Computer Science and Engineering, Nanjing University of Science and Technology)

Shuo Li (Department of Medical Imaging, Western University, Canada)

Source Information

Official Website: https://ieee-dataport.org/open-access/octa-500

Download Link: https://ieee-dataport.org/open-access/octa-500

Article Address: https://ieeexplore.ieee.org/document/9085991

Publication Date: 2020-06

Citation

@article{li2019octa,
  title={OCTA-500},
  author={Li, Mingchao and Chen, Yerui and Yuan, Songtao and Chen, Qiang},
  journal={IEEE Transactions on Medical Imaging},
  volume={39},
  number={9},
  pages={2806--2818},
  year={2019},
  publisher={IEEE},
  doi={10.1109/TMI.2020.2992244},
  url={https://doi.org/10.1109/TMI.2020.2992244}
}

@ARTICLE{9085991,
  author={Li, Mingchao and Chen, Yerui and Ji, Zexuan and Xie, Keren and Yuan, Songtao and Chen, Qiang and Li, Shuo},
  journal={IEEE Transactions on Medical Imaging}, 
  title={Image Projection Network: 3D to 2D Image Segmentation in OCTA Images}, 
  year={2020},
  volume={39},
  number={11},
  pages={3343-3354},
  doi={10.1109/TMI.2020.2992244}}

Original introduction article is here.