Corpus ID: 236171000

A Deep Learning-based Quality Assessment and Segmentation System with a Large-scale Benchmark Dataset for Optical Coherence Tomographic Angiography Image

@article{Wang2021ADL,
  title={A Deep Learning-based Quality Assessment and Segmentation System with a Large-scale Benchmark Dataset for Optical Coherence Tomographic Angiography Image},
  author={Yufei Wang and Yiqing Shen and Meng Yuan and Jing Xu and Bin Yang and Chi Liu and Wenjia Cai and Weijing Cheng and Wei Wang},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.10476}
}
  • Yufei Wang, Yiqing Shen, +6 authors Wei Wang
  • Published 2021
  • Computer Science, Engineering
  • ArXiv
Optical Coherence Tomography Angiography (OCTA) is a non-invasive and non-contacting imaging technique providing visualization of microvasculature of retina and optic nerve head in human eyes in vivo. The adequate image quality of OCTA is the prerequisite for the subsequent quantification of retinal microvasculature. Traditionally, the image quality score based on signal strength is used for discriminating low quality. However, it is insufficient for identifying artefacts such as motion and off… Expand

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