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A deep learning-based framework for retinal fundus image enhancement.

Kang Geon LeeSu Jeong SongSoochahn LeeHyeong Gon YuDong Ik KimKyoung Mu Lee
Published in: PloS one (2023)
Our enhancement process improves LQ fundus images that suffer from complex degradation significantly. Moreover our customized CNN achieved improved performance over the existing state-of-the-art methods. Overall, our framework can have a clinical impact on reducing re-examinations and improving the accuracy of diagnosis.
Keyphrases
  • deep learning
  • diabetic retinopathy
  • convolutional neural network
  • optical coherence tomography
  • artificial intelligence
  • machine learning