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Deep learning for ultra-widefield imaging: a scoping review.

Nishaant BhambraFares AntakiFarida El MaltAnQi XuRenaud Duval
Published in: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie (2022)
The application of DL to UWF imaging has demonstrated significant effectiveness in the diagnosis and detection of ophthalmic diseases including diabetic retinopathy, retinal detachment, and glaucoma. DL has also been applied in the generation of synthetic ophthalmic images. This scoping review highlights and discusses the current uses of DL with UWF imaging, and the future of DL applications in this field.
Keyphrases
  • high resolution
  • diabetic retinopathy
  • deep learning
  • optical coherence tomography
  • randomized controlled trial
  • mass spectrometry
  • current status
  • fluorescence imaging
  • optic nerve
  • real time pcr