Deep Learning for Retinal Image Quality Assessment of Optic Nerve Head Disorders.

Journal: Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Published Date:

Abstract

Deep learning (DL)-based retinal image quality assessment (RIQA) algorithms have been gaining popularity, as a solution to reduce the frequency of diagnostically unusable images. Most existing RIQA tools target retinal conditions, with a dearth of studies looking into RIQA models for optic nerve head (ONH) disorders. The recent success of DL systems in detecting ONH abnormalities on color fundus images prompts the development of tailored RIQA algorithms for these specific conditions. In this review, we discuss recent progress in DL-based RIQA models in general and the need for RIQA models tailored for ONH disorders. Finally, we propose suggestions for such models in the future.

Authors

  • Ebenezer Jia Jun Chan
    Duke-NUS School of Medicine, Singapore.
  • Raymond P Najjar
    Singapore Eye Research Institute.
  • Zhiqun Tang
    Visual Neuroscience Group, Singapore Eye Research Institute, Singapore.
  • Dan Milea
    Singapore National Eye Centre.