Impact of lens autofluorescence and opacification on retinal imaging.

Leon von der EmdeGeena C RennenMarc VaisbandJan HasenauerRaffael G LieglMonika FleckensteinMaximilian PfauFrank G HolzThomas Ach

Published in: BMJ open ophthalmology (2024)

The use of CNN-based retinal image quality assessment achieved excellent results. The study highlights the vulnerability of BAF to lenticular remodelling. These results can aid in the development of cut-off values for clinical studies, ensuring reliable data collection for the monitoring of retinal diseases.

Keyphrases

optical coherence tomography
diabetic retinopathy
optic nerve
high resolution
deep learning
electronic health record
machine learning
big data
convolutional neural network
mass spectrometry
data analysis
fluorescence imaging