Automated diabetic retinopathy detection with two different retinal imaging devices using artificial intelligence: a comparison study.

Valentina SaraoDaniele VerittiPaolo Lanzetta

Published in: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie (2020)

The automated image analysis software is well suited to work with different imaging technologies. It achieved a better diagnostic performance when the white LED confocal scanner is used. Further evaluation in the context of screening campaigns is needed.

Keyphrases

diabetic retinopathy
artificial intelligence
machine learning
optical coherence tomography
deep learning
high resolution
big data
high throughput
computed tomography
magnetic resonance imaging
magnetic resonance
mass spectrometry
image quality
fluorescence imaging
data analysis