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Extracting spacing-derived estimates of rod density in healthy retinae.

Heather HeitkotterEmily J PattersonErica N WoertzJenna A CavaMina GaffneyIniya AdhanJohnny TamRobert F CooperJoseph Carroll
Published in: Biomedical optics express (2022)
Quantification of the rod photoreceptor mosaic using adaptive optics scanning light ophthalmoscopy (AOSLO) remains challenging. Here we demonstrate a method for deriving estimates of rod density and rod:cone ratio based on measures of rod spacing, cone numerosity, and cone inner segment area. Twenty-two AOSLO images with complete rod visualization were used to validate this spacing-derived method for estimating density. The method was then used to estimate rod metrics in an additional 105 images without complete rod visualization. The spacing-derived rod mosaic metrics were comparable to published data from histology. This method could be leveraged to develop large normative databases of rod mosaic metrics, though limitations persist with intergrader variability in assessing cone area and numerosity.
Keyphrases
  • deep learning
  • systematic review
  • big data
  • mass spectrometry
  • machine learning
  • electronic health record