Deep neural networks for evaluation of specular microscopy images of the corneal endothelium with Fuchs’ dystrophy

Sergio Sanchez, Kevin Mendoza, Fernando Quintero, Angélica M. Prada, Alejandro Tello, Virgilio Galvis, Lenny A. Romero, Andres G. Marrugo

Research output: Book / Book Chapter / ReportResearch Bookspeer-review

Abstract

Corneal endothelium assessment is carried out via specular microscopy imaging. However, automated image analysis often fails due to inadequate image quality conditions or the presence of dark regions in pathologies such as Fuchs’ dystrophy. Therefore, an early reliable image classification strategy is required before automated evaluation based on cell segmentation. Moreover, conventional classification approaches rely on manually labeled data which are difficult to obtain. We propose a two-stage semi-supervised classification algorithm, feature detection and prediction of a blurring level and guttae severity that allows us to cluster images based on the degree of segmentation complexity. For validation, we developed a web-based annotation application and surveyed a pair of expert ophthalmologists for grading a portion of the 1169 images. Preliminary results show that this approach provides a reliable and fast approach for corneal endothelial cell (CEC) image classification.

Original languageEnglish
Title of host publicationPattern Recognition and Tracking XXXIV
EditorsMohammad S. Alam, Vijayan K. Asari
PublisherSPIE
ISBN (Electronic)9781510661684
DOIs
StatePublished - 2023
EventPattern Recognition and Tracking XXXIV 2023 - Orlando, United States
Duration: 3 May 20234 May 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12527
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferencePattern Recognition and Tracking XXXIV 2023
Country/TerritoryUnited States
CityOrlando
Period3/05/234/05/23

Keywords

  • IQA
  • cornea guttata
  • corneal endothelium
  • regression score
  • self-supervised
  • specular microscopy

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