Keratoconus Detection Based on a Single Scheimpflug Image.
cornea
corneal visualization Scheimpflug technology
image statistical analysis
keratoconus
keratoconus detection
Journal
Translational vision science & technology
ISSN: 2164-2591
Titre abrégé: Transl Vis Sci Technol
Pays: United States
ID NLM: 101595919
Informations de publication
Date de publication:
06 2020
06 2020
Historique:
received:
21
02
2020
accepted:
10
05
2020
entrez:
25
8
2020
pubmed:
25
8
2020
medline:
25
8
2020
Statut:
epublish
Résumé
To introduce a new approach for keratoconus detection based on corneal microstructure observed in vivo derived from a single Scheimpflug image. Scheimpflug single-image snapshots from 25 control subjects and 25 keratoconus eyes were analyzed; from each group, five subjects were randomly selected to provide out-of-sample data. Each corneal image was segmented, after which the stromal pixel intensities were statistically modeled with a Weibull distribution. Distribution estimated parameters The combination of CCT (sensitivity = 88%; specificity = 84%) with microscopic parameters extracted from statistical modeling of light intensity distribution, The combination of microscopic and macroscopic corneal parameters extracted from a static Scheimpflug image is a promising, non-invasive tool to differentiate corneal diseases without the need to perform measurements based on induced deformation of the corneal structure. The proposed methodology has the potential to support clinicians in the detection of keratoconus, without compromising patient comfort.
Identifiants
pubmed: 32832241
doi: 10.1167/tvst.9.7.36
pii: TVST-20-2358
pmc: PMC7414642
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Pagination
36Informations de copyright
Copyright 2020 The Authors.
Déclaration de conflit d'intérêts
Disclosure: A. Consejo, None; J. Solarski, None; K. Karnowski, None; J.J. Rozema, None; M. Wojtkowski, None; D.R. Iskander, None
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