Literature DB >> 16212291

Screening patients with the corneal navigator.

Stephen D Klyce1, Michael D Karon, Michael K Smolek.   

Abstract

PURPOSE: To present a corneal topography screening device for the detection of corneal ectasias and various refractive procedures based on corneal topography patterns.
METHODS: A database of corneal topography patterns were analyzed and used to "train" a neural network on nine different corneal topography patterns using nineteen corneal topography indices of corneal shape and power.
RESULTS: Sample normal and corneal topographies were recognized correctly.
CONCLUSIONS: The use of the corneal navigator to screen various corneal topographies aids clinical diagnosis.

Entities:  

Mesh:

Year:  2005        PMID: 16212291     DOI: 10.3928/1081-597X-20050902-12

Source DB:  PubMed          Journal:  J Refract Surg        ISSN: 1081-597X            Impact factor:   3.573


  9 in total

1.  Distinguishing Highly Asymmetric Keratoconus Eyes Using Combined Scheimpflug and Spectral-Domain OCT Analysis.

Authors:  Eric S Hwang; Claudia E Perez-Straziota; Sang Woo Kim; Marcony R Santhiago; J Bradley Randleman
Journal:  Ophthalmology       Date:  2018-07-25       Impact factor: 12.079

2.  Epithelial remodeling as basis for machine-based identification of keratoconus.

Authors:  Ronald H Silverman; Raksha Urs; Arindam Roychoudhury; Timothy J Archer; Marine Gobbe; Dan Z Reinstein
Journal:  Invest Ophthalmol Vis Sci       Date:  2014-03-13       Impact factor: 4.799

3.  Distinguishing Highly Asymmetric Keratoconus Eyes Using Dual Scheimpflug/Placido Analysis.

Authors:  Oren Golan; Andre L Piccinini; Eric S Hwang; Ildamaris Montes De Oca Gonzalez; Mark Krauthammer; Sumitra S Khandelwal; David Smadja; J Bradley Randleman
Journal:  Am J Ophthalmol       Date:  2019-02-02       Impact factor: 5.258

4.  Discriminant Value of Custom Ocular Response Analyzer Waveform Derivatives in Forme Fruste Keratoconus.

Authors:  Allan Luz; Bernardo Lopes; Katie M Hallahan; Bruno Valbon; Bruno Fontes; Paulo Schor; William J Dupps; Renato Ambrósio
Journal:  Am J Ophthalmol       Date:  2015-12-29       Impact factor: 5.258

5.  Keratoconus diagnosis with optical coherence tomography pachymetry mapping.

Authors:  Yan Li; David M Meisler; Maolong Tang; Ake T H Lu; Vishakha Thakrar; Bibiana J Reiser; David Huang
Journal:  Ophthalmology       Date:  2008-11-05       Impact factor: 12.079

6.  Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

Authors:  Yi Xie; Lanqin Zhao; Xiaonan Yang; Xiaohang Wu; Yahan Yang; Xiaoman Huang; Fang Liu; Jiping Xu; Limian Lin; Haiqin Lin; Qiting Feng; Haotian Lin; Quan Liu
Journal:  JAMA Ophthalmol       Date:  2020-05-01       Impact factor: 7.389

7.  Evaluation of machine learning classifiers in keratoconus detection from orbscan II examinations.

Authors:  Murilo Barreto Souza; Fabricio Witzel Medeiros; Danilo Barreto Souza; Renato Garcia; Milton Ruiz Alves
Journal:  Clinics (Sao Paulo)       Date:  2010       Impact factor: 2.365

8.  Elevation Matrix Data in the Evaluation of Keratoconus and Normal Corneas.

Authors:  Jaime Tejedor; Francisco J Gutiérrez-Carmona
Journal:  Ophthalmol Ther       Date:  2022-01-15

9.  Predictive Ability of Galilei to Distinguish Subclinical Keratoconus and Keratoconus from Normal Corneas.

Authors:  Sepehr Feizi; Mehdi Yaseri; Bahareh Kheiri
Journal:  J Ophthalmic Vis Res       Date:  2016 Jan-Mar
  9 in total

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