Literature DB >> 25561067

Computer-Aided Methodology for Syndromic Strabismus Diagnosis.

João Dallyson Sousa de Almeida1, Aristófanes Corrêa Silva, Jorge Antonio Meireles Teixeira, Anselmo Cardoso Paiva, Marcelo Gattass.   

Abstract

Strabismus is a pathology that affects approximately 4 % of the population, causing aesthetic problems reversible at any age and irreversible sensory alterations that modify the vision mechanism. The Hirschberg test is one type of examination for detecting this pathology. Computer-aided detection/diagnosis is being used with relative success to aid health professionals. Nevertheless, the routine use of high-tech devices for aiding ophthalmological diagnosis and therapy is not a reality within the subspecialty of strabismus. Thus, this work presents a methodology to aid in diagnosis of syndromic strabismus through digital imaging. Two hundred images belonging to 40 patients previously diagnosed by an specialist were tested. The method was demonstrated to be 88 % accurate in esotropias identification (ET), 100 % for exotropias (XT), 80.33 % for hypertropias (HT), and 83.33 % for hypotropias (HoT). The overall average error was 5.6Δ and 3.83Δ for horizontal and vertical deviations, respectively, against the measures presented by the specialist.

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Year:  2015        PMID: 25561067      PMCID: PMC4501954          DOI: 10.1007/s10278-014-9758-0

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  12 in total

1.  Kappa and Hirschberg ratio measured with an automated video gaze tracker.

Authors:  Frank Schaeffel
Journal:  Optom Vis Sci       Date:  2002-05       Impact factor: 1.973

2.  Computational methodology for automatic detection of strabismus in digital images through Hirschberg test.

Authors:  João Dallyson Sousa de Almeida; Aristófanes Corrêa Silva; Anselmo Cardoso de Paiva; Jorge Antonio Meireles Teixeira
Journal:  Comput Biol Med       Date:  2011-11-26       Impact factor: 4.589

3.  Fixation-free assessment of the Hirschberg ratio.

Authors:  Dmitri Model; Moshe Eizenman; Veit Sturm
Journal:  Invest Ophthalmol Vis Sci       Date:  2010-04-07       Impact factor: 4.799

4.  Epidemiology of surgical strabismus in Saudi Arabia.

Authors:  Theodore H Curtis; Maureen McClatchey; David T Wheeler
Journal:  Ophthalmic Epidemiol       Date:  2010-10       Impact factor: 1.648

5.  The differential diagnosis of vertical strabismus from prism cover test data using an artificially intelligent expert system.

Authors:  Anthony C Fisher; Arvind Chandna; Ian P Cunningham
Journal:  Med Biol Eng Comput       Date:  2007-07-05       Impact factor: 2.602

6.  Quantitative assessment of the static properties of the oculo-motor system by the photo-oculographic technique.

Authors:  C Buquet; J R Charlier
Journal:  Med Biol Eng Comput       Date:  1994-03       Impact factor: 2.602

7.  Individual case photogrammetric calibration of the Hirschberg Ratio (HR) for corneal light reflection test strabometry.

Authors:  Paul E Romano
Journal:  Binocul Vis Strabismus Q       Date:  2006

8.  The Hirschberg test: correlation with corneal radius and axial length.

Authors:  J B Eskridge; D M Perrigin; N E Leach
Journal:  Optom Vis Sci       Date:  1990-04       Impact factor: 1.973

9.  Evaluation of the relationship between corneal diameter and lens diameter.

Authors:  Christopher Khng; Robert H Osher
Journal:  J Cataract Refract Surg       Date:  2008-03       Impact factor: 3.351

10.  The accuracy of experienced strabismologists using the Hirschberg and Krimsky tests.

Authors:  R Y Choi; B J Kushner
Journal:  Ophthalmology       Date:  1998-07       Impact factor: 12.079

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  5 in total

1.  An artificial intelligence platform for the diagnosis and surgical planning of strabismus using corneal light-reflection photos.

Authors:  Keli Mao; Yahan Yang; Chong Guo; Yi Zhu; Chuan Chen; Jingchang Chen; Li Liu; Lifei Chen; Zijun Mo; Bingsen Lin; Xinliang Zhang; Sijin Li; Xiaoming Lin; Haotian Lin
Journal:  Ann Transl Med       Date:  2021-03

2.  The reliability of the angle of deviation measurement from the Photo-Hirschberg tests and Krimsky tests.

Authors:  S Tengtrisorn; A Tungsattayathitthan; S Na Phatthalung; P Singha; N Rattanalert; S Bhurachokviwat; S Chouyjan
Journal:  PLoS One       Date:  2021-12-01       Impact factor: 3.240

3.  Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions.

Authors:  Yena Christina Kang; Hee Kyung Yang; Young Jae Kim; Jeong-Min Hwang; Kwang Gi Kim
Journal:  Biomed Res Int       Date:  2022-03-24       Impact factor: 3.411

4.  An improved strabismus screening method with combination of meta-learning and image processing under data scarcity.

Authors:  Xilang Huang; Sang Joon Lee; Chang Zoo Kim; Seon Han Choi
Journal:  PLoS One       Date:  2022-08-05       Impact factor: 3.752

5.  An automatic screening method for strabismus detection based on image processing.

Authors:  Xilang Huang; Sang Joon Lee; Chang Zoo Kim; Seon Han Choi
Journal:  PLoS One       Date:  2021-08-03       Impact factor: 3.240

  5 in total

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