Quantification of sun-related changes in the eye in conjunctival ultraviolet autofluorescence images

Emily Huynh; Danuta M. Bukowska; Seyhan Yazar; Charlotte McKnight; Ajmal Mian; David Mackey

doi:10.1117/1.JMI.3.3.034001

Quantification of sun-related changes in the eye in conjunctival ultraviolet autofluorescence images

Emily Huynh, Danuta M. Bukowska, Seyhan Yazar, Charlotte McKnight, Ajmal Mian, David Mackey

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Abstract

Quantification of sun-related changes in conjunctival ultraviolet autofluorescence (CUVAF) images is a subjective and tedious task, in which reproducibility of results is difficult. Thus, we have developed a semiautomatic method in MATLAB(®) to analyze CUVAF images retrospectively. The algorithm was validated on 200 images from 50 randomly selected participants from the Western Australian Pregnancy Cohort (Raine) study 20-year follow-up assessment, in which CUVAF area measurements were available from previous manual analysis. Algorithm performance was compared to manual measurements and yielded better than 95% correspondence in both intra- and interobserver agreement. Furthermore, the semiautomatic method significantly reduced analysis time by 50%.

Original language	English
Article number	034001
Pages (from-to)	1-7
Number of pages	7
Journal	Journal of Medical Imaging
Volume	3
Issue number	3
DOIs	https://doi.org/10.1117/1.JMI.3.3.034001
Publication status	Published - 1 Jul 2016

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10.1117/1.JMI.3.3.034001

Huynh et.al., 2016 Quantification of Sun-related Changes in the Eye in Conjunctival Ultraviolet Autofluorescence Images
© 2016. Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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abstract = "Quantification of sun-related changes in conjunctival ultraviolet autofluorescence (CUVAF) images is a subjective and tedious task, in which reproducibility of results is difficult. Thus, we have developed a semiautomatic method in MATLAB({\textregistered}) to analyze CUVAF images retrospectively. The algorithm was validated on 200 images from 50 randomly selected participants from the Western Australian Pregnancy Cohort (Raine) study 20-year follow-up assessment, in which CUVAF area measurements were available from previous manual analysis. Algorithm performance was compared to manual measurements and yielded better than 95\% correspondence in both intra- and interobserver agreement. Furthermore, the semiautomatic method significantly reduced analysis time by 50\%.",

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AU - Mian, Ajmal

AU - Mackey, David

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Quantification of sun-related changes in the eye in conjunctival ultraviolet autofluorescence images

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Genes for juvenile-onset myopia

Active Multispectral Computer Vision for Defence & Security

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Quantification of sun-related changes in the eye in conjunctival ultraviolet autofluorescence images

Abstract

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Genes for juvenile-onset myopia

Active Multispectral Computer Vision for Defence & Security

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