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%.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999096 | PMC |
http://dx.doi.org/10.1117/1.JMI.3.3.034001 | DOI Listing |
J Med Imaging (Bellingham)
July 2016
University of Western Australia , Centre for Ophthalmology and Visual Science, Lions Eye Institute, 2 Verdun Street, Nedlands, Perth, Western Australia 6009, Australia.
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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!