Journal
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
Volume 9, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fcell.2021.713209
Keywords
uveal melanoma; iris color; artificial intelligence; machine learning; Chinese population
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Funding
- Capital Health Research and Development of Special [2020-1-2052]
- Science & Technology Project of Beijing Municipal Science & Technology Commission [Z201100005520045, Z181100001818003]
- Beijing Municipal Administration of Hospitals Ascent Plan [DFL20150201]
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The study investigated the correlation between iris color and prevalence of UM in the Chinese population using deep learning methods, obtaining satisfactory segmentation results. The iris color spectrum was highly consistent with expert ratings, but showed no significant correlation with UM incidence.
Previous studies have shown that light iris color is a predisposing factor for the development of uveal melanoma (UM) in a population of Caucasian ancestry. However, in all these studies, a remarkably low percentage of patients have brown eyes, so we applied deep learning methods to investigate the correlation between iris color and the prevalence of UM in the Chinese population. All anterior segment photos were automatically segmented with U-NET, and only the iris regions were retained. Then the iris was analyzed with machine learning methods (random forests and convolutional neural networks) to obtain the corresponding iris color spectra (classification probability). We obtained satisfactory segmentation results with high consistency with those from experts. The iris color spectrum is consistent with the raters' view, but there is no significant correlation with UM incidence.
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