Comparison of different smartphone cameras to evaluate conjunctival hyperaemia in normal subjects

Sci Rep. 2019 Feb 4;9(1):1339. doi: 10.1038/s41598-018-37925-5.

Abstract

Despite the significant advantages that smartphones' cameras can provide in teleophthalmology and artificial intelligence applications, their use as black-box systems for clinical data acquisition, without adequate information of the quality of photographs can compromise data accuracy. The aim of this study is to compare the objective and subjective quantification of conjunctival redness in images obtained with calibrated and non-calibrated cameras, in different lighting conditions and optical magnifications. One hundred ninety-two pictures of the eye were taken in 4 subjects using 3 smartphone cameras{Bq, Iphone, Nexus}, 2 lighting levels{high 815 lx, low 122 lx} and 2 magnification levels{high 10x, low 6x}. Images were duplicated: one set was white balanced and color corrected (calibrated) and the other was left as it was. Each image was subjective and objectively evaluated. There were no significant differences in subjective evaluation in any of the conditions whereas many statistically significant main effects and interaction effects were shown for all the objective metrics. The clinician's evaluation was not affected by different cameras, lighting conditions or optical magnifications, demonstrating the effectiveness of the human eye's color constancy properties. However, calibration of a smartphone's camera is essential when extracting objective data from images.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Artificial Intelligence
  • Calibration
  • Color
  • Conjunctival Diseases / diagnosis
  • Conjunctival Diseases / diagnostic imaging*
  • Conjunctival Diseases / physiopathology
  • Female
  • Humans
  • Hyperemia / diagnosis
  • Hyperemia / diagnostic imaging*
  • Hyperemia / physiopathology
  • Lighting
  • Male
  • Ophthalmology / methods
  • Photography / methods
  • Smartphone*
  • Telemedicine / methods*