Abstract
.Significance: The use of the transscleral illumination approach has the potential to simplify the optical design of fundus cameras. In particular, this approach could allow the use of smaller and cheaper cameras that are easier to use by non-specialists, thereby facilitating a wider spread of eye disease screening programs.Aim: Our aim was to investigate the suitability of transscleral illumination in a fundus camera system. In particular, we explored the impact of the illumination spectrum and the eye pigmentation on the quality of the image. These factors have never been systematically investigated before in the literature on transscleral illumination.Approach: A fundus camera was constructed using transscleral illumination. We studied the influence of eye pigmentation and choice of illumination spectra on the image quality for a group of 10 individuals with varied skin pigmentation, ranging from pale white (North-European) to darkest brown (African). The influence of the light source spectrum on the image quality was assessed using wavelength filters.Results: There was a difference of a factor of 100 in the signal level of retinal images between individuals with low and high skin pigmentation. The image contrast was highest using illumination wavelengths of 500 to 600 nm. The illumination level can be adjusted to obtain high-quality images for highly pigmented eyes while keeping the system eye-safe.Conclusions: We have demonstrated that a fundus camera with transscleral illumination can provide high-quality images. However, the variations observed in scleral and retinal pigmentation in a practical setting require a system that must be able to adapt illumination and/or exposure to the individual patient.
Highlights
A number of common eye diseases can be diagnosed using retina images
We have demonstrated that a fundus camera with transscleral illumination can provide high-quality images
The results show that the illumination spectrum strongly influences the image contrast, and that differences in eye pigmentation cause differences in signal levels; in particular, the signal level between eyes with the lowest and highest pigmentation differs by a factor of 100
Summary
A number of common eye diseases can be diagnosed using retina images. A prominent example is diabetic retinopathy, which is a leading cause of vision loss in many developed countries.[1] Other examples include glaucoma,[2] age-related macular degeneration,[3] retinopathy of prematurity,[4] and malarial retinopathy.[5] Early screening of these diseases can simplify treatment and prevent complications leading to blindness.[6] Currently, this type of screening is performed at hospitals or other specialized institutions using expensive fundus camera systems that capture high-resolution retina images In countries where this type of healthcare service is not available for the majority of the population, such screening is not possible.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call