Optimal green (red-free) digital imaging of conjunctival vasculature

Ophthalmic Physiol Opt. 2002 May;22(3):234-43. doi: 10.1046/j.1475-1313.2002.00028.x.

Abstract

Aims/background: Green illumination is commonly used to image vessels of the retina and conjunctiva. The purpose was to derive the best optical set-up for imaging vessels of the conjunctiva.

Methods: The concept of exposure density was used to predict a digital camera response to imaging vessels on a scleral background. Practical verification was performed to verify vessel contrast because of the difficulties in measuring the spectral components of the imaging system, such as the spectral reflectivity of vessels and sclera. Images of the same conjunctiva were repetitively taken through different coloured filters, using the Nikon FS-2 photo slit-lamp and recorded on different coloured channels of the Kodak DCS 100 digital camera. Gaussian blurred tubular models were fitted to densitometric profiles across three vessels from each image, allowing vessel contrast and width to be objectively measured. These measures were compared using different optical set-ups.

Results: Optimal exposure density calculations and vessel contrast was obtained with the xenon light source filtered with Wratten 99 (green) and Wratten 96 (neutral density, 0.2 log units) gelatine absorption filters using the green channel of the digital camera. This image set-up was associated with a 46% (99% CI 43-51%) to 64% (99% CI 58-72%) increase in contrast compared with vessels imaged without filtration, using the combined colour channel of the digital camera. Although differences in vessel widths resulted, absolute differences were marginal.

Conclusion: With the increased use of digital imaging, and the need for image processing of vascular networks, image optimisation is beneficial. This study verified the optimal set-up for non-invasively imaging vessels of the bulbar conjunctiva.

Publication types

  • Validation Study

MeSH terms

  • Blood Vessels / anatomy & histology
  • Color
  • Conjunctiva / blood supply*
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Lighting / methods
  • Photography / methods*