Digital image capture and automated analysis of posterior capsular opacification

David S. Friedman, Donald D. Duncan, Beatriz Munoz, Sheila K. West, Oliver D. Schein

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Purpose. To develop and validate a digital imaging and analysis technique for assessing the extent of posterior capsular opacification after cataract surgery. Methods. Retroillumination images of the posterior capsule were obtained by using a digital camera mounted on a slit lamp. The images were analyzed using an available image analysis software program. The image acquisition and analysis techniques were tested for face validity, reproducibility, and the ability to detect progression of capsular opacity over time. Results. Digital retroillumination images were obtained without patient discomfort. Automated analysis of images correlated well with clinical grading both at slit lamp examination and when looking at the images themselves (Spearman's correlation coefficient >0.7). Analysis of images taken at different times showed high reproducibility (intraclass correlation >0.9), and the system was able to identify progression of capsular opacity over a 2-year period with a mean increase of 15.8% in progressors versus an increase of 0.6% in nonprogressors (P < 0.05). Conclusions. Digital retroillumination images of the posterior capsule can be obtained reliably, and automated analyses correlate well with clinical assessment. The system presented here uses commercially available instruments and software, and it is practical for use in longitudinal studies of posterior capsule opacification. It is reliable, easy to use, and can detect small changes in the percentage area covered by posterior capsule opacification over time.

Original languageEnglish (US)
Pages (from-to)1715-1726
Number of pages12
JournalInvestigative Ophthalmology and Visual Science
Issue number8
StatePublished - 1999

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience


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