Quantification of posterior capsular opacification in digital images after cataract surgery.

PURPOSE To describe a software program developed to provide an objective assessment of the amount of posterior capsular opacification (PCO) in high-resolution digital images of the posterior capsule after cataract surgery. METHODS Images are analyzed by a set protocol of defining the area of the posterior capsule, removing the Purkinje light reflexes by intensity segmentation, contrast enhancement, filtering to enhance low-density PCO, and variance analysis using a co-occurrence matrix to assess texture. The accuracy of the system was tested for validity and repeatability. RESULTS The software developed has been demonstrated to be an objective method of quantifying PCO. In validation tests, the image analysis-derived measure of PCO showed good agreement with clinically derived measures of PCO. Clinicians assessed PCO on a computer screen image and also under slit lamp examination (Pearson correlation coefficient for both methods >0.92). The entire acquisition and analysis system was demonstrated to have a confidence limit for 2 SDs of 9.8% for group data. CONCLUSIONS This system is capable of producing an accurate and reproducible measure of PCO that is relevant to assessing techniques of PCO prevention.