Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features

RESULTS. The algorithm was able to assign cup, rim, and background correctly to 88% of all pixels. Correlations of the LCDR estimates of glaucoma fellows with those of the reference standard were 0.73 (95% CI, 0.58‐0.83), 0.81 (95% CI, 0.70‐ 0.89), and 0.86 (95% CI, 0.78‐0.91), respectively, whereas the correlation of the algorithm with the reference standard was 0.93 (95% CI, 0.89‐0.96; n 58). CONCLUSIONS. The pixel feature classification algorithm allows objective segmentation of the optic disc from conventional color stereo photographs automatically without human input. The performance of the disc segmentation and LCDR calculation of the algorithm was comparable to that of glaucoma fellows in training and is promising for objective evaluation of optic disc cupping. (Invest Ophthalmol Vis Sci. 2007;48: 1665‐1673) DOI:10.1167/iovs.06-1081