Purpose: We improved the visibility of the lamina cribrosa (LC), including its posterior boundary, in optical coherence tomography (OCT) images of the human optic nerve head (ONH).
Methods: An adaptive compensation algorithm was developed to overcome a limitation of our standard compensation algorithm, that is the overamplification of noise at high depth. Such limitation currently hampers our ability to distinguish the posterior LC boundary. In adaptive compensation, standard compensation operations are performed until an energy threshold is reached, at which stage the compensation process is stopped to limit noise overamplification in the deeper portion of the OCT image. The performance of adaptive compensation was compared to that of standard compensation using OCT images of 5 human ONHs.
Results: Adaptive compensation significantly reduced the intralayer contrast (a measure of pixel intensity uniformity) in the deeper portion of the OCT images (from 0.62 ± 0.11-0.30 ± 0.03, P < 0.001), indicating successful removal of noise overamplification. Furthermore, adaptive compensation significantly increased the interlayer contrast (a measure of boundary visibility) across the posterior LC boundary (from 0.29 ± 0.13-0.61 ± 0.21, P < 0.001), indicating improved posterior LC boundary visibility.
Conclusions: Adaptive compensation provided significant improvement compared to standard compensation by eliminating noise overamplification at high depth and improving the visibility of the posterior LC boundary. These improvements were performed while maintaining all other benefits of compensation, such as shadow removal and contrast enhancement. Adaptive compensation will help further our efforts to characterize in vivo ONH biomechanics for the diagnosis and monitoring of glaucoma.