Multiple layer segmentation and analysis in three-dimensional spectral-domain optical coherence tomography volume scans.

Spectral-domain optical coherence tomography (SD-OCT) is a three-dimensional imaging technique that allows direct visualization of retinal morphology and architecture. The various retinal layers may be affected differentially by various diseases. An automated graph search algorithm is developed to sequentially segment 11 retinal surfaces in SD-OCT volumes using a three-stage approach. In stage 1, the four most easily discernible and/or distinct surfaces are identified in four-times-downsampled images and are used as a priori information to limit the graph search for the other surfaces in stage 2. Eleven surfaces were then detected in two-times-downsampled images in stage 2, and refined in the original images in stage 3 using the graph search integrating the estimated morphological shape models. Twenty macular SD-OCT volume scans from 20 normal subjects are used in this initial study. The overall mean and absolute mean differences in border positions between the automated and manual segmentation for the 11 surfaces are -0.20 ± 0.53 voxels (-0.76 ± 2.06 μm) and 0.82 ± 0.64 voxels (3.19 ± 2.46 μm), respectively. Intensity/reflectivity and thickness properties in various retinal layers are also investigated. This investigation in normal subjects may provide a comparative reference for subsequent adaptations in eyes with diseases.