26 March 2013 Automated multilayer segmentation and characterization in 3D spectral-domain optical coherence tomography images
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Proceedings Volume 8567, Ophthalmic Technologies XXIII; 85670P (2013) https://doi.org/10.1117/12.2003172
Event: SPIE BiOS, 2013, San Francisco, California, United States
Abstract
Spectral-domain optical coherence tomography (SD-OCT) is a 3-D imaging technique, allowing direct visualization of retinal morphology and architecture. The various layers of the retina may be affected differentially by various diseases. In this study, an automated graph-based multilayer approach was developed to sequentially segment eleven retinal surfaces including the inner retinal bands to the outer retinal bands in normal SD-OCT volume scans at three different stages. For stage 1, the four most detectable and/or distinct surfaces were identified in the four-times-downsampled images and were used as a priori positional information to limit the graph search for other surfaces at stage 2. Eleven surfaces were then detected in the two-times-downsampled images at stage 2, and refined in the original image space at stage 3 using the graph search integrating the estimated morphological shape models. Twenty macular SD-OCT (Heidelberg Spectralis) volume scans from 20 normal subjects (one eye per subject) were used in this study. The overall mean and absolute mean differences in border positions between the automated and manual segmentation for all 11 segmented surfaces were -0.20 ± 0.53 voxels (-0.76 ± 2.06 μm) and 0.82 ± 0.64 voxels (3.19 ± 2.46 μm). Intensity and thickness properties in the resultant retinal layers were investigated. This investigation in normal subjects may provide a comparative reference for subsequent investigations in eyes with disease.
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Zhihong Hu, Xiaodong Wu, Amirhossein Hariri, SriniVas R. Sadda, "Automated multilayer segmentation and characterization in 3D spectral-domain optical coherence tomography images", Proc. SPIE 8567, Ophthalmic Technologies XXIII, 85670P (26 March 2013); doi: 10.1117/12.2003172; https://doi.org/10.1117/12.2003172
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