Purchase this article with an account.
Hiroshi Ishikawa, Jongsick Kim, Thomas R. Friberg, Gadi Wollstein, Larry Kagemann, Michelle L. Gabriele, Kelly A. Townsend, Kyung R. Sung, Jay S. Duker, James G. Fujimoto, Joel S. Schuman; Three-Dimensional Optical Coherence Tomography (3D-OCT) Image Enhancement with Segmentation-Free Contour Modeling C-Mode. Invest. Ophthalmol. Vis. Sci. 2009;50(3):1344-1349. doi: 10.1167/iovs.08-2703.
Download citation file:
© 2017 Association for Research in Vision and Ophthalmology.
purpose. To develop a semiautomated method to visualize structures of interest (SoIs) along their contour within three-dimensional, spectral domain optical coherence tomography (3D SD-OCT) data, without the need for segmentation.
methods. With the use of two SD-OCT devices, the authors obtained 3D SD-OCT data within 6 × 6 × 1.4-mm and 6 × 6 × 2-mm volumes, respectively, centered on the fovea in healthy eyes and in eyes with retinal pathology. C-mode images were generated by sampling a variable thickness plane semiautomatically modeled to fit the contour of the SoI. Unlike published and commercialized methods, this method did not require retinal layer segmentation, which is known to fail frequently in the presence of retinal pathology. Four SoIs were visualized for healthy eyes: striation of retinal nerve fiber (RNF), retinal capillary network (RCN), choroidal capillary network (CCN), and major choroidal vasculature (CV). Various SoIs were visualized for eyes with retinal pathology.
results. Seven healthy eyes and seven eyes with retinal pathology (cystoid macular edema, central serous retinopathy, vitreoretinal traction, and age-related macular degeneration) were imaged. CCN and CV were successfully visualized in all eyes, whereas RNF and RCN were visualized in all healthy eyes and in 42.8% of eyes with pathologies. Various SoIs were successfully visualized in all eyes with retinal pathology.
conclusions. The proposed C-mode contour modeling may provide clinically useful images of SoIs even in eyes with severe pathologic changes in which segmentation algorithms fail.
This PDF is available to Subscribers Only