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Cristina M. Savastano, Gaspare Giovinco, Salvatore Ventre, Emilio Balestrazzi, Antonello Tamburrino; Healthy Retinal Layers Thickness Detection by Optical Coherence Tomography Spectral Domain Images. Invest. Ophthalmol. Vis. Sci. 2011;52(14):3673.
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Accurate diagnosis and management of retinal diseases strictly depend on non-invasive imaging techniques such as Optical Coherence Tomography (OCT) in the frequency domain, which allows the collection of in-vivo retinal structural information without any invasive intervention.Therefore, OCT images segmentation is extremely useful for the detection of each retinal layer thickness. For this aim, the authors developed a fully automatic image segmentation algorithm that provides quantitative thickness measurement of retinal layers.
In order to demonstrate the ability of the software, the authors used 4 healthy eyes images acquired from 4 of the latest commercially available OCT systems: Zeiss Cirrus, RTvue-100 Optovue, Heidelberg Spectralis, Nidek RS-3000.The software is very fast (about 45 s/image on a 2.33 GHz CPU) and the peak memory usage is about 1.3 GB. Therefore, it can be easily embedded in the OCT software provided by the manufacturers, to obtain quasi real time analyses.
The algorithm identifies 6 boundaries and measures thickness of 5 retinal layers: 1) nerve fiber layer, 2) inner plexiform layer and ganglion cell layer, 3) inner nuclear layer and outer plexiform layer, 4) outer nuclear layer and photoreceptor inner segments and 5) photoreceptor outer segments.
The application of this image segmentation technique is very effective to investigate thickness of retinal layers and will be used by the authors to obtain retinal layer thickness normative data for the different OCT systems.
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