FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography

Zhu, H., Crabb, D. P., Schlottmann, P. G., Holm, T. & Garway-Heath, D. F. (2010). FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography. Optics Express, 18(24), pp. 24595-24610. doi: 10.1364/OE.18.024595

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Abstract

Spectral-domain optical coherence tomography (SD-OCT) provides volumetric images of retinal structures with unprecedented detail. Accurate segmentation algorithms and feature quantification in these images, however, are needed to realize the full potential of SD-OCT. The fully automated segmentation algorithm, FloatingCanvas, serves this purpose and performs a volumetric segmentation of retinal tissue layers in three-dimensional image volume acquired around the optic nerve head without requiring any pre-processing. The reconstructed layers are analysed to extract features such as blood vessels and retinal nerve fibre layer thickness. Findings from images obtained with the RTVue-100 SD-OCT (Optovue, Fremont, CA, USA) indicate that FloatingCanvas is computationally efficient and is robust to the noise and low contrast in the images. The FloatingCanvas segmentation demonstrated good agreement with the human manual grading. The retinal nerve fibre layer thickness maps obtained with this method are clinically realistic and highly reproducible compared with time-domain StratusOCTâ„¢.

Item Type: Article
Uncontrolled Keywords: Science & Technology, Physical Sciences, Optics, OPTICS, FIBER LAYER THICKNESS, AUTOMATIC SEGMENTATION, GLAUCOMATOUS EYES, IMAGES, REPRODUCIBILITY, OCT
Subjects: R Medicine > RE Ophthalmology
Divisions: School of Health Sciences > Department of Optometry & Visual Science
URI: http://openaccess.city.ac.uk/id/eprint/3327

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