Automated detection of retinal layer structures on optical coherence tomography images
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- 12 December 2005
- journal article
- Published by Optica Publishing Group in Optics Express
- Vol. 13 (25), 10200-10216
- https://doi.org/10.1364/opex.13.010200
Abstract
Segmentation of retinal layers from OCT images is fundamental to diagnose the progress of retinal diseases. In this study we show that the retinal layers can be automatically and/or interactively located with good accuracy with the aid of local coherence information of the retinal structure. OCT images are processed using the ideas of texture analysis by means of the structure tensor combined with complex diffusion filtering. Experimental results indicate that our proposed novel approach has good performance in speckle noise removal, enhancement and segmentation of the various cellular layers of the retina using the STRATUSOCT™ system.Keywords
This publication has 14 references indexed in Scilit:
- Delineating fluid-filled region boundaries in optical coherence tomography images of the retinaIEEE Transactions on Medical Imaging, 2005
- Macular Segmentation with Optical Coherence TomographyInvestigative Opthalmology & Visual Science, 2005
- Retinal thickness measurements from optical coherence tomography using a Markov boundary modelIEEE Transactions on Medical Imaging, 2001
- Phase-Domain Processing of Optical Coherence Tomography ImagesJournal of Biomedical Optics, 1999
- Speckle in Optical Coherence TomographyJournal of Biomedical Optics, 1999
- Speckle noise reduction for optical coherence tomographyPublished by SPIE-Intl Soc Optical Eng ,1998
- Axioms and fundamental equations of image processingArchive for Rational Mechanics and Analysis, 1993
- Optical Coherence TomographyScience, 1991
- Scale-space and edge detection using anisotropic diffusionIEEE Transactions on Pattern Analysis and Machine Intelligence, 1990
- Using Canny's criteria to derive a recursively implemented optimal edge detectorInternational Journal of Computer Vision, 1987