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Content Provider | IEEE Xplore Digital Library |
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Author | Gawish, Ahmed Fieguth, Paul Marschall, Sebastian Bizheva, Kostadinka |
Copyright Year | 2014 |
Description | Author affiliation: Vision and Image Processing (VIP) Lab, Dept. of Systems Design Engineering, University of Waterloo, Waterloo, Canada (Gawish, Ahmed; Fieguth, Paul) || Dept. of Physics and Astronomy, University of Waterloo, Waterloo, Canada (Marschall, Sebastian; Bizheva, Kostadinka) |
Abstract | A limitation of Optical Coherence Tomography (OCT) image segmentation is the poor signal-to-noise ratio of the imaging process, particularly because images are sampled quickly, at high resolutions, and in-vivo. Furthermore, speckle noise is generated by the reflections of the OCT LASER. Because OCT is widely used in imaging the cornea, retina, and skin, OCT layer segmentation is of key interest in all applications. In this paper, a multi-resolution parametric active contour is used for OCT segmentation. The proposed method uses an undecimated wavelet transform to obtain scale-dependent noise reduction, while the active contour is initialized with a generalized Hough transform. Experimental results show that the proposed method outperforms classical as well as state-of-the-art methods and segments OCT images with high level of accuracy. |
Starting Page | 882 |
Ending Page | 886 |
File Size | 1470564 |
Page Count | 5 |
File Format | |
ISBN | 9781479957514 |
DOI | 10.1109/ICIP.2014.7025177 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-10-27 |
Publisher Place | France |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image segmentation Active contours Transforms Noise Cornea Image resolution Image edge detection Hough transform Undecimated wavelet transform optical coherence tomography active contours |
Content Type | Text |
Resource Type | Article |
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