Avanaki, Mohammadreza R.N. and Marques, Manuel J. and Bradu, Adrian and Hojjatoleslami, Ali and Podoleanu, Adrian Gh. (2013) A new algorithm for speckle reduction of optical coherence tomography images. In: Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVIII. Proceedings of SPIE . SPIE. ISBN 978-0-8194-9847-2. (doi:10.1117/12.2041943) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:49355)
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Official URL: http://dx.doi.org/10.1117/12.2041943 |
Abstract
In this study, we present a new algorithm based on an artificial neural network (ANN) for reducing speckle noise from optical coherence tomography (OCT) images. The noise is modeled for different parts of the image using Rayleigh distribution with a noise parameter, sigma, estimated by the ANN. This is then used along with a numerical method to solve the inverse Rayleigh function to reduce the noise in the image. The algorithm is tested successfully on OCT images of retina, demonstrating a significant increase in the signal-to-noise ratio (SNR) and the contrast of the processed images.
Item Type: | Book section |
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DOI/Identification number: | 10.1117/12.2041943 |
Uncontrolled keywords: | Artificial neural network; Despeckling; Eye images; Image quality improvement; Optical coherence tomography (OCT); Speckle |
Subjects: |
Q Science > QC Physics R Medicine > R Medicine (General) > R857.O6 Optical instruments |
Divisions: | Divisions > Division of Natural Sciences > Physics and Astronomy |
Depositing User: | M.J.M. Marques |
Date Deposited: | 16 Jul 2015 09:49 UTC |
Last Modified: | 05 Nov 2024 10:33 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/49355 (The current URI for this page, for reference purposes) |
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