Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering
Optical coherence tomography (OCT) has continually evolved and expanded as one of the most valuable routine tests in ophthalmology. However, noise (speckle) in the acquired images causes quality degradation of OCT images and makes it difficult to analyze the acquired images. In this paper, an iterat...
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sg-ntu-dr.10356-831162020-03-07T11:35:26Z Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering Palanisamy, P. Rajan, Jeny Xiaojun, Yu Sudeep, P. V. Issac Niwas, Swamidoss Wang, Xianghong Luo, Yuemei Liu, Linbo School of Chemical and Biomedical Engineering School of Electrical and Electronic Engineering Bilateral filtering Denoising Optical coherence tomography (OCT) has continually evolved and expanded as one of the most valuable routine tests in ophthalmology. However, noise (speckle) in the acquired images causes quality degradation of OCT images and makes it difficult to analyze the acquired images. In this paper, an iterative approach based on bilateral filtering is proposed for speckle reduction in multiframe OCT data. Gamma noise model is assumed for the observed OCT image. First, the adaptive version of the conventional bilateral filter is applied to enhance the multiframe OCT data and then the bias due to noise is reduced from each of the filtered frames. These unbiased filtered frames are then refined using an iterative approach. Finally, these refined frames are averaged to produce the denoised OCT image. Experimental results on phantom images and real OCT retinal images demonstrate the effectiveness of the proposed filter. NMRC (Natl Medical Research Council, S’pore) MOE (Min. of Education, S’pore) Accepted version 2017-05-17T03:57:26Z 2019-12-06T15:12:08Z 2017-05-17T03:57:26Z 2019-12-06T15:12:08Z 2016 Journal Article Sudeep, P. V., Issac Niwas, S., Palanisamy, P., Rajan, J., Xiaojun, Y., Wang, X., et al. (2016). Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering. Computers in Biology and Medicine, 71, 97-107. 0010-4825 https://hdl.handle.net/10356/83116 http://hdl.handle.net/10220/42441 10.1016/j.compbiomed.2016.02.003 en Computers in Biology and Medicine © 2016 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Computers in Biology and Medicine, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.compbiomed.2016.02.003]. 38 p. application/pdf |
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Bilateral filtering Denoising Palanisamy, P. Rajan, Jeny Xiaojun, Yu Sudeep, P. V. Issac Niwas, Swamidoss Wang, Xianghong Luo, Yuemei Liu, Linbo Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering |
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Optical coherence tomography (OCT) has continually evolved and expanded as one of the most valuable routine tests in ophthalmology. However, noise (speckle) in the acquired images causes quality degradation of OCT images and makes it difficult to analyze the acquired images. In this paper, an iterative approach based on bilateral filtering is proposed for speckle reduction in multiframe OCT data. Gamma noise model is assumed for the observed OCT image. First, the adaptive version of the conventional bilateral filter is applied to enhance the multiframe OCT data and then the bias due to noise is reduced from each of the filtered frames. These unbiased filtered frames are then refined using an iterative approach. Finally, these refined frames are averaged to produce the denoised OCT image. Experimental results on phantom images and real OCT retinal images demonstrate the effectiveness of the proposed filter. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Palanisamy, P. Rajan, Jeny Xiaojun, Yu Sudeep, P. V. Issac Niwas, Swamidoss Wang, Xianghong Luo, Yuemei Liu, Linbo |
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Article |
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Palanisamy, P. Rajan, Jeny Xiaojun, Yu Sudeep, P. V. Issac Niwas, Swamidoss Wang, Xianghong Luo, Yuemei Liu, Linbo |
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Palanisamy, P. |
title |
Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering |
title_short |
Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering |
title_full |
Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering |
title_fullStr |
Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering |
title_full_unstemmed |
Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering |
title_sort |
enhancement and bias removal of optical coherence tomography images: an iterative approach with adaptive bilateral filtering |
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2017 |
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https://hdl.handle.net/10356/83116 http://hdl.handle.net/10220/42441 |
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1681037615184216064 |