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Journal of Biomedical Optics

Denoising during optical coherence tomography of the prostate nerves via wavelet shrinkage using dual-tree complex wavelet transform
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Paper Abstract

The dual-tree complex wavelet transform (CDWT) is a relatively recent enhancement to the discrete wavelet transform (DWT), with important additional properties. It is nearly shift-invariant and directionally selective in two and higher dimensions. In this letter, a locally adaptive denoising algorithm is applied to reduce speckle noise in time-domain optical coherence tomography (OCT) images of the prostate. The algorithm is illustrated using DWT and CDWT. Applying the CDWT provides improved results for speckle noise reduction in OCT images. The cavernous nerve and prostate gland can be separated from discontinuities due to noise, and image quality metrics improvements with a signal-to-noise ratio increase of 14 dB are attained.

Paper Details

Date Published: 1 January 2009
PDF: 6 pages
J. Biomed. Opt. 14(1) 014031 doi: 10.1117/1.3081543
Published in: Journal of Biomedical Optics Volume 14, Issue 1
Show Author Affiliations
Shahab Chitchian, The Univ. of North Carolina at Charlotte (United States)
Michael A. Fiddy, The Univ. of North Carolina at Charlotte (United States)
Nathaniel M. Fried, The Univ. of North Carolina at Charlotte (United States)

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