1 January 2009 Denoising during optical coherence tomography of the prostate nerves via wavelet shrinkage using dual-tree complex wavelet transform
Author Affiliations +
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.
© (2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Shahab Chitchian, Shahab Chitchian, Michael A. Fiddy, Michael A. Fiddy, Nathaniel M. Fried, Nathaniel M. Fried, } "Denoising during optical coherence tomography of the prostate nerves via wavelet shrinkage using dual-tree complex wavelet transform," Journal of Biomedical Optics 14(1), 014031 (1 January 2009). https://doi.org/10.1117/1.3081543 . Submission:
JOURNAL ARTICLE
6 PAGES


SHARE
Back to Top