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

被引：50

作者：

Chitchian, Shahab ^{[1
]}

Fiddy, Michael A. ^{[1
]}

Fried, Nathaniel M. ^{[1
,2
]}

机构：

[1] Univ N Carolina, Dept Phys & Opt Sci, Charlotte, NC 28223 USA

[2] Johns Hopkins Med Inst, Dept Urol, Baltimore, MD 21287 USA

来源：

JOURNAL OF BIOMEDICAL OPTICS | 2009年 / 14卷 / 01期

关键词：

wavelet denoising; optical coherence tomography; prostate nerves; CAVERNOUS NERVES; RAT PROSTATE;

D O I：

10.1117/1.3081543

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

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. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3081543]

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