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

Shahab Chitchian, Michael A. Fiddy, Nathaniel M. Fried

Research output: Contribution to journalArticlepeer-review

57 Scopus citations

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 14dB are attained.

Original languageEnglish (US)
Article number014031
JournalJournal of Biomedical Optics
Volume14
Issue number1
DOIs
StatePublished - 2009

Keywords

  • optical coherence tomography
  • prostate nerves
  • wavelet denoising

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials
  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics

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