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. 2012 Nov;17(11):116009.
doi: 10.1117/1.JBO.17.11.116009.

Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform

Shahab Chitchian  1 , Markus A Mayer, Adam R Boretsky, Frederik J van Kuijk, Massoud Motamedi
Affiliations

Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform

Shahab Chitchian et al. J Biomed Opt. 2012 Nov.

Abstract

ABSTRACT. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained.

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Figures

Fig. 1
Fig. 1
SLO image captured by the Spectralis OCT and a corresponding OCT B-Scan (top). The selected image: (a) original; (b) DD-CDWT denoised. Eight ROIs are shown in the original image. Combined application of the proposed denoising algorithm and the averaging method available in clinical systems: (c) 10-frame averaged image; and (d) DD-CDWT denoised of the averaged image.
Fig. 2
Fig. 2
Denoising of an intermediate AMD retinal image: (a) before (20-frame averaged); (b) after DD-CDWT denoising.
See this image and copyright information in PMC

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