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Current Medical Imaging


ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Multiresolution Denoising for Optical Coherence Tomography: A Review and Evaluation

Author(s): Aleksandra Pizurica, Ljubomir Jovanov, Bruno Huysmans, Vladimir Zlokolica, Paul De Keyser, Frans Dhaenens and Wilfried Philips

Volume 4, Issue 4, 2008

Page: [270 - 284] Pages: 15

DOI: 10.2174/157340508786404044

Price: $65


Recently emerging non-invasive imaging modality - optical coherence tomography (OCT) – is becoming an increasingly important diagnostic tool in various medical applications. One of its main limitations is the presence of speckle noise which obscures small and low-intensity features. The use of multiresolution techniques has been recently reported by several authors with promising results. These approaches take into account the signal and noise properties in different ways. Approaches that take into account the global orientation properties of OCT images apply accordingly different level of smoothing in different orientation subbands. Other approaches take into account local signal and noise covariances. So far it was unclear how these different approaches compare to each other and to the best available single-resolution despeckling techniques. The clinical relevance of the denoising results also remains to be determined. In this paper we review systematically recent multiresolution OCT speckle filters and we report the results of a comparative experimental study. We use 15 different OCT images extracted from five different three-dimensional volumes, and we also generate a software phantom with real OCT noise. These test images are processed with different filters and the results are evaluated both visually and in terms of different performance measures. The results indicate significant differences in the performance of the analyzed methods. Wavelet techniques perform much better than the single resolution ones and some of the wavelet methods improve remarkably the quality of OCT images.

Keywords: Optical coherence tomography, image denoising, wavelets

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