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Speckle noise removal in ultrasound images by first- and second-order total variation

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Abstract

Speckle noise contamination is a common issue in ultrasound imaging system. Due to the edge-preserving feature, total variation (TV) regularization-based techniques have been extensively utilized for speckle noise removal. However, TV regularization sometimes causes staircase artifacts as it favors solutions that are piecewise constant. In this paper, we propose a new model to overcome this deficiency. In this model, the regularization term is represented by a combination of total variation and high-order total variation, while the data fidelity term is depicted by a generalized Kullback-Leibler divergence. The proposed model can be efficiently solved by alternating direction method with multipliers (ADMM). Compared with some state-of-the-art methods, the proposed method achieves higher quality in terms of the peak signal to noise ratio (PSNR) and the structural similarity index (SSIM). Numerical experiments demonstrate that our method can remove speckle noise efficiently while suppress staircase effects on both synthetic images and real ultrasound images.

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Acknowledgements

The authors would like to thank Meriem Hacini (Laboratoire d’ Automatique et de Robotique, Algeria) for providing the real ultrasound images. This research is supported by 973 Program (2013CB329404), NSFC (61370147, 11401081, 61402082).

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Authors and Affiliations

  1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, People’s Republic of China

    Si Wang

  2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, People’s Republic of China

    Ting-Zhu Huang, Xi-Le Zhao, Jin-Jin Mei & Jie Huang

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  1. Si Wang
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Correspondence to Ting-Zhu Huang.

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Wang, S., Huang, TZ., Zhao, XL. et al. Speckle noise removal in ultrasound images by first- and second-order total variation. Numer Algor 78, 513–533 (2018). https://doi.org/10.1007/s11075-017-0386-x

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