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An optimized non-local LMMSE approach for speckle noise reduction of medical ultrasound images

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Abstract

In this paper, a modified linear-minimum-mean-square-error (LMMSE)-based estimator is presented to reduce speckle noise in ultrasound (US) medical images. In order to significantly improve the performance of the LMMSE estimator, we consider the data redundancy feature which naturally exists in the US images. Since the classical LMMSE method, due to the use of local statistics, cannot perform well in areas where the intensity variation is high, we exploit the similarity between pixels to resolve this problem. In this regards, by using characteristics of the second order local statistics and Pearson distance, an optimum set of similar pixels is selected to be used in the proposed LMMSE-based estimator. Therefore, a good balance between maintaining small details and reducing speckle noise in different regions of US images can be achieved. Quantitative and qualitative results on synthetic and real US data demonstrate that the proposed method yields competitive results in despeckling process compared to the state-of-the-art methods.

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Acknowledgments

The authors would like to thank the help of Dr. Mohammad Ghahramani in providing useful comments and editorial assistance with the preparation of this paper.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Guilan, Rasht, Iran

    Niloofar Rahimizadeh & Reza PR Hasanzadeh

  2. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Canada

    Farrokh Janabi-Sharifi

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  1. Niloofar Rahimizadeh
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  2. Reza PR Hasanzadeh
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  3. Farrokh Janabi-Sharifi
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Correspondence to Reza PR Hasanzadeh.

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Rahimizadeh, N., Hasanzadeh, R.P. & Janabi-Sharifi, F. An optimized non-local LMMSE approach for speckle noise reduction of medical ultrasound images. Multimed Tools Appl 80, 9231–9253 (2021). https://doi.org/10.1007/s11042-020-10051-z

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