Volume 14, Issue 1
A Patch-Based Low-Rank Minimization Approach for Speckle Noise Reduction in Ultrasound Images

Xiao-Guang Lv, Fang Li, Jun Liu & Sheng-Tai Lu

Adv. Appl. Math. Mech., 14 (2022), pp. 155-180.

Published online: 2021-11

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  • Abstract

Ultrasound is a low-cost, non-invasive and real-time imaging modality that has proved popular for many medical applications. Unfortunately, the acquired ultrasound images are often corrupted by speckle noise from scatterers smaller than ultrasound beam wavelength. The signal-dependent speckle noise makes visual observation difficult. In this paper, we propose a patch-based low-rank approach for reducing the speckle noise in ultrasound images. After constructing the patch group of the ultrasound images by the block-matching scheme, we establish a variational model using the weighted nuclear norm as a regularizer for the patch group. The alternating direction method of multipliers (ADMM) is applied for solving the established nonconvex model. We return all the approximate patches to their original locations and get the final restored ultrasound images. Experimental results are given to demonstrate that the proposed method outperforms some existing state-of-the-art methods in terms of visual quality and quantitative measures.

  • Keywords

Ultrasound images, patch, speckle noise, low-rank, weighted nuclear norm minimization.

  • AMS Subject Headings

68U10, 15A29, 65K05

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{AAMM-14-155, author = {Lv , Xiao-Guang and Li , Fang and Liu , Jun and Lu , Sheng-Tai}, title = {A Patch-Based Low-Rank Minimization Approach for Speckle Noise Reduction in Ultrasound Images}, journal = {Advances in Applied Mathematics and Mechanics}, year = {2021}, volume = {14}, number = {1}, pages = {155--180}, abstract = {

Ultrasound is a low-cost, non-invasive and real-time imaging modality that has proved popular for many medical applications. Unfortunately, the acquired ultrasound images are often corrupted by speckle noise from scatterers smaller than ultrasound beam wavelength. The signal-dependent speckle noise makes visual observation difficult. In this paper, we propose a patch-based low-rank approach for reducing the speckle noise in ultrasound images. After constructing the patch group of the ultrasound images by the block-matching scheme, we establish a variational model using the weighted nuclear norm as a regularizer for the patch group. The alternating direction method of multipliers (ADMM) is applied for solving the established nonconvex model. We return all the approximate patches to their original locations and get the final restored ultrasound images. Experimental results are given to demonstrate that the proposed method outperforms some existing state-of-the-art methods in terms of visual quality and quantitative measures.

}, issn = {2075-1354}, doi = {https://doi.org/10.4208/aamm.OA-2021-0011}, url = {http://global-sci.org/intro/article_detail/aamm/19980.html} }
TY - JOUR T1 - A Patch-Based Low-Rank Minimization Approach for Speckle Noise Reduction in Ultrasound Images AU - Lv , Xiao-Guang AU - Li , Fang AU - Liu , Jun AU - Lu , Sheng-Tai JO - Advances in Applied Mathematics and Mechanics VL - 1 SP - 155 EP - 180 PY - 2021 DA - 2021/11 SN - 14 DO - http://doi.org/10.4208/aamm.OA-2021-0011 UR - https://global-sci.org/intro/article_detail/aamm/19980.html KW - Ultrasound images, patch, speckle noise, low-rank, weighted nuclear norm minimization. AB -

Ultrasound is a low-cost, non-invasive and real-time imaging modality that has proved popular for many medical applications. Unfortunately, the acquired ultrasound images are often corrupted by speckle noise from scatterers smaller than ultrasound beam wavelength. The signal-dependent speckle noise makes visual observation difficult. In this paper, we propose a patch-based low-rank approach for reducing the speckle noise in ultrasound images. After constructing the patch group of the ultrasound images by the block-matching scheme, we establish a variational model using the weighted nuclear norm as a regularizer for the patch group. The alternating direction method of multipliers (ADMM) is applied for solving the established nonconvex model. We return all the approximate patches to their original locations and get the final restored ultrasound images. Experimental results are given to demonstrate that the proposed method outperforms some existing state-of-the-art methods in terms of visual quality and quantitative measures.

Xiao-Guang Lv, Fang Li, Jun Liu & Sheng-Tai Lu. (1970). A Patch-Based Low-Rank Minimization Approach for Speckle Noise Reduction in Ultrasound Images. Advances in Applied Mathematics and Mechanics. 14 (1). 155-180. doi:10.4208/aamm.OA-2021-0011
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