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Local Statistics-based Speckle Reducing Bilateral Filter for Medical Ultrasound Images

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Abstract

One of the most widely used medical modality by healthcare industry is ultrasound imaging, which is often corrupted by multiplicative noise (known as speckle). The reduction of such kind of noise from ultrasound images is highly desirable for providing the proper diagnosis of a disease in real-time. The classical bilateral filter (CBF) is well known as most effective edge preserving and denoising filter for Gaussian noise reduction. Therefore, in this paper, a new speckle denoising filter is designed which is based on local statistics, Chi-square-based distance measure and box-based kernel function in bilateral filter framework for application and use in real time. The proposed speckle denoising scheme is tested on various synthetic, B-mode, simulated and real ultrasound images. The various quantitative and qualitative results suggest that the proposed local statistics-based bilateral filter (LSBF) outperforms the various existing speckle noise suppression techniques in term of denoising and restoration of fine textural information in the denoised images. The proposed LSBF method is compared with existing speckle noise reduction methods and experimental results demonstrate that, the proposed LSBF method have better noise removing and structure preserving capability as compared to existing standard denoising filters for speckle noise.

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Acknowledgments

The author would like to thanks Dr. Debhdoot Sheet and Peter C. Tay for providing the code of B-mode simulation and SBF filter. We acknowledge our all the co-authors for providing the proof read, valuable comments and expert scorings which is needful for further improvement of this manuscript. We are also thankful to anonymous reviewers for providing the valuable comments which help us to improve the overall representation of manuscript.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Karamjeet Singh & Ashutosh Aggarwal

  2. Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India

    Bhisham Sharma

  3. Department of Computer Applications, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, 140401, India

    Jaiteg Singh

  4. Department of Mathematics and Computer Science, Brandon University, Brandon, R7A 6A9, Canada

    Gautam Srivastava

  5. Research Center for Interneural Computing, China Medical University, Taichung, 40402, Taiwan, Republic of China

    Gautam Srivastava

  6. Department of Computer Engineering, Marwadi University, Rajkot, 360008, India

    Suchita Sharma

  7. Computer Science, Middlesex University, London, UK

    Xiaochun Cheng

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  1. Karamjeet Singh
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  2. Bhisham Sharma
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  6. Ashutosh Aggarwal
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  7. Xiaochun Cheng
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Correspondence to Karamjeet Singh, Bhisham Sharma or Gautam Srivastava.

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Singh, K., Sharma, B., Singh, J. et al. Local Statistics-based Speckle Reducing Bilateral Filter for Medical Ultrasound Images. Mobile Netw Appl 25, 2367–2389 (2020). https://doi.org/10.1007/s11036-020-01615-2

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