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Comparative analysis of wavelet transform filtering systems for noise reduction in ultrasound images

Author

Listed:
  • Dominik Vilimek
  • Jan Kubicek
  • Milos Golian
  • Rene Jaros
  • Radana Kahankova
  • Pavla Hanzlikova
  • Daniel Barvik
  • Alice Krestanova
  • Marek Penhaker
  • Martin Cerny
  • Ondrej Prokop
  • Marek Buzga

Abstract

Wavelet transform (WT) is a commonly used method for noise suppression and feature extraction from biomedical images. The selection of WT system settings significantly affects the efficiency of denoising procedure. This comparative study analyzed the efficacy of the proposed WT system on real 292 ultrasound images from several areas of interest. The study investigates the performance of the system for different scaling functions of two basic wavelet bases, Daubechies and Symlets, and their efficiency on images artificially corrupted by three kinds of noise. To evaluate our extensive analysis, we used objective metrics, namely structural similarity index (SSIM), correlation coefficient, mean squared error (MSE), peak signal-to-noise ratio (PSNR) and universal image quality index (Q-index). Moreover, this study includes clinical insights on selected filtration outcomes provided by clinical experts. The results show that the efficiency of the filtration strongly depends on the specific wavelet system setting, type of ultrasound data, and the noise present. The findings presented may provide a useful guideline for researchers, software developers, and clinical professionals to obtain high quality images.

Suggested Citation

  • Dominik Vilimek & Jan Kubicek & Milos Golian & Rene Jaros & Radana Kahankova & Pavla Hanzlikova & Daniel Barvik & Alice Krestanova & Marek Penhaker & Martin Cerny & Ondrej Prokop & Marek Buzga, 2022. "Comparative analysis of wavelet transform filtering systems for noise reduction in ultrasound images," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-26, July.
    • Handle: RePEc:plo:pone00:0270745
    DOI: 10.1371/journal.pone.0270745
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