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.

Deparment of Physiology and Pathophysiology Faculty of Medicine University of Ostrava Ostrava Czech Republic

Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava Ostrava Czech Republic

Department of Imaging Method Faculty of Medicine University of Ostrava Ostrava Czech Republic

Human Motion Diagnostic Center Department of Human Movement Studies University of Ostrava Ostrava Czech Republic

MEDIN a s Nove Mesto na Morave Czech Republic

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