Journal
PLOS ONE
Volume 17, Issue 7, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0270745
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Funding
- project entitled Innovative Therapeutic Methods of Musculoskeletal System in Accident Surgery within the Operational Programme Research [CZ.02.1.01/0.0/0.0/17_049/0008441]
- Ministry of Education of the Czech Republic [SP2022/34, SV4502261/SP2022/98]
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This study analyzes the application effect of wavelet transform in biomedical image processing, evaluates the impact of different wavelet basis functions and noise types on the filtering effect through ultrasound image processing. The results of this study provide guidance for researchers, software developers, and clinical professionals to obtain high-quality images.
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.
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