Comparison of wavelet transform methods and Gaussian filter for noise reduction in PET brain images and evaluation of sequence effect of using these methods in MATLAB

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عنوان دوره: اولین دوره بین المللی و بیست و هشتمین دوره ملی (1400)
today Noise removal from medical images even with the advancement of technology is still a major challenge for researchers. Many algorithms for noise cancellation have been introduced, each with its own advantages and disadvantages. In this paper, after applying the salts of salt pepper, Gaussian, Poisson and Speckel to the color image of brain PET two methods of noise cancellation wavelet and Gaussian filter have been investigated by image quality evaluation parameters. The combination of these methods has also been investigated.. In the meantime, the Gaussian smoothing filter has shown the best result in the SNR index, but this filter reduces the contrast compared to the wavelet, ie the edge in the image disappears.Also in the combination of these methods, as expected, the application of Gaussian filter and then wavelet transform to reduce noise and preserve the edge has shown better results of reverse configuration
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