Images are often contaminated with noise due to sensor errors or during transmission. Noise in an image reduces the effectiveness of subsequent image processing operations, such as edge detection, segmentation, and object recognition. The use of an appropriate filter to reduce or eliminate noise in medical images shortens imaging time and consequently minimizes the exposure of patients to X-ray radiation. In the medical field, this improvement can enhance a physician’s analysis of captured images, thereby reducing medical errors. In conventional noise removal methods using wavelet coefficient thresholding, the threshold value is uniformly applied to all image coefficients, leading to abrupt changes in values close to the threshold and causing image distortions. To address this issue, fuzzy logic is employed to achieve more effective noise reduction, overcoming the shortcomings of traditional thresholding methods and ensuring that the resulting image is not only quantitatively enhanced but also subjectively satisfactory. Due to its ability to model uncertain and approximate values, fuzzy logic can be effectively utilized for image denoising. By accepting approximation in data processing, fuzzy logic often provides more suitable behavior in many cases. This study aims to introduce an innovative approach for noise removal from CT scan images with the highest precision and sensitivity, considering evaluation criteria such as Peak Signal-to-Noise Ratio (PSNR) and Signal-to-Noise Ratio (SNR), among others. The proposed method integrates wavelet transform and fuzzy logic to establish a novel approach to noise reduction, overcoming existing challenges in this domain through fuzzy logic rules.
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Kargaran,D. , Moallem,P. and Hashemi,M. (2021). Noise Reduction in CT Scan Images Using Wavelet Transform and Fuzzy Logic. Transactions on Machine Intelligence, 4(3), 118-127. doi: 10.47176/TMI.2021.118
MLA
Kargaran,D. , , Moallem,P. , and Hashemi,M. . "Noise Reduction in CT Scan Images Using Wavelet Transform and Fuzzy Logic", Transactions on Machine Intelligence, 4, 3, 2021, 118-127. doi: 10.47176/TMI.2021.118
HARVARD
Kargaran D., Moallem P., Hashemi M. (2021). 'Noise Reduction in CT Scan Images Using Wavelet Transform and Fuzzy Logic', Transactions on Machine Intelligence, 4(3), pp. 118-127. doi: 10.47176/TMI.2021.118
CHICAGO
D. Kargaran, P. Moallem and M. Hashemi, "Noise Reduction in CT Scan Images Using Wavelet Transform and Fuzzy Logic," Transactions on Machine Intelligence, 4 3 (2021): 118-127, doi: 10.47176/TMI.2021.118
VANCOUVER
Kargaran D., Moallem P., Hashemi M. Noise Reduction in CT Scan Images Using Wavelet Transform and Fuzzy Logic. Trans. Mach. Intell., 2021; 4(3): 118-127. doi: 10.47176/TMI.2021.118
