Abstract
This study proposes a novel combined filter accompanied with different optimization algorithms for Poisson noise reduction and increases image quality in digital X-ray and CT images. This filter uses 4th-order PDE, TV, Bayes shrink threshold with optimization algorithms and an exact unbiased inverse of generalized Anscombe transformation (EUIGAT). Experiments were conducted on the basis of displaying the influence of denoising filter on 105 simulated, 102 radiographic and 102 CT images of individuals aged 20–70 years old; 53 men and 49 women. Experimental results demonstrated the lowest value for MSE and the highest values for PSNR, IQI, SSIM, FOM and CNR in different kinds of kernels and images compared with the other fuzzy Bio-inspired algorithms. The results showed proposed method helps physicians and orthopedists in order to enhance their performances in treating injuries of the pelvic region such as acetabulum fossa and head and neck femur bone.
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Available at http://the natural image noise dataset is published on wiki-media commons (https://commons.wikimedia.org/wiki/Natural_Image_Noise_Dataset)
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Rafati, M., Kalantari, N., Azadbakht, J. et al. Performance evaluation of fuzzy genetic, fuzzy particle swarm and similar insects’ optimization algorithms on denoising problem based on novel combined filter for digital X-ray and CT images in Pelvic Region. Multimed Tools Appl 83, 15483–15531 (2024). https://doi.org/10.1007/s11042-023-15341-w
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DOI: https://doi.org/10.1007/s11042-023-15341-w