Abstract

Medical image noise, ambiguity, and fuzziness pose challenges to the medical image analysis process. To lessen these problems, fuzzy sets are utilized; however, they frequently ignore the pixel's spatial context. The neutrosophic set (NS) is employed in picture denoising to get over these restrictions. Neutronosophic theory, in particular the NS Bilateral filter, NS Wiener filter, NS Median filter, NS gaussian filter, and NS rank-ordered filter, is covered in this paper. The Lung-cancer dataset of X-Ray images is used to assess the performance of different denoising techniques. The effectiveness of NS-based denoising techniques over conventional techniques is demonstrated through comparisons with other approaches, demonstrating the NS's function in X-ray image denoising.

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