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Although present advances in deep-learning-based picture renovation algorithms can relieve this dilemma, medical image sets utilized in deep understanding training usually do not align pixel-wise. Consequently, in this research, two different deep-learning-based denoising algorithms-self-supervised discovering and unsupervised learning-are proposed; these algorithms are applicable to medical datasets which are not aligned pixel-wise. The two techniques tend to be c