Receiving a high dose of radiation by the patient during the CT procedure, The disadvantage of using traditional neural networks for noise reduction of CT images is the presence of a noticeable proportion of random errors in their work, leading to false image artifacts and an erroneous diagnosis of the doctor. Our mathematical apparatus allows us to create and apply figurative-logical neural networks for additional noise reduction, while solving the problem of random errors and artifacts in CT images for existing neural networks.
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