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Abstract
This study aims to develop an integrated system for segmentation and classification of MRI images of the patient's brain by reducing noise in the image using the Cycle-GANs method. This method aims to improve the accuracy of segmentation and classification results by reducing the impact of noise on the image. Furthermore, the developed model will be combined into an integrated system with segmentation and classification models to obtain better results in the process of diagnosis and treatment of various medical conditions in patients.