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This paper focuses on tumor segmentation and detection of MRI brain images using an intuitionistic fuzzy sets method. Now a day, people of all ages are affected by brain tumors because of the uncontrolled growth of tissues in the human brain. This tumor turns into cancer. Segmentation plays an important in detecting different types of tumor, which is developed inside the brain, but in segmentation, it is very difficult which are not properly illuminated. In medical imaging techniques, there are many ways used to detect the location of a brain tumor. Most of them using Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET) to diagnose a brain tumor. In this paper, identifying the immune cells, that can find the tumor cells and for the segmentation of brain image is used Intuitionistic Fuzzy Clustering Mean (IFCM) algorithm to find the new membership values of the pixels, that Pixel identifies depends on the intensity to attract the neighboring pixel towards its own cluster. The experimental results on brain images to detect the tumor and its size by using the imaging techniques.And to take the intuitionistic fuzzy sets for segmentation using a newly designed formula. Each cluster has membership and non-membership degrees as intervals.