Cognitive Computing , Cognitive Architecture , Cognitive load analysis, learning , Human memory Process

This research work attempted to determine the brain activation level influence of stress in tumor affected region using MRI data. By applying Discrete Wavelet Transform (DWT) to pixel slices, researchers identify active neurons and stress levels. The Equal Interval Method clusters pixel values to detect high-density regions, indicating tumor impact. Frequency analysis reveals stressed versus relaxed neurons, helping forecast tumor zones. Preprocessing of NRRD files enables accurate visualization, and clustering techniques enhance precision. The methodology combines neuron activity computation and density-based clustering to understand the relationship between brain stress and tumor presence.The research involves using slices of the raw raster data to generate frequency waves, which calculates the pixel position variation. Although the sliced pictures are employed for tumor-affected region identification, this is done utilising the approaches of the Equal Interval. Study the relationship between stressed/relaxed neurons in the tumor-affecting brain MRI and stress level in the tumor. Digital Number (DN) values from image frames represent pixel density, which helps identify active or inactive neurons. Frequency waves are generated from these values, showing different patterns based on neuron activeness. Stress levels are computed based on frequency variations, categorized as inactive, low, normal, stress, and high stress. The analysis revealed a high percentage of neurons under stress, indicating a malignant condition. This method effectively links high-frequency wave patterns to elevated stress levels in brain scans.