BRAIN TUMOR DETECTION USING LEVEL SEGMENTATION AND K-MEANS CLUSTERING

The unchecked growth of strange tumors of brain cells is known as a brain tumor. Tumor cells are extracted from the tumor using an input magnetic resonance imaging (MRI) scan. Pre-processing techniques are applied to minimize noise. After applying K-means clustering to the image, the skull has been eliminated from the clustered image. Quickly finding tumor cells by looking at their shape.Last, this image is cleaned up using segmentation and thresholding, which get rid of the tumor cells.To evaluate the accuracy of our findings, recall, consistency, false positives(FP),true negatives(TN),true positives (TP), and true negatives (TN) are analyzed.