Brain Tumor Detection Using Image Segmentation Techniques

Brain Tumor is the unconstrained growth of bizarre cells in brain. In this work, dicom Magnetic Resonance Image (MRI) is taken as an input and tried to extract tumor cells from the input image. Pre-processing technique is used to remove noise from image. To this image, k-means clustering is applied and from this clustered image, skull was removed using morphological operations to identify tumor cells easily. Finally, image thresholding is applied to this image followed by levelset segmentation to extract tumor cells. Performance matrices like true positive (TP), true negative (TN), false positive (FP), false negative (FN), precision and recall to measure the accuracy of our results, is also evaluated.