Segmentation and Analysis of Brain Tumor using Meta-Heuristic Algorithm

Abnormal cells which accrue in the form of mass tissue is called tumor. A tumor which begins in the brain tissues are generally identified as primary brain tumors. A tumor can either be malignant or benign. Diagnosis of this tumor can be done by neurological examine, computed tomography (CT), magnetic resonance imaging (MRI) and other tests which helps in predicting the right treatment. Early recognition reduces the severity and death rate. This work proposes the two step method to examine the tumor. To enhance the tumor social group optimization assisted Tsallis entropy approach is used and to segment the tumor water shed method is used. This tool is tested with various images in the BRATS dataset. The competence of the proposed work is established by image likeness measures, such as Jaccard, dice, sensitivity and specificity. The result shows that the proposed method is clinically significant as it contributes superior image similarity and statistical measures.