Brain Tumor Segmentation and Classification using Spatial Fuzzy C mean and Quadratic Support Vector Machine

Precise detection and classification of brain tumors at a reasonable time is vital to enhance the survival of a patient. But due to the big dimensional and anatomical diversity between brain tumors, this is a difficult job. In this contribution, we are proposing an improved spatial fuzzy c-mean (SFCM) for brain tumor segmentation and a quadratic support vector machine (QSVM) for tumor type classification. When applied to the BraTS 2018 dataset, the acquired segmentation outcomes were shown to be 7.16% and 12.78% better than the conventional fuzzy c-mean (FCM) and k-mean. This method assists radiologists in understanding the medical image and gives a second opinion.