Automatic Brain Tumor Detection And Classification Using Svm Classifier
Tumor is unwanted growth of unhealthy cell which increase intracranial pressure within skull. Medical image
processing is the most challenging and innovative field specially MRI imaging modalities. The strategy presented in this
paper involves preprocessing, segmentation, feature extraction, detection of tumor and its classification from MRI scanned
brain images. Magnetic Resonance Imaging (MRI) is a non-invasive imaging modalities which is best suited for the
detection of brain tumor. The segmentation method proposed in this paper is fuzzy c-means (FCM) which can improve
medical image segmentation. The algorithm is easy to handle and identification of tumor and its classification in scanned
region has been done accurately. A user friendly environment has been created by using GUI in MATLAB resulting in an
automated brain tumor detection system for MRI scanned images. By using the GUI tool, the physician and other
practitioners are facilitated in detecting the tumor and its geometrical feature extraction. Multi-SVM has used to classify the
various type of tumors like Gliomas, Metastasis, Astrocytoma etc. In this work, Multi Support Vector Machines (m-SVMs)
has been proposed and applied to brain scanned image slices classification using features derived from slices. This work
helps in recognition of tumor which in turn saves the precious time of medical diagnostic to diagnose the tumor
automatically in short span of time.
Keywords— Image Classification, Medical Diagnosis, Tumors.