Abstract
Brain Tumor is a dangerous disease. The chance of the death is more in case of the brain tumor. The method of detection and classification of brain tumor is by human intervention with use of medical resonant brain images. MR Images may contain noise or blur caused by MRI operator performance which can lead to difficult in classification. We can apply effective segmentation techniques to partition the image and apply the classification technique. Support Vector machine is the best classification tool we identified as part of this work. The use Support Vector Machine show great potential in this field. SVM is a binary Classifier based on supervised learning which gives better result than other classifiers. SVM classifies between two classes by constructing hyper plane in high-dimensional feature space which can be used for classification.
Highlights
A brain tumor is accumulation of anomalous cells in the brain
Mahajan [4] described about the Brain Tumor detection and Support Vector Machine (SVM) classification
ShwetaJain [5] explains the type of tumor using Artificial Neural Network (ANN) in MRI images of patients
Summary
A brain tumor is accumulation of anomalous cells in the brain This can be classified in to two types of tumors: fatal tumors and benevolent tumors. The brain tumors may yield indications that may be different depending on the different parts of the brain These indications may include continuous pain in head, convulsion, and issue with eyesight, Vomit, and changes in the cerebral. The continuous pain in head worst in the beginning of the day and went away. Before we go for the removal of the tumor parts from the brain, we need to identify the tumor size, location and clear picture of the tumor. After extracting the features from segmented parts of the brain image and later submitted to support vector machine classifier to determine the tumor. SVM will give the finer results when compared to the other classifiers
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