Brain tumor classification using SVM based AlexNet

Advanced MRI techniques is one of the best proven technique in tumor analysis and visualization. More than a decade, several machine learning techniques have been deployed for tumor segmentation, feature extraction and classification. The outcome ofBrain Tumor classification plays a critical role in diagnosis and further treatment. The efficacy of the conventional machine learning algorithms depends on the feature extraction.Spotting the suitable feature extraction technique is a tedious task in Machine Learning. At present, Deep learning networks are highly capable of extracting prominent features automatically from images for classification. In this paper, the pre-trained CNNs is used to classify three types of brain tumors from the bench mark dataset, T1 weighted contrast enhanced MRI. The pre-trained network was experimented using the segmented brain tumor image. Experimental results show that the pretrained network achieves 95% for tumor classification.