International Journal of Engineering and Technology

detection of the tumour in a human brain is a challenging problem, due to the arrangement of the tumour cells in the brain. This paper presents an analytical method that improves the detection of brain tumour cells in its early stages and to analyze anatomical structures by classification of the samples in support vector machine and tumour cell segmentation of the sample using gray level co-occurrence matrix and extracted features. The support vector machine is used to train and classify the stage of brain tumour that would be benign, malignant or normal, and classifying the tumour for 80%. The automatic support intelligent system is proposed to detect brain tumour through the combination of discrete wavelet transform and support vector machine. This system helps to diagnose brain tumour and in vain for its treatment.