• Mrs.P.Elaveni
• V.T.Sivasubbu
• R.Vignesh

The detection of brain tumour is one of the most challenging tasks in the field of medical image processing, since brain images are very complicated and tumours can be analyze efficiently only by the expert radiologists. Therefore, there is a significant need to automate this process. Segmentation of human brain from MRI scan slices without human intervention has become one of the most active research areas in the field of medical image processing. Brain segmentation has various important applications in diagnosing a number of disorders. The main aim of this research work is to recognize a tumour and its quantifications from a specific MRI scan of a brain image thereby obtaining the quantitative analysis of MRI brain tumour which allows useful key indicators of disease progression. Thresholding approach segment scalar images by generating a binary partitioning of the image intensities. Otsu's technique is used to automatically carry out histogram shape-based image thresholding. Then, Compute the area of the tumour by fully automated process and its symmetry analysis. Segmentation is done on basis of a threshold, due to which whole image is converted into binary image. Finally SVM is used to carry out the actual classification.

Graphical User Interfacing (GUI), brain tumour, Magnetic resonance imaging, Otsu thresholding, Tumour segmentation, Magnetic resonance imaging, SVM Classifier, MATLAB.

"A Novel Approach to Brain Tumour Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.54-58, May-2019, Available :http://www.jetir.org/papers/JETIRBM06010.pdf

"A Novel Approach to Brain Tumour Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp54-58, May-2019, Available at : http://www.jetir.org/papers/JETIRBM06010.pdf