An efficient approach to predict tumor in 2D Brain image using classification techniques

The Brain is one of the most important organs in human body. The brain controls everything: sight, hearing, taste, touch, emotions etc. In medical field, brain plays an important role in every aspect. In the last decade one of the dangerous diseases is brain tumour and also prediction of tumour in brain is very difficult process. This proposed system explains how to find the brain tumour in patient´s body using some data mining techniques such as segmentation and classification. Images are considered as one of the most important medium of conveying information. Understanding images and extracting the information from them such that the information can be used for other tasks is an important aspect of Machine learning. One of the first steps in direction of understanding images is to segment them and find out different objects in them. For segmentation we are using K-means clustering algorithm. In the second step we perform classification of MRI brain image using decision tree and SVM classification algorithms and predict which is better classification technique and extract tumour parts in brain. The proposed technique is used to find diseased brain image of patient to match with the database tumour image.