Alternate machine validation of early brain tumor detection

In this age of modernization, there exists a trend of computerized completely automated trend of living. In such an age, automated diagnostic systems play an essential role, especially for cancer detection. For the detection of cancer, it is quite difficult to detect cancer in an early stage as symptoms appear in the advanced stage. If cancer detection is made possible at early stages, the mortality rate can be greatly reduced. There are various existing techniques for the detection of cancer, but most of the techniques detect cancer at the advanced stage, thereby bringing down the chance of survival of a patient. The early detection of cancer is a challenge because of the overlapped structure of the cancer cells. In this project digital image processing techniques are used for preprocessing of the images and feature extraction process and support vector machine (SVM) and neural network classifier to checking early stage.