SUMMARY
Even with the enormous progress in medical technology, brain tumor detection is still an extremely tedious and complex task for the physicians. The early and accurate detection of brain tumors enables effective and efficient therapy and thus can result in increased survival rates. Automatic detection and classification of brain tumors have the potential to achieve efficiency and a higher degree of predictable accuracy. However, it is well established that the accuracy performance of automatic detection and classification techniques varies from technique to technique, and tends to be image modality dependent. This paper reviews the state-of-the-art detection techniques and highlights their pros and cons.