Automatic Brain Tumor Detection through MRI – A Survey

This review paper, intents to analyze and compare the diverse methods of automatic detection of brain tumor through Magnetic Resonance Image (MRI) used in different stages of Computer Aided Detection System (CAD).Tumor detection and segmentation are two key problems in research undertaken on brain diagnosis. The main techniques for detection and segmentation are clustering based, knowledge-based, Model-based, level-set evolution, or combination of them. In particular, the Preprocessing, Enhancement and Segmentation are studied and compared. Classification procedure used to obtain final results is also discussed. In Preprocessing and Enhancement stage, medical image is converted into standard format and is manipulated for noise reduction by background removal, edge sharpening, filtering process and removal of film artifacts. Segmentation determines the process of dividing an image into disjoint homogenous regions of a medical image. Classification helps to compare the system generated result with the radiologist report are studied and compared.