A Review - Various Segmentation Techniques for Brain Tumor Detection

In the analysis of medical images for computer-aided diagnosis and treatment, segmentation is required as a primary stage. Medical image segmentation is a complex and challenging task due to the intrinsic nature of the images. The brain has particularly complex structure and its precise segmentation is very useful for detecting tumors, edema, and necrotic tissues, in order to prescribe related therapy. Magnetic resonance imaging (MRI) is an important diagnostic imaging technique for the early detection of abnormal changes in tissues and organs. MRI Imaging forms one of the core methods to identify Brain Tumors, and access the existence, size and volume of the tumor. Clustering is one of the widely used image segmentation techniques which divide patterns in such a way that samples of the same group are more similar to one another than samples belonging to different groups. This paper presents review on some of segmentation methods based on clustering and Region Based with their advantages and disadvantages. Here, also include various measurements like Area, Volume, and Size of tumor