1Assistant Professor, Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu
2Professor, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore, Tamil Nadu, India
Online published on 15 March, 2019.
Brain tumors are most aggressive and tends to short life expectancy rate. Automatic segmentation is important for quantitative analysis in MR brain images. Magnetic resonance imaging (MRI) is a common imaging technique to assess these kind of tumors which gives segmentation in a reasonable time and produces large amount of data. This paper presents survey on automatic brain tumor segmentation and discuss validation metrics like dice similarity coefficient, specificity, sensitivity, true positive, true negative and etc,. The main scope of this paper is to compare the different segmentation techniques.
Brain Tumor, MRI, segmentation
