A Review on State-of-the-Art Techniques for Image Segmentation and Classification for Brain MR Images

Abstract

The diagnosis of tumors in the initial stage plays a crucial role in improving the clinical outcomes of a patient. Evaluation of brain tumors from many MRI images generated regularly in a clinical environment is a complex and time-consuming process. Therefore,there comes a need for an efficient and accurate model for the early detection of tumors. This paper revolves around the current strategies used for brain tumor segmentation and classification from MRI images of the brain. This approach also tries to pave the way for the significance of their performance measure and quantitative evaluation of forefront strategies. This state of the art clearly describes the importance of several brain image segmentation and classification methodsduring the past 13 years of publication by various researchers. In this instance, new calculations are being made for potential clients to analyze the concerned area of research. This review acknowledges the key accomplishments expressed in the diagnostic measures and their success indicators of qualitative and quantitative measurement. This research study also explores the key outcomes and reasons for finding the lessons learned.

Keywords: CT; MRI; brain tumor; classification; image segmentation; segmentation.