Perceptive Proposition of Combined Boosted Algorithm for Brain Tumor Segmentation

Abstract

In recent days, brain tumor detection through Magnetic Resonance Imaging (MRI) is becoming broad and current interest because it is a very challenging task even, in today's modern medical image processing research. Earlier, many researchers used a variety of algorithms to segment the tumor from MRI images. However, this research paper outlines a hybrid approach detecting brain tumor through MRI image segmentation for better accuracy than earlier techniques, where both region-based and supervised classifiers-based techniques are combined together. The problem of over-segmentation has been minimized. The combined feature extraction technique has also added a new concept in our system. In addition, the paper concludes with the status checking of the tumor & provides a necessary diagnosis of brain tumor. Lastly, we compare our proposed model with other techniques and get a far better result.