Cognition-based MRI brain tumor segmentation technique using modified level set method

Gliomas are the most common types of brain tumors seen in adults. Generally, it starts from glioma cells and affects the adjacent tissues. Even though the analysis of glioma has well developed, the identification is still poor. In this paper, we propose an efficient modified level set method for brain tumor segmentation, in which we preprocess the image to remove the noise and then accurately segment the magnetic resonance images (MRI). Therefore, this document anticipated an innovative level set algorithm for segmenting gliomas from the MRI brain images where the segmentation is made automatically by means of selecting the initial contour automatically from the maximum intensity pixel computed from the histogram intensity plots. The proposed methodology is implemented in the working platform of MATLAB to produce 99% accuracy, and the results are analyzed by the existing methods.