Automatic brain tumor segmentation in MRI: Hybridized multilevel thresholding and level set

Segmentation of tumor from magnetic resonance image (MRI) brain images is an emergent research area in the field of medical image segmentation. As segmentation of brain tumor plays an important role for necessary treatment and planning of tumor surgery. However, segmentation of the brain tumor is still a great challenge in clinics, specially automatic segmentation. In this paper we proposed hybridized multilevel thresholding and level set method for automatic segmentation of brain tumor. The innovation for this paper is to interface the initial segmentation from multilevel thresholding and extract a fine portrait using level set method with morphological operations. The results are compared with the existing method and also with radiologist manual segmentation which confirm the effectiveness of this hybridized paradigm for brain tumor segmentation.