The study of white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF) regions in the brain magnetic resonance (MR) images can be useful for determining different brain disorders, assisting brain surgery, post-surgical analysis, saliency detection and for studying regions of interest. In this paper, a novel hybrid region-based multiphase (four-phase) active contours method is proposed to partition a brain MR image into three distinct regions i.e., GM, WM and CSF. The proposed energy functional is formulated by combining local and global fitted images in a multiplicative fashion. Both fitted images are defined by integrating two-phase global and local intensity from Chan-Vese (CV) and local binary fitted (LBF) models, respectively. In this paper, a post processing (pixel correction) method is also devised which improves the accuracy of the segmented WM, GM and CSF regions in a brain MR image. Different thresholds are decided based on averages of all three regions. According to the computed thresholds, a binary value (0 or 1) is then assigned to each pixel. Experimental results using both two-dimensional (2D) and three-dimensional (3D) brain MR images show that the proposed method outperforms the state-of-the-art both qualitatively and quantitatively.