Automated connectivity-based thresholding segmentation of midsagittal brain MR images

In this paper, we propose an algorithm for automated segmentation of midsagittal brain MR images. First, we apply thresholding to obtain binary images. From the binary images, we locate some landmarks. Based on the landmarks and anatomical information, we preprocess the binary images to eliminate small regions and remove the skull, which substantially simplifies the subsequent operations. We perform segmentation in the binary image as much as possible and then return to the gray scale image to solve problematic areas. We propose a new connectivity-based thresholding segmentation to separate brain regions from surrounding tissues. Experiments show promising results.