A Hybrid Technique for the Automated Segmentation of Corpus Callosum in Midsagittal Brain Mri

摘要

The corpus callosum (CC) is the largest white-matter structure in human brain. In this paper, we take two techniques to observe the results of segmentation of Corpus Callosum. The first one is mean shift algorithm and morphological operation. The second one is k-means clustering. In this paper, it is performed in three steps. The first step is finding the corpus callosum area using adaptive mean shift algorithm or k-means clustering . In second step, the boundary of detected CC area is then used as the initial contour in the Geometric Active Contour (GAC) mode and final step to remove unknown noise using morphological operation and evolved to get the final segmentation result. The experimental results demonstrate that the mean shift algorithm and k-means clustering has provided a reliable segmentation performance.