Automated Brain Segmentation Algorithm for 3D Magnetic Resonance Brain Images
Jong Geun Park, Taeuk Jeong, Chulhee Lee · 2007
In this paper, we propose a new brain segmentation method for 3D magnetic resonance (MR) brain images. The proposed method consists of four steps: background rejection, image normalization, initial slice segmentation, and brain segmentation. In the image normalization step, intensity non-uniformity is removed. In the brain segmentation step, we use mathematical morphological operators and masking. The proposed algorithm was tested with twenty 3D MR normal brain image sets. Experiment results showed the proposed algorithm is fast and provides robust and satisfactory results.