TY - GEN
T1 - Automated brain segmentation algorithm for 3D magnetic resonance brain images
AU - Park, Jong Geun
AU - Jeong, Taeuk
AU - Lee, Chulhee
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=47949116255&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47949116255&partnerID=8YFLogxK
U2 - 10.1109/SOFA.2007.4318305
DO - 10.1109/SOFA.2007.4318305
M3 - Conference contribution
AN - SCOPUS:47949116255
SN - 9781424416080
T3 - SOFA 2007 - 2nd IEEE International Workshop on Soft Computing Applications Proceedings
SP - 57
EP - 61
BT - 2nd IEEE International Workshop on Soft Computing Applications Proceedings, SOFA 2007
T2 - 2nd IEEE International Workshop on Soft Computing Applications, SOFA 2007
Y2 - 21 August 2007 through 23 August 2007
ER -