DocumentCode :
1364534
Title :
Fully automatic segmentation of the brain in MRI
Author :
Atkins, M. Stella ; Mackiewich, Blair T.
Author_Institution :
Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
Volume :
17
Issue :
1
fYear :
1998
Firstpage :
98
Lastpage :
107
Abstract :
A robust fully automatic method for segmenting the brain from head magnetic resonance (MR) images has been developed, which works even in the presence of radio frequency (RF) inhomogeneities. It has been successful in segmenting the brain in every slice from head images acquired from several different MRI scanners, using different-resolution images and different echo sequences. The method uses an integrated approach which employs image processing techniques based on anisotropic filters and "snakes" contouring techniques, and a priori knowledge, which is used to remove the eyes, which are tricky to remove based on image intensity alone. It is a multistage process, involving first removal of the background noise leaving a head mask, then finding a rough outline of the brain, then refinement of the rough brain outline to a final mask. The paper describes the main features of the method, and gives results for some brain studies.
Keywords :
biomedical NMR; brain; image segmentation; medical image processing; a priori knowledge; anisotropic filters; background noise removal; brain MRI; contouring techniques; different-resolution images; echo sequences; fully automatic segmentation; head magnetic resonance images; head mask; image intensity alone; multistage process; radiofrequency inhomogeneities; rough brain outline; Anisotropic filters; Background noise; Eyes; Image processing; Image segmentation; Magnetic heads; Magnetic resonance; Magnetic resonance imaging; Radio frequency; Robustness; Brain; Humans; Magnetic Resonance Imaging;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/42.668699
Filename :
668699
Link To Document :
بازگشت