title: Fully automatic segmentation of the brain in MRI.
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.
authors.affiliation: School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. stella@cs.sfu.ca
authors.forename: M S
authors.initials: MS
authors.lastname: Atkins
authors.forename: B T
authors.initials: BT
authors.lastname: Mackiewich
mesh_terms: D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*