title: Fast robust automated brain extraction.
abstract: An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods.
authors.affiliation: Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Department of Clinical Neurology, Oxford University, John Radcliffe Hospital, Headington, Oxford, United Kingdom. steve@fmrib.ox.ac.uk
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Smith
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*