title: Quantitative comparison of four brain extraction algorithms.
abstract: In a companion paper (Rehm et al., 2004), we introduced Minneapolis Consensus Strip (McStrip), a hybrid algorithm for brain/non-brain segmentation. In this paper, we compare the performance of McStrip and three brain extraction algorithms (BEAs) in widespread use within the neuroimaging community--Statistical Parametric Mapping v.2 (SPM2), Brain Extraction Tool (BET), and Brain Surface Extractor (BSE)--to the "gold standard" of manually stripped T1-weighted MRI brain volumes. Our comparison was based on quantitative boundary and volume metrics, reproducibility across repeat scans of a single subject, and assessments of performance consistency across datasets acquired on different scanners at different institutions. McStrip, a hybrid method incorporating warping to a template, intensity thresholding, and edge detection, consistently outperformed SPM2, BET, and BSE, all of which rely on a single algorithmic strategy.
authors.affiliation: Department of Neurology, University of Minnesota, Minneapolis, MN 55417, USA. kristi@neurovia.umn.edu
authors.forename: Kristi
authors.initials: K
authors.lastname: Boesen
authors.forename: Kelly
authors.initials: K
authors.lastname: Rehm
authors.forename: Kirt
authors.initials: K
authors.lastname: Schaper
authors.forename: Sarah
authors.initials: S
authors.lastname: Stoltzner
authors.forename: Roger
authors.initials: R
authors.lastname: Woods
authors.forename: Eileen
authors.initials: E
authors.lastname: Lüders
authors.forename: David
authors.initials: D
authors.lastname: Rottenberg
mesh_terms: D000465:Algorithms; D001921:Brain; D001931:Brain Mapping; D003627:Data Interpretation, Statistical; D003952:Diagnostic Imaging; D006801:Humans