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Quantitative comparison of four brain extraction algorithms.

Kristi Boesen·Kelly Rehm·Kirt Schaper·Sarah Stoltzner·Roger Woods·Eileen Lüders·David Rottenberg
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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.

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AlgorithmsBrainBrain MappingData Interpretation, StatisticalDiagnostic ImagingHumansJournal ArticleResearch Support, U.S. Gov't, P.H.S.

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Kristi Boesen, Kelly Rehm, Kirt Schaper, Sarah Stoltzner, Roger Woods, Eileen Lüders, David Rottenberg. 2004. Quantitative comparison of four brain extraction algorithms.. https://doi.org/10.1016/j.neuroimage.2004.03.010

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