Quantitative comparison of four brain extraction algorithms

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

Research output: Contribution to journalArticlepeer-review

109 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1255-1261
Number of pages7
Issue number3
StatePublished - Jul 1 2004

Bibliographical note

Funding Information:
Supported in part by Human Brain Project grant P20 EB02013.


  • Brain
  • Extraction algorithms
  • McStrip


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