Putting our heads together: A consensus approach to brain/non-brain segmentation in T1-weighted MR volumes

Kelly Rehm; Kirt Schaper; Jon Anderson; Roger Woods; Sarah Stoltzner; David Rottenberg

doi:10.1016/j.neuroimage.2004.03.011

Putting our heads together: A consensus approach to brain/non-brain segmentation in T1-weighted MR volumes

Kelly Rehm, Kirt Schaper, Jon Anderson, Roger Woods, Sarah Stoltzner, David Rottenberg

University of Minnesota Twin Cities

Research output: Contribution to journal › Article › peer-review

58 Scopus citations

Abstract

We describe an approach to brain extraction from T1-weighted MR volumes that uses a hierarchy of masks created by different models to form a consensus mask. The algorithm (McStrip) incorporates atlas-based extraction via nonlinear warping, intensity-threshold masking with connectivity constraints, and edge-based masking with morphological operations. Volume and boundary metrics were computed to evaluate the reproducibility and accuracy of McStrip against manual brain extraction on 38 scans from normal and ataxic subjects. McStrip masks were reproducible across six repeat scans of a normal subject and were significantly more accurate than the masks produced by any of the individual algorithmic components.

Original language	English (US)
Pages (from-to)	1262-1270
Number of pages	9
Journal	NeuroImage
Volume	22
Issue number	3
DOIs	https://doi.org/10.1016/j.neuroimage.2004.03.011
State	Published - Jul 1 2004

Keywords

Algorithm
Brain
MR volume

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Putting our heads together: A consensus approach to brain/non-brain segmentation in T1-weighted MR volumes

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Keywords

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