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Cited by 166

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Online resource for validation of brain segmentation methods

Open access
Shattuck, David W., Prasad, Gautam, Mirza, Mubeena, Narr, Katherine L., Toga, Arthur W.·2009·NeuroImage
DOI 10.1016/j.neuroimage.2008.10.066
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Abstract

One key issue that must be addressed during the development of image segmentation algorithms is the accuracy of the results they produce. Algorithm developers require this so they can see where methods need to be improved and see how new developments compare with existing ones. Users of algorithms also need to understand the characteristics of algorithms when they select and apply them to their neuroimaging analysis applications. Many metrics have been proposed to characterize error and success rates in segmentation, and several datasets have also been made public for evaluation. Still, the methodologies used in analyzing and reporting these results vary from study to study, so even when studies use the same metrics their numerical results may not necessarily be directly comparable. To address this problem, we developed a web-based resource for evaluating the performance of skull-stripping in T1-weighted MRI. The resource provides both the data to be segmented and an online application that performs a validation study on the data. Users may download the test dataset, segment it using whichever method they wish to assess, and upload their segmentation results to the server. The server computes a series of metrics, displays a detailed report of the validation results, and archives these for future browsing and analysis. We applied this framework to the evaluation of 3 popular skull-stripping algorithms – the Brain Extraction Tool (Smith, 2002), the Hybrid Watershed Algorithm (Ségonne et al., 2004), and the Brain Surface Extractor (Shattuck et al., 2001) under several different program settings. Our results show that with proper parameter selection, all 3 algorithms can achieve satisfactory skull-stripping on the test data.

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Research works printed but not linked: 31

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Metadata

Authors
Shattuck, D. W., Prasad, G., Mirza, M., Narr, K. L., & Toga, A. W.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2009-04
Volume
45
Issue
2
Pages
431-439
ISSN
1053-8119 (ISSN-L)
DOI
10.1016/j.neuroimage.2008.10.066
OpenAlex
W2169952919
Cited by
166
References
2
FWCI
14.80
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Online resource for validation of brain segmentation methods. https://app.cochat.ai/papers/10.1016/j.neuroimage.2008.10.066
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Shattuck, D. W., Prasad, G., Mirza, M., Narr, K. L., & Toga, A. W. (2009). Online resource for validation of brain segmentation methods. NeuroImage. https://doi.org/10.1016/j.neuroimage.2008.10.066

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