Brain extraction using the watershed transform from markers

Beare, Richard, Chen, Jian, Adamson, Christopher L., Silk, Timothy, Thompson, Deanne K., Yang, Joseph Y. M., Anderson, Vicki A., Seal, Marc L. and Wood, Amanda G. 2013, Brain extraction using the watershed transform from markers, Frontiers in neuroinformatics, vol. 7, pp. 1-15, doi: 10.3389/fninf.2013.00032.

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Title Brain extraction using the watershed transform from markers
Author(s) Beare, Richard
Chen, Jian
Adamson, Christopher L.
Silk, TimothyORCID iD for Silk, Timothy
Thompson, Deanne K.
Yang, Joseph Y. M.
Anderson, Vicki A.
Seal, Marc L.
Wood, Amanda G.
Journal name Frontiers in neuroinformatics
Volume number 7
Article ID 32
Start page 1
End page 15
Total pages 15
Publisher Frontiers
Place of publication Lausanne, Switzerland
Publication date 2013
ISSN 1662-5196
Keyword(s) Insight Toolkit
brain extraction
human brain extraction
macaque brain extraction
mathematical morphology
watershed transform from markers
Science & Technology
Life Sciences & Biomedicine
Mathematical & Computational Biology
Neurosciences & Neurology
Summary Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important step in many types of neuro-imaging research using both humans and animal subjects. The importance of brain extraction is well appreciated-numerous approaches have been published and the benefits of good extraction methods to subsequent processing are well known. We describe a tool-the marker based watershed scalper (MBWSS)-for isolating the brain in T1-weighted MR images built using filtering and segmentation components from the Insight Toolkit (ITK) framework. The key elements of MBWSS-the watershed transform from markers and aggressive filtering with large kernels-are techniques that have rarely been used in neuroimaging segmentation applications. MBWSS is able to reliably isolate the brain without expensive preprocessing steps, such as registration to an atlas, and is therefore useful as the first stage of processing pipelines. It is an informative example of the level of accuracy achievable without using priors in the form of atlases, shape models or libraries of examples. We validate the MBWSS using a publicly available dataset, a paediatric cohort, an adolescent cohort, intra-surgical scans and demonstrate flexibility of the approach by modifying the method to extract macaque brains.
Language eng
DOI 10.3389/fninf.2013.00032
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2013, Beare, Chen, Adamson, Silk, Thompson, Yang, Anderson, Seal and Wood.
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Document type: Journal Article
Collections: Faculty of Health
School of Psychology
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