User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability

http://www.sciencedirect.com/science/article/pii/S1053811906000632
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Links to Media http://www.sciencedirect.com/science/article/pii/S1053811906000632
Publication Type journal article
Creator Gerig, Guido
Other Author Yushkevich, Paul A.; Piven, Joseph; Hazlett, Heather Cody; Smith, Rachel Gimpel; Ho, Sean; Gee, James C.
Title User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability
Date 2006-01-01
Description Active contour segmentation and its robust implementation using level set methods are well-established theoretical approaches that have been studied thoroughly in the image analysis literature. Despite the existence of these powerful segmentation methods, the needs of clinical research continue to be fulfilled, to a large extent, using slice-by-slice manual tracing. To bridge the gap between methodological advances and clinical routine, we developed an open source application called ITK-SNAP, which is intended to make level set segmentation easily accessible to a wide range of users, including those with little or no mathematical expertise. This paper describes the methods and software engineering philosophy behind this new tool and provides the results of validation experiments performed in the context of an ongoing child autism neuroimaging study. The validation establishes SNAP intrarater and interrater reliability and overlap error statistics for the caudate nucleus and finds that SNAP is a highly reliable and efficient alternative to manual tracing. Analogous results for lateral ventricle segmentation are provided.
Type InteractiveResource
Publisher Elsevier
Journal Title NeuroImage
Volume 31
Issue 3
First Page 1116
Last Page 1128
DOI 10.1016/j.neuroimage.2006.01.015
Subject Computational anatomy; Image segmentation; Caudate nucleus; 3D active contour models; Open source software; Validation; Anatomical objects
Language eng
Bibliographic Citation Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006). User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage, 31(3), 1116-28.
Rights Management (c) Elsevier ; Authors manuscript from Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006). User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage, 31(3),1116-28. http://dx.doi.org/10.1016/j.neuroimage.2006.01.015.
Format Medium application/html
Identifier uspace, 19290
ARK ark:/87278/s6m93js8
Setname ir_uspace
Date Created 2015-04-01
Date Modified 2015-04-02
ID 712900
Reference URL https://collections.lib.utah.edu/ark:/87278/s6m93js8
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