Article

Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig GUser-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31:1116-1128

Department of Computer Science, University of North Carolina at Chapel Hill, North Carolina, United States
NeuroImage (Impact Factor: 6.36). 08/2006; 31(3):1116-28. DOI: 10.1016/j.neuroimage.2006.01.015
Source: PubMed

ABSTRACT

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.

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    • "Pixel size of these images ranged from 0.10 to 0.21 mm, slice thickness was 0.5 mm for all individuals, and slice interval ranged from 0.20 to 0.50 mm. Virtual endocasts were reconstructed from these CT images using a threshold-based 2D segmentation procedure in ITK-SNAP 3.0 (Yushkevich et al., 2006; Aristide et al., 2015). A threshold gray value was defined to separate bone from empty spaces. "
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    • "InsightToolkit (ITK, RRID:nif-0000-00319, Schroeder 2005, http://www.itk.org/) compiled with Python wrappings (WrapITK, Lehmann et al. 2006), Convert3d (Yushkevich et al. 2006b, http://www.itksnap.org/, RRID:nif-0000-00317) and ImageMagick (http://www.imagemagick.org/) "
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    • "Manual segmentation was performed using ITK-SNAP software (v.2.4.0, http://www.itksnap.org, last accessed November 27, 2015; Yushkevich et al. 2006) and was doublechecked by 2 different investigators. "
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