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User-Guided Level Set Segmentation of Anatomical Structures with ITK-SNAP

Yushkevich, Paul A., Piven, Joseph, Cody, Heather, Ho, Sean, Gee, James C., Gerig, Guido
University of Pennsylvania
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/20
New: Prefer using the following doi: https://doi.org/10.54294/13sgje
Published in The Insight Journal - 2005 MICCAI Open-Source Workshop.
Submitted by Paul Yushkevich on 2005-07-30T21:22:54Z.

Active contour segmentation and its robust implementation using level sets have been studied thoroughly in the medical image analysis literature. Despite the availability of these powerful methods, clinical research still largely relies on manual slice-by-slice outlining for anatomical structure segmentation. To bridge the gap between methodological advances and clinical routine, we developed ITK-SNAP: an open source application intended to make level set segmentation easily accessible to a wide range of users with various levels of mathematical expertise. We briefly describe this new tool and report the results of a validation study in which ITK-SNAP was compared to manual segmentation of the caudate in the context of an ongoing child neuroimaging autism study.