Template-Cut: A Pattern-Based Segmentation Paradigm

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Template-Cut: A Pattern-Based Segmentation Paradigm

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Title: Template-Cut: A Pattern-Based Segmentation Paradigm
Author: Freisleben, Bernd; Nimsky, Christopher; Egger, Jan; Kapur, Tina

Note: Order does not necessarily reflect citation order of authors.

Citation: Egger, Jan, Bernd Freisleben, Christopher Nimsky, and Tina Kapur. 2012. Template-cut: A pattern-based segmentation paradigm. Scientific Reports 2:420.
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Abstract: We present a scale-invariant, template-based segmentation paradigm that sets up a graph and performs a graph cut to separate an object from the background. Typically graph-based schemes distribute the nodes of the graph uniformly and equidistantly on the image, and use a regularizer to bias the cut towards a particular shape. The strategy of uniform and equidistant nodes does not allow the cut to prefer more complex structures, especially when areas of the object are indistinguishable from the background. We propose a solution by introducing the concept of a “template shape” of the target object in which the nodes are sampled non-uniformly and non-equidistantly on the image. We evaluate it on 2D-images where the object's textures and backgrounds are similar, and large areas of the object have the same gray level appearance as the background. We also evaluate it in 3D on 60 brain tumor datasets for neurosurgical planning purposes.
Published Version: doi:10.1038/srep00420
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3359527/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10385396
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