[Insight-users] The Insight Journal-New Submission

[Julien Jomier]

Hello,
A new submission has been added to the Insight Journal.

Title: Automatic Branch Decomposition for Tubular Structures
Author(s):Xiong G., Xing L., Taylor C.
Abstract:
     Branches of tubular structures (vasculature, trachea, neuron, etc.) 
in medical images are critical for the topology of these structures. In 
many applications, It is very helpful to be able to decompose tubular 
structures and identify every individual branch. For example, 
quantification of geometric vascular features, registration of trachea 
movement due to respiration, tracing of neuron path. However, manual 
decomposition can be tedious, time-consuming, and subject to operator 
bias. In this paper, we propose a novel method to decompose tubular 
structures automatically and describe how to implement it in ITK 
framework. The input is a 2D/3D binary image that can be obtained from 
any segmentation techniques, as well as the junctions, which can be 
generated automatically from our previously contributed ITK class: 
itk::JunctionDetectionFilter. The output will be branches with their 
labels and their connection. There are only two parameters which need to 
be set by the user. We
  provide here the implementation as a ITK class: 
itk::BranchDecompositionFilter.

Download and Review the paper at: 
http://www.insight-journal.org/browse/publication/641

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