Level Set Segmentation: Active Contours without edge
Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
systems biology, harvard Medical School
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1532
An Insight Toolkit (ITK) processing framework for segmentation using active contours without edges
is presented in this paper. Our algorithm is based on the work of Chan and Vese [1] that uses level-
sets to accomplish region segmentation in images with poor or no gradient information. The basic idea
is to partion the image into two piecewise constant intensity regions. This work is in contrast to the
level-set methods currently available in ITK which necessarily require gradient information. Similar to
those methods, the methods presented in this paper are also made efficient using a sparse implementation
strategy that solves the contour evolution PDE at the level-set boundary. The framework consists of 6
new ITK filters that inherit in succession from itk::SegmentationFilter. We include 2D/3D example
code, parameter settings and show the results generated on a 2D cardiac image.
Code
plus Automatic Testing Results by Insight-Journal Dashboard on Wed Apr 29 09:30:38 2009 for revision #2
starstarstarstarstar expertise: 5 sensitivity: 5

Reviews
minus Review of Level Set Segmentation: Active Contours without edge by Navneeth Subramanian on 2009-05-11 04:47:20 for revision #3
starstarstarstarstar expertise: 4 sensitivity: 5
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Summary:

The authors have developed an ITK based implementation of the 'Active Contours without edges' formulation of level set segmentation.

Open Science:

Source code and demonstration data are included.

Reproducibility:

Compiled from source and tested with the 2D datasets provided by authors. Compiles with minor modifications to the CMakeLists.txt file.

Use of Open Source Software:

Software uses only open source toolkits.

Open source Contributions:

Full source provided.

Free comment :

Level sets using region-based criteria such as this submission are far more managable than the edge based criteria present in ITK today. This is very useful contribution to the ITK community.

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Information
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Paper Id: 322
Categories: Level sets, Region growing
Keywords: level set, chan and vese,
Toolkit: ITK (moved into the sandbox)
Revision: 3 (05-08-2009)
Status: Open for public review
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Data
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Full download: .zip
Paper: view, .pdf
Source code : Download

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