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Level Set Segmentation: Active Contours without edge

mosaliganti, kishore , smith, benjamin, gelas, arnaud, gouaillard, alexandre, megason, sean
Singapore Agency for Science Technology and Research
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1532
New: Prefer using the following doi: https://doi.org/10.54294/8jk6oy
Submitted by Alexandre Gouaillard on 2009-03-13 14:36:05.

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.