Work

Level Set Segmentation: Active Contours without edge

Year: 2009

Type: article

Abstract: 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.

Source: The Insight Journal

DOI: 10.54294/8jk6oy

Authors: Kishore Mosaliganti, Benjamin Smith, Arnaud Gelas, Alexandre Gouaillard, sean megason

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4206616384

FWCI: 0.368

Cites: 1

Cited by: 2

Related to: 10