Title:	AUTOMATIC MEDICAL IMAGE SEGMENTATION BASED ON VFC-SNAKE
Author(s):	Houda Bakir, Maher Charfi
ISBN:	978-972-8939-22-9
Editors:	Yingcai Xiao, Tomaz Amon and Piet Kommers
Year:	2010
Edition:	Single
Keywords:	Automatic image segmentation, VFC-Snake, contour initialization, contour splitting
Type:	Short Paper
First Page:	362
Last Page:	366
Language:	English
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Paper Abstract:	An automatic approach to contour segmentation of Computed Tomography (CT) images is presented in this work. Image segmentation is achieved by means of the snake algorithm and the dynamic programming (DP) optimization technique. Based upon the Vector field convolution (VFC), a new strategy for contour points initialization and splitting is presented. Contour initialization is carried out from VFC magnitude thresholding. In the multi-object image segmentation, the delineation of all the image objects is done through the splitting of the contour at the divergent points (DP) in the image. The proposed technique can attain a good solution without the need of an operator intervention. Some experiences on synthetic and CT medical images show the advantages of the proposed algorithm in comparing with two state-of-the art automatic initialization methods.
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