Dual-t-snakes model for medical imaging segmentation

Authors:
G. Giraldi;E. Strauss;A. Oliveira
Affiliations:
National Laboratory for Scientific Computing, Av. Getulio Vargas, 333, 25651-071, Petropolis, Rio de Janeiro, Brazil;Federal University of Rio de Janeiro, Department of Electronics Engineering--DELIEE, Rio de Janeiro, RJ, Brazil;Federal University of Rio de Janeiro, Computer Graphics Laboratory, Mail Box 68511, 21945-970 Rio de Janeiro, RJ, Brazil
Venue:
Pattern Recognition Letters - Special issue: Sibgrapi 2001
Year:
2003

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Abstract

The Dual-T-Snakes model plus dynamic programming (DP) techniques is a powerful methodology for boundary extraction and segmentation of 2D images. However, the original Dual-T-Snakes is not efficient for noisy images due to nonconvexity problems. In this paper we improve the model through multigrid and region growing methods to get more robustness against local minima. Besides, we demonstrate the advantage of using pass-band filtering methods and a fuzzy segmentation technique plus Dual-T-Snakes. We test these methods for artificial and cell images.