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Medical image segmentation via min s-t cuts with sides constraints

11 years 8 months ago
Medical image segmentation via min s-t cuts with sides constraints
Graph cut algorithms (i.e., min s-t cuts) [3][10][15] are useful in many computer vision applications. In this paper we develop a formulation that allows the addition of side constraints to the min s-t cuts algorithm in order to improve its performance. We apply this formulation to foreground/background segmentation and provide empirical evidence to support its usefulness. From our experiments on medical image segmentation, the graph cut with constraints achieve significantly better performance than that without any constraint. Although the constrained min s-t cut problem is generally NPhard, our approximation algorithm that uses linear programming relaxation and a simple rounding technique as a heuristic produces good results in a few seconds with our unoptimized code.
Jiun-Hung Chen, Linda G. Shapiro
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICPR
Authors Jiun-Hung Chen, Linda G. Shapiro
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