Mean Field Annealing Deformable Contour Method: A Constrained Global Optimization Approach

摘要

This paper presents an efficient global optimization approach to the problem of constrained contour energy minimization for the object boundary extraction. In the method, with a given contour energy function, different target boundaries can be modeled as constrained global optimal solutions under different constraints expressed as a set of parameters characterizing the target contour interior structure. To search for the constrained global optimal solution, a fast and efficient global approach based on mean field annealing (MFA) is employed to avoid local minima. An illustrative example of three target boundaries in a synthetic image modeled as constrained global energy minimum contours with different constraint parameters is successfully located using the derived algorithm. A conventional variational based deformable contour method (Wang et al., 2002) with the same energy function and constraint fails to achieve the same task. Experimental evaluations and comparisons with other methods on ultrasound pig heart, MRI knee, and CT kidney images where gaps, blur contour segments having complex shape and inhomogeneous interiors have been conducted with most favorable results