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<p>We propose an optimization approach to the estimation of a simple closed curve describing the boundary of an object represented in an image. The problem arises in a variety of applications, such as template matching schemes for medical image registration. A regularized optimization formulation with an objective function that measures the normalized image contrast between the inside and outside of a boundary is proposed. Numerical methods are developed to implement the approach, and a set of simulation studies are carried out to quantify statistical performance characteristics. One set of simulations models emission computed tomography (ECT) images; a second set considers images with a locally coherent noise pattern. In both cases, the error characteristics are found to be quite encouraging. The approach is highly automated, which offers some practical advantages over currently used technologies in the medical imaging field.</p>
edge detection; computerised tomography; optimisation; statistical analysis; regularized contrast statistic; object boundary estimation; statistical evaluation; optimization; closed curve; medical imaging; objective function; normalized image contrast; numerical methods; emission computed tomography; coherent noise pattern; error characteristics

F. O'Sullivan and M. Qian, "A Regularized Contrast Statistic for Object Boundary Estimation-Implementation and Statistical Evaluation," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 16, no. , pp. 561-570, 1994.
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