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2007
Springer

A Shape-Guided Deformable Model with Evolutionary Algorithm Initialization for 3D Soft Tissue Segmentation

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A Shape-Guided Deformable Model with Evolutionary Algorithm Initialization for 3D Soft Tissue Segmentation
Abstract. We present a novel method for the segmentation of volumetric images, which is especially suitable for highly variable soft tissue structures. Core of the algorithm is a statistical shape model (SSM) of the structure of interest. A global search with an evolutionary algorithm is employed to detect suitable initial parameters for the model, which are subsequently optimized by a local search similar to the Active Shape mechanism. After that, a deformable mesh with the same topology as the SSM is used for the final segmentation: While external forces strive to maximize the posterior probability of the mesh given the local appearance around the boundary, internal forces governed by tension and rigidity terms keep the shape similar to the underlying SSM. To prevent outliers and increase robustness, we determine the applied external forces by an algorithm for optimal surface detection with smoothness constraints. The approach is evaluated on 54 CT images of the liver and
Hans-Peter Meinzer, Ivo Wolf, Sascha Münzing,
Added 16 Nov 2009
Updated 16 Nov 2009
Type Conference
Year 2007
Where IPMI
Authors Hans-Peter Meinzer, Ivo Wolf, Sascha Münzing, Tobias Heimann
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