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Real-time visualization plays an important role in medical imaging applications such as image-guided surgery, surgical simulation and medical education. For the real-time visualization and the simultaneous overlay of 3D triangulated objects onto live recordings of patient data gathered with fast imaging devices (e.g. from the beating heart) it is essential that the number of triangles used for displaying the meshes are reasonably low. For this purpose, we developed a novel, optimized surface reconstruction algorithm for planar cross sections based on the non-constrained 3D Delaunay triangulation using pre-computed contour data. The proposed method generates 50% fewer triangles for the cardiac images used in our application domain in comparison to standard reconstruction methods from planar cross sections. Besides reducing the number of triangles, our method eliminates 'stair-case' artifacts that can occur between consecutive cross sections for non-uniformly sampled input image data often found in biomedical imaging applications.