Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
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ACM Transactions on Graphics (TOG)
ACM Transactions on Graphics (TOG)
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Handbook of mathematics (3rd ed.)
Handbook of mathematics (3rd ed.)
Computational geometry in C (2nd ed.)
Computational geometry in C (2nd ed.)
International Journal of Computer Vision
Modelling with implicit surfaces that interpolate
ACM Transactions on Graphics (TOG)
Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
Curvature-Dependent Triangulation of Implicit Surfaces
IEEE Computer Graphics and Applications
Constrained Elastic Surface Nets: Generating Smooth Surfaces from Binary Segmented Data
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Curve and surface smoothing without shrinkage
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Harmonic Embeddings for Linear Shape Analysis
Journal of Mathematical Imaging and Vision
LV shape and motion: B-spline-based deformable model and sequential motion decomposition
IEEE Transactions on Information Technology in Biomedicine
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This paper presents a novel method for the generation of myocardial wall surface meshes from segmented 3D MR images, which typically have strongly anisotropic voxels. The method maps a premeshed sphere to the surface of the segmented object. The mapping is defined by the gradient field of the solution of the Laplace equation between the sphere and the surface of the object. The same algorithm is independently used to generate the surface meshes of the epicardium and endocardium of the four cardiac chambers. The generated meshes are smooth despite the strong voxel anisotropy, which is not the case for the marching cubes and related methods. While the proposed method generates more regular mesh triangles than the marching cubes and allows for a complete control of the number of triangles, the generated meshes are still close to the ones obtained by the marching cubes. The method was tested on 3D short-axis cardiac MR images with strongly anisotropic voxels in the long-axis direction. For the five tested subjects, the average in-slice distance between the meshes generated by the proposed method and by the marching cubes was 0.4 mm.