SpUDD defines superpower contours from power diagrams of unsigned distance samples, proves convergence to the true surface, and uses them to generate approximating polygonal meshes that outperform prior strategies.
IEEE transactions on visualization and computer graphics , volume=
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End-to-end framework reconstructs 4D whole-heart meshes from cine MRI using differentiable contour rendering and multi-scale temporal modeling, reporting 1.68 mm MAE and improved motion smoothness over prior methods.
A single-objective rectified flow variant uses neural ODEs trained by regression to monotonically decrease a fixed convex transport cost while preserving marginal distributions.
citing papers explorer
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SpUDD: Superpower Contouring of Unsigned Distance Data
SpUDD defines superpower contours from power diagrams of unsigned distance samples, proves convergence to the true surface, and uses them to generate approximating polygonal meshes that outperform prior strategies.
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Personalized 4D Whole-Heart Mesh Reconstruction from Cine MRI via Multi-Scale Temporal Modeling and Differentiable Contour Rendering
End-to-end framework reconstructs 4D whole-heart meshes from cine MRI using differentiable contour rendering and multi-scale temporal modeling, reporting 1.68 mm MAE and improved motion smoothness over prior methods.
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Rectified Flow: A Marginal Preserving Approach to Optimal Transport
A single-objective rectified flow variant uses neural ODEs trained by regression to monotonically decrease a fixed convex transport cost while preserving marginal distributions.