The disordered sponge morphology is a topologically distinct disordered variant of the single-gyroid network, featuring mostly trivalent nodes and non-intercatenated loops unlike the intercatenated double-gyroid.
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2026 4representative citing papers
Vesselpose predicts voxel-wise direction vectors to extend the TEASAR algorithm for topologically accurate vascular graph reconstruction from 3D images.
A new sub-Riemannian snake model on the projective line bundle uses a symmetric cusp-free pseudo-distance with triangle inequality properties and connected-component costs to enable efficient robust segmentation of overlapping objects in SEM images.
3D CNNs predict elastic moduli of nanoporous metals with R²=0.955, outperforming descriptor-based models, and transfer learning works on smaller denser datasets for large-scale Pareto optimization.
citing papers explorer
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Topological and morphological signatures of disorder in a self-assembled, soft matter sponge network
The disordered sponge morphology is a topologically distinct disordered variant of the single-gyroid network, featuring mostly trivalent nodes and non-intercatenated loops unlike the intercatenated double-gyroid.
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Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images
Vesselpose predicts voxel-wise direction vectors to extend the TEASAR algorithm for topologically accurate vascular graph reconstruction from 3D images.
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Sub-Riemannian Snakes on the Projective Line Bundle with Applications to Segmentation of SEM Images
A new sub-Riemannian snake model on the projective line bundle uses a symmetric cusp-free pseudo-distance with triangle inequality properties and connected-component costs to enable efficient robust segmentation of overlapping objects in SEM images.
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Transferable 3D Convolutional Neural Networks for Elastic Constants Prediction in Nanoporous Metals
3D CNNs predict elastic moduli of nanoporous metals with R²=0.955, outperforming descriptor-based models, and transfer learning works on smaller denser datasets for large-scale Pareto optimization.