FPicker is a topology‑guided framework for filament tracing in low‑signal Cryo‑EM images. It combines a center‑endpoint representation with an open‑curve evolution module to model non‑cyclic connectivity, overcoming limitations of pixel‑wise segmenters, box‑based detectors, sequential trackers, and traditional active contours. On simulated benchmarks, FPicker improves mean spatio‑angular precision by over 40 % and reduces topological gap rates by more than 60 % under extreme noise, and it achieves state‑of‑the‑art performance on real EMPIAR data after fine‑tuning.
TopoFuse introduces a topology-aware tri-planar fusion method for 3D cryo-electron tomography segmentation. It replaces traditional loss penalties with a differentiable projection operator that identifies and sparsely edits critical voxels to enforce specified topological constraints. The approach achieves a 54% reduction in Betti number error, a 4.6-point Dice improvement, and edits only 3.1% of voxels across three benchmarks.
By Rohit Kumar Salla, Neelesh Gupta, Xingjian Li, Min Xu
arXiv:2607. 05815v1 Announce Type: new Abstract: The Minkowski functionals of a field's excursion sets -- area, boundary measure, and Euler characteristic -- describe its level-set morphology; the Euler characteristic is the cheapest handle on topology.
By Gunner Levi Howe
The paper introduces Structural Dual Super‑Resolution (SDN), a novel approach that shifts from pixel‑level super‑resolution to topological inference for trabecular bone morphology. By training on 2‑D slices and evaluating on 3‑D morphological metrics, SDN learns to predict invariant microstructures from low‑resolution CT inputs, using bidirectional modeling, a multi‑scale consistency discriminator, and four structural duality constraints. The method achieves SSIM of 0.8 and morphological parameters closely matching synchrotron micro‑CT across six metrics, demonstrating cross‑source generalization and trustworthy inference rather than mere pixel generation.
By Fan Zhang, Yi Zhang, Ling Wang
arXiv:2606. 10255v1 Announce Type: cross Abstract: Cryo-electron tomography (cryoET) has emerged as a powerful tool in structural and cellular biology by enabling direct visualization of macromolecular structures within intact cells, thereby linking molecular architecture to cellular organization in a native context.
By Jonathan Schwartz, Utz Heinrich Ermel, C. Braxton Owens, Zhuowen Zhao, Ariana Peck, Gus L. W. Hart, Grant J. Jensen, Bridget Carragher, Dari Kimanius
arXiv:2607. 02561v1 Announce Type: cross Abstract: Consumer depth sensors such as the LiDAR scanner on recent iPhones provide metric range, but their useful range is short and their returns are sparse.
By Jinwen Wen