Skip to content
Log in
Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Rapid robust high-fidelity 3D neuronal extraction from multiview calcium imaging datasets.

Yu-Jia Chen Guo-Xun Zhang Ming-Rui Wang Yuan-Long Zhang Jing-Yu Xie Zhi-Feng Zhao Ru-Qi Huang Jia-Min Wu Qiong-Hai Dai
Sep 2026 · Nature Methods · 0 citations · 35 references
Medicine

TL;DR

DeepWonder3D outperforms state-of-the-art methods in 3D localization accuracy with a tenfold reduction in computational costs, validated by numerical simulations and a hybrid two-photon/light-field imaging system.

DOI PubMed Semantic Scholar
View source

Similar papers

2026

A Computational Protocol for Whole Brain Histology Imaging.

A robust, end-to-end pipeline designed to manage and analyze these large-scale volumes efficiently, using a chunk-based data structure (OME-Zarr) to drastically lower hardware memory requirements, enabling the processing of terabyte-scale data on standard workstations.

Chao-Ying Huang, Li-An Chu · 0 citations
Open access Aug 2026

LFCD-Net: physics-inspired 3D reconstruction architecture for miniature light-field microscopy

A physics inspired light-field characteristic driven 3D reconstruction network integrating three core innovations: spatial-angular feature blocks for aliasing suppression, multi-scale feature blocks for structural fidelity, and a physics-inspired adaptive weighting loss to ensure high-quality reconstruction of sparse b...

Jing-Fei Hou, Yue Xing, Chu-Qi Yuan et al. · 0 citations
Conference Sep 2026

Self-supervised denoising of light field microscopy for high-dimensional neural imaging

Photon noise arising during image acquisition remains a major obstacle to resolving fine structures in optical microscopy, particularly under low-light conditions. Due to the inherent difficulty to obtain noise-free ground truth data, selfsupervised denoising approaches have been widely adopted for microscopy imaging....

Wentao Chen, Zhi Lu · 0 citations
Preprint Sep 2026

SkNeXt enables topology-guided neuronal reconstruction from petabyte-scale microscopy data

Recent advances in high-resolution fluorescence and electron microscopy have enabled nanoscale imaging across increasingly large brain volumes, but the resulting terabyte- to petabyte-scale datasets make complete neuronal reconstruction prohibitively expensive in computation, data movement, and manual proofreading. Her...

Jia-Yi Ding, Hu Zhao · 0 citations
#graph neural networks Open access Sep 2026

DeepMoCo: graph neural network-based adaptive correction for motion artifacts in fluorescence microscopy

DeepMoCo is proposed, an innovative deep learning-based framework that integrates a graph neural network (GNN) to establish spatiotemporal feature correlations between biological motion patterns and imaging artifacts and presents a robust and universal solution for high-precision in vivo fluorescence imaging studies.

Shuyue Wang, Rui-Wen Wang, Ge-Lang Hu et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.