6 papers
NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation
Haiyang Yan, Jinyue Guo, Yanchao Zhang +6
Accurate 3D neuron segmentation in fluorescence microscopy is critical for neuroscience. However, the sparse and elongated morphology of neurons poses significant challenges to exi…
Probe-EM: Targeted Neuron Tracing via Training-Free Semantic Verification
Liuyun Jiang, Yanchao Zhang, Jinyue Guo +5
Establishing large-scale, high-resolution neural connectivity maps is fundamental to elucidating the structural basis of brain function. However, when processing terabyte- or petab…
SkelEM: Training-Signal Decoupling of Skeleton and Diffusion for Self-supervised Axial Super-Resolution in Volume Microscopy
Bohao Chen, Yanchao Zhang, Yanan Lv +3
Volume microscopy, including electron and light microscopy, suffers from severe anisotropic resolution due to physical axial sectioning. Existing self-supervised axial super-resolu…
NeuroMamba: Multi-Perspective Feature Interaction with Visual Mamba for Neuron Segmentation
Liuyun Jiang, Yizhuo Lu, Yanchao Zhang +2
Neuron segmentation is the cornerstone of reconstructing comprehensive neuronal connectomes, which is essential for deciphering the functional organization of the brain. The irregu…
Diffusion Model-Based Data Augmentation for Enhanced Neuron Segmentation
Liuyun Jiang, Yanchao Zhang, Jinyue Guo +3
Neuron segmentation in electron microscopy (EM) aims to reconstruct the complete neuronal connectome; however, current deep learning-based methods are limited by their reliance on…
From Diffusion to Resolution: Leveraging 2D Diffusion Models for 3D Super-Resolution Task
Bohao Chen, Yanchao Zhang, Yanan Lv +2
Diffusion models have recently emerged as a powerful technique in image generation, especially for image super-resolution tasks. While 2D diffusion models significantly enhance the…