40 citations · 182 across the 16 of their papers we have counts for
17 papers
PyTorch Connectomics: A Scalable and Flexible Segmentation Framework for EM Connectomics
Zudi Lin, Donglai Wei, Jeff Lichtman +1
We present PyTorch Connectomics (PyTC), an open-source deep-learning framework for the semantic and instance segmentation of volumetric microscopy images, built upon PyTorch. We de…
NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale
Zudi Lin, Donglai Wei, Mariela D. Petkova +12
Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages. Howe…
VICE: Visual Identification and Correction of Neural Circuit Errors
Felix Gonda, Xueying Wang, Johanna Beyer +3
A connectivity graph of neurons at the resolution of single synapses provides scientists with a tool for understanding the nervous system in health and disease. Recent advances in…
Learning Guided Electron Microscopy with Active Acquisition
Lu Mi, Hao Wang, Yaron Meirovitch +5
Single-beam scanning electron microscopes (SEM) are widely used to acquire massive data sets for biomedical study, material analysis, and fabrication inspection. Datasets are typic…
A Topological Nomenclature for 3D Shape Analysis in Connectomics
Abhimanyu Talwar, Zudi Lin, Donglai Wei +7
One of the essential tasks in connectomics is the morphology analysis of neurons and organelles like mitochondria to shed light on their biological properties. However, these biolo…
Detecting Synapse Location and Connectivity by Signed Proximity Estimation and Pruning with Deep Nets
Toufiq Parag, Daniel Berger, Lee Kamentsky +5
Synaptic connectivity detection is a critical task for neural reconstruction from Electron Microscopy (EM) data. Most of the existing algorithms for synapse detection do not identi…