- Overview
- Background
- Reference
- Materials
- Group
- Contribution
We are mainly focusing connectomics datasets generated by the volume electron microscopy.
Name for short |
Species | Sample | Microscopy | Size μm3 |
Resolution nm3 |
Number | Link | Reference | Note |
---|---|---|---|---|---|---|---|---|---|
AxonEM | mouse | primary visual cortex | ssTEM | 30x30x30 | 7x7x40 | 18,000 axons | grand-challenge | Wei et al., 2021 | subsets of MICrONS and H01 |
human | temporal cortex | ATUM-mSEM | 8x8x30 | ||||||
ISBI | drosophila | ventral nerve line | ssTEM | 2x2x1.5 | 4x4x50 | Segmentation of neuronal structures in EM stacks | |||
SNEMI3D | mouse | cortex | ATUM-SEM | 6x6x3 | 6x6x30 | SNEMI3D: 3D Segmentation of neurites in EM images | |||
AC3/AC4 | mouse | cortex | ATUM-SEM | 6x6x3 | 6x6x30 | different membrane labeling at myelin | |||
CREMI | drosophila | melanogaster brain | ssTEM | 5x5x5 | 4x4x40 | CREMI | MICCAI Challenge on Circuit Reconstruction from Electron Microscopy Images | ||
VNC | drosophila | ventral nerve cord | ssTEM | 4.7x4.7x1 | 4.6x4.6x45 | github | Gerhard et al., 2013 | ||
SegEM | et al., 2015 | ||||||||
FIB-25 (training) | https://github.com/janelia-flyem/neuroproof_examples | et al., 2013 | |||||||
MICRONS (training from 3 stacks) | et al., 2013 |
Name for short |
Species | Sample | Microscopy | Size μm3 |
Resolution nm3 |
Number | Link | Reference | Note |
---|---|---|---|---|---|---|---|---|---|
AxonEM | mouse | primary visual cortex | ssTEM | 30x30x30 | 7x7x40 | 18,000 axons | grand-challenge | Wei et al., 2021 | subsets of MICrONS and H01 |
human | temporal cortex | ATUM-mSEM | 8x8x30 | ||||||
H01 | human | temporal lobe | ATUM-mSEM | 2,000x3,000x175 | 4x4x30 | 50,000 cells 133,700,000 synapses |
Shapson-Coe et al., 2021 | ||
J0126 | finch | area X | SBF-SEM | 96x98x114 | 9x9x20 | 33 blocks 12+50 skels |
cloudvolume-raw cloudvolume-seg |
Januszewski et al., 2018 | testing for FFN |
Kasthuri | mouse | neocortex | ATUM-SEM | 40x40x50 | 3x3x30 | 1,700 synapses | vast | Kasthuri et al., 2015 | superset of SNEMI |
MICrONS Cortical mm3 | mouse | primary visual cortex and three higher visual areas | autoTEM | 1,300x870x820 | 4x4x40 | 200,000 cells 524,000,000 synapses |
microns zenodo bossdb |
MICrONS Consortium et al., 2021 | |
MICrONS Layer 2/3 | mouse | primary visual cortex | ssTEM | 250x140x90 | 3.58x3.58x40 | 451 neurons (417 PyCs) 169 non-neuronal cells |
microns | Turner et al., 2022 | pilot dataset of MICrONS Cortical mm3 |
ISBI | drosophila | ventral nerve line | ssTEM | 2x2x1.5 | 4x4x50 | Segmentation of neuronal structures in EM stacks | |||
SNEMI3D | mouse | cortex | ATUM-SEM | 6x6x3 | 6x6x30 | SNEMI3D: 3D Segmentation of neurites in EM images | |||
CREMI | drosophila | melanogaster brain | ssTEM | 5x5x5 | 4x4x40 | CREMI | MICCAI Challenge on Circuit Reconstruction from Electron Microscopy Images | ||
Images of mouse piriform cortex | mouse | piriform cortex | ssTEM | 3.5x3.5x6.8 | 7x7x40 | Kisuk Lee et al., 2015 | |||
VNC | drosophila | ventral nerve cord | ssTEM | 4.7x4.7x1 | 4.6x4.6x45 | github | Gerhard et al., 2013 |
- Kornfeld and Denk. Progress and Remaining Challenges in High-throughput Volume Electron Microscopy. 2018
- Kievits et al. How Innovations in Methodology Offer New Prospects for Volume Electron Microscopy. 2022
- Beyer et al. A Survey of Visualization and Analysis in High-Resolution Connectomics. 2022
- Open Connectome Project
- BossDB
- webKnossos
- Neuroglancer
- Local Shape Descriptors
- PyTorch Connectomics
- EMPIAR
- Zenodo
- Lichtman Lab, Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University
- Seung Lab, Computer Science Department, Princeton Neuroscience Institute
- Helmstaedter Lab, Department of Connectomics, Max Planck Institute for Brain Research
- Pfister Lab, Visual Computing Group, School of Engineering and Applied Sciences, Harvard University
- Funke Lab, Janelia Research Campus, Howard Hughes Medical Institute
- Lee Lab, Boston Children's Hospital, Harvard Medical School
Please contribute if you think a new dataset or a relevant paper is missing.
Let's enjoy the beauty of EM data and the awesome micro-connectomes!