MitoVerse / README.md
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metadata
license: other
task_categories:
  - image-segmentation
tags:
  - electron-microscopy
  - connectomics
  - mitochondria
  - 3d-segmentation
  - instance-segmentation
pretty_name: MitoVerse
size_categories:
  - 10B<n<100B

MitoVerse

A generalist 3D-EM mitochondria segmentation benchmark: many domains (modality, species, tissue, resolution) in one consistent format, with instance labels.

Code, loaders, ingestion, and PyTorchConnectomics usage: 👉 https://github.com/PytorchConnectomics/mitoverse

Each volume is one zarr store data/<dataset>/<volume>.zarr with arrays img (uint8, ZYX) and mito (instance, 0=background); per-volume metadata (voxel size, modality, species, tissue) lives in its .zattrs and in catalog.json. Semantic masks are mito > 0 — derive as needed.

3D EM Datasets with Mitochondria Annotation

* = instance labels we converted from binary segmentation. = redistribution caveat. Shape is the average (x,y,z) per volume, ×N = number of volumes.

Microscope Dataset Species Region Avg Shape (xyz) Resolution (nm) # Mitos
FIB-SEM OpenOrganelle (Xu'21), CellMap annot. mixed various cells/tissues (213,204,203)×147 8×8×8 1580
FIB-SEM └ + MitoEM2.0 chunks (Liu et al. '26) mixed jurkat/macro/kidney/liver/cardiac (1024,1024,256)×10 8×8×8 2910
FIB-SEM Müller'21 (BetaSeg)* Mouse Pancreas (β-cells) (874,669,979)×7 16×16×16 1852
FIB-SEM Mekuč'20 (UroCell) Mouse Urinary bladder (256,256,256)×5 16×16×15 287
FIB-SEM Kunduri'22 Drosophila Gonad (spermatocyte) (1024,1024,341)×3 16×16×16 621
FIB-SEM Conrad'23 (MitoNet) mixed fly brain / C. elegans / HeLa / muscle / salivary (546,446,466)×5 12–24 (iso) 635
ssSEM Wei'20 (MitoEM) Human Temporal lobe (L2) (4096,4096,500) 8×8×30 10552
ssSEM Wei'20 (MitoEM) Rat V1 (L2/3) (4096,4096,500) 8×8×30 5446
ssSEM Casser'20 (Kasthuri++)* Mouse Somatosensory (L4/5) (700,791,80)×2 12×12×30 265
FIB-SEM └ Lucchi++ (Lucchi'13)* Mouse Hippocampus (512,768,82) 10×10×10 70
ssSEM Xiao'18 Mouse Auditory cortex (2156,2104,31) 8×8×50 468
ssSEM Han'24 Mouse Cerebellum (mossy fiber) (1357,1411,331)×5 8×8×30 1144
ssTEM Turner'22 (MICrONS, Pinky) Mouse V1 (Pinky + MICrONS1) (1203,1282,83)×16 8×8×40 1420
SBF-SEM Jiang'25 Mouse Brainstem (1000,1000,100)×3 15×15×40 2057
SBF-SEM Guay'21* Human Platelet (667,736,65)×3 10×10×50 279
SBF-SEM Haberl'18 (CDeep3M)* Mouse Cerebellum (brain) (256,256,15)×2 10×10×24 247

Total: 212 volumes, 29,833 mitochondria. Volumes are organized by imaging source; benchmarks are split overlays in splits/: cellmap.json (CellMap challenge over OpenOrganelle crops) and mitoem2.0.json (MitoEM2.0 generalization suite). The OpenOrganelle *_test0/_test1 volumes are lab-annotated and belong to mitoem2.0.

MitoEM2.0 benchmark

MitoEM2.0 (Liu et al., 2026) is a multi-domain generalization benchmark of 8 sub-datasets. Official nnU-Net release: Zenodo 10.5281/zenodo.20417683. Within MitoVerse it is not duplicated — it is the split overlay splits/mitoem2.0.json over the source volumes below (muller21, openorganelle, han24, wei20, jiang25, kunduri22). EFI/DCI are per-dataset difficulty metrics from the MitoEM2.0 paper; redistribution caveat, * converted to instances.

Name Organism Tissue Cell type Modality Avg Shape (xyz) Voxels Split (tr/val/te) # Mito EFI/DCI Source
ME2-Beta Mouse Pancreas β-cell FIB-SEM (874,669,979) 3961M 3/1/3 1935 0.02/2.68 Müller'21 †
ME2-Jurkat Human Cell line Jurkat FIB-SEM (1024,1024,256) 805M 1/1/1 372 0.00/1.62 Xu'21 *
ME2-Macro Human Cell line Macrophages FIB-SEM (1024,1024,256) 805M 1/1/1 497 0.01/1.38 Xu'21 *
ME2-Mossy Mouse Cerebellum Mossy Fiber ssSEM (1024,1024,500) 3333M 3/1/3 1099 0.10/4.13 Han'24
ME2-Pyra Human Cerebrum Pyramidal ssSEM (4096,4096,500) 8388M 3/1/11 45 0.96/0.53 Wei'20
ME2-Podo Mouse Kidney Podocyte FIB-SEM (1024,1024,256) 805M 1/1/1 1333 0.00/2.43 CellMap'24 †
ME2-Sperm Drosophila Gonad Spermatocyte FIB-SEM (1024,1024,341) 1073M 3/1/4 775 0.01/0.96 Kunduri'22 †
ME2-Stem Mouse Brainstem Mix SBF-SEM (1024,1024,100) 300M 1/1/1 2058 0.09/0.80 Jiang'25

License

Per-volume; see each volume's source in catalog.json. Some sources (MICrONS †, CellMap) carry attribution or redistribution caveats — check before reuse.

Acknowledgement