Datasets:
Tasks:
Image Segmentation
Languages:
English
Size:
1K - 10K
Tags:
medical-imaging
electron-microscopy
nuclei-segmentation
3d-segmentation
zebrafish
neuroscience
License:
Search is not available for this dataset
main array 2D |
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End of preview. Expand in Data Studio
NucMM-Z Dataset
Overview
NucMM-Z (Neuronal Nuclei from Zebrafish) is a 3D electron microscopy (EM) dataset for nuclei instance segmentation from zebrafish brain tissue.
| Property | Value |
|---|---|
| Modality | Electron Microscopy (EM) |
| Task | Nuclei instance segmentation |
| Anatomy | Zebrafish brain |
| Volume Size | 64 × 64 × 64 voxels per patch |
| Train Volumes | 27 |
| Val Volumes | 27 |
| Total Size | ~1.09 GB |
Dataset Structure
NucMM-Z/
├── image.tif # Full raw volume (~1 GB)
├── mask.h5 # Full annotation volume
├── README.txt # Original readme
├── Image/
│ ├── train/ # 27 training patches (.h5)
│ └── val/ # 27 validation patches (.h5)
└── Label/
├── train/ # 27 training labels (.h5)
└── val/ # 27 validation labels (.h5)
Label Format
- Instance Segmentation: Each nucleus has a unique integer ID
- Background: 0
- Typical density: 50-300 nuclei per 64×64×64 volume
Usage with EasyMedSeg
from dataloader import NucMMZImageDataset, NucMMZVideoDataset
# Image mode (2D slices) - Recommended
dataset = NucMMZImageDataset(split='train')
sample = dataset[0] # Returns dict with 'image' and 'mask'
# Video mode (3D volumes as frame sequences)
dataset = NucMMZVideoDataset(split='train')
video = dataset[0] # Returns dict with 'frames' and 'masks'
Benchmark Results (SAM2)
| Mode | Model | Mean Dice | Mean IoU |
|---|---|---|---|
| Image | sam2_hiera_large | 0.3438 | 0.2566 |
| Video | sam2_video_hiera_large | 0.0631 | 0.0425 |
Recommendation: Use image mode for this dataset.
Source
- Original: PyTorch Connectomics NucMM
- Paper: Wei et al., MICCAI 2020
License
CC BY 4.0
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