Datasets:
Tasks:
Image Segmentation
Languages:
English
Size:
1K<n<10K
Tags:
medical-imaging
electron-microscopy
nuclei-segmentation
3d-segmentation
zebrafish
neuroscience
License:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 49, in _split_generators
import h5py
ModuleNotFoundError: No module named 'h5py'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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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