| | --- |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | dataset_info: |
| | features: |
| | - name: image |
| | dtype: image |
| | - name: crop_name |
| | dtype: string |
| | - name: axis |
| | dtype: string |
| | - name: slice |
| | dtype: int32 |
| | splits: |
| | - name: train |
| | num_bytes: 54704214286 |
| | num_examples: 238805 |
| | download_size: 54701266342 |
| | dataset_size: 54704214286 |
| | license: cc-by-4.0 |
| | --- |
| | # CellMap 2D |
| |
|
| | This dataset contains all 2D slices from the EM volumes used in the [CellMap segmentation challenge](https://cellmapchallenge.janelia.org/). |
| | The dataset contains all *x*, *y*, *z* slices obtained from a total of 289 3D EM volume crops (the crops come from 22 different samples). |
| | The slices are in their native resolution (no resizing). |
| |
|
| | You can load the dataset as follows (*non-streaming* mode): |
| | ```python |
| | ds = load_dataset("eminorhan/cellmap-2d", split='train') |
| | ``` |
| | and then inspect the first data row: |
| | ```python |
| | >>> print(ds[0]) |
| | >>> { |
| | 'image': <PIL.PngImagePlugin.PngImageFile image mode=L size=300x300 at 0xFFF93926C850>, |
| | 'crop_name': 'jrc_mus-kidney/recon-1/crop129', |
| | 'axis': 'z', |
| | 'slice': 0 |
| | } |
| | ``` |
| | where: |
| | * `image` contains the actual 2D slice encoded as a `PIL.Image` object. |
| | * `crop_name` is an identifier string indicating the sample and crop names the slice comes from. |
| | * `axis` indicates the axis along which the slice was taken (`x`, `y`, or `z`). |
| | * `slice` is the slice index along the `axis`. |
| |
|
| | Please note that the dataset rows are pre-shuffled to make the shards roughly uniform in size. |
| |
|
| | **License:** The data originally come from HHMI Janelia's [OpenOrganelle](https://www.openorganelle.org/) data portal [released](https://www.openorganelle.org/faq#sharing) under the [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/deed.en) license. |
| |
|
| | **Citation:** If you use these data, please cite the following papers: |
| | ``` |
| | @article{heinrich2021whole, |
| | title={Whole-cell organelle segmentation in volume electron microscopy}, |
| | author={Heinrich, Larissa and Bennett, Davis and Ackerman, David and Park, Woohyun and Bogovic, John and Eckstein, Nils and Petruncio, Alyson and Clements, Jody and Pang, Song and Xu, C Shan and others}, |
| | journal={Nature}, |
| | volume={599}, |
| | number={7883}, |
| | pages={141--146}, |
| | year={2021}, |
| | publisher={Nature Publishing Group UK London} |
| | } |
| | ``` |
| | [Paper link](https://www.nature.com/articles/s41586-021-03977-3) |
| |
|
| |
|
| | ``` |
| | @misc{CellMap2024, |
| | title={CellMap 2024 Segmentation Challenge}, |
| | author={{CellMap Project Team} and Ackerman, David and Ahrens, Misha B. and Aso, Yoshinori and Avetissian, Emma and Bennett, Davis and others}, |
| | year={2024}, |
| | publisher={Janelia Research Campus}, |
| | doi={10.25378/janelia.c.7456966}, |
| | } |
| | ``` |
| | [Paper link](https://janelia.figshare.com/collections/CellMap_2024_Segmentation_Challenge/7456966) |
| |
|
