| --- |
| dataset_info: |
| features: |
| - name: organ |
| dtype: string |
| - name: image |
| dtype: image |
| - name: binary_mask |
| dtype: image |
| - name: classes_mask |
| dtype: image |
| - name: volume_id |
| dtype: int32 |
| - name: slice_id |
| dtype: int32 |
| splits: |
| - name: train |
| num_bytes: 8036673401.379 |
| num_examples: 95311 |
| download_size: 8926670093 |
| dataset_size: 8036673401.379 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-segmentation |
| language: |
| - en |
| tags: |
| - organs |
| - medical |
| - ct |
| - mri |
| pretty_name: Mini Medical Segmentation Decathlon 244 |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # Processed and Reduced Medical Segmentation Decathlon Dataset |
| <!-- Provide a quick summary of the dataset. --> |
| The miniMSD dataset is a medical image segmentation benchmark covering 10 human organs. |
| It is derived from the [Medical Segmentation Decathlon (MSD)](http://medicaldecathlon.com) by converting volumetric scans |
| from NIfTI (NII) format into serialized 2D RGB images, alongside their corresponding segmentation masks. |
| The dataset is provided in multiple resolution variants ([244](https://huggingface.co/datasets/chehablaborg/miniMSD244) |
| and [512](https://huggingface.co/datasets/chehablaborg/miniMSD512)), enabling easier use, |
| off-the-shelf accessibility, and flexible experimentation. |
|
|
| ## Dataset Details |
| The dataset covers 10 human body organs, listed below. |
| Each organ includes up to 40 volumes, with each volume consisting of a variable number of image slices. |
| Each dataset entry contains the following components: the organ type, the image, a binary mask, |
| a detailed (multi-class) mask, a volume ID, and a slice ID. |
| The image, binary mask, and detailed mask are all provided as PIL images. |
| The binary mask contains two labels: 0 for background and 1 for the target region. |
| The detailed mask contains multiple labels (0, 1, 2, 3, …), where each label corresponds to a specific |
| anatomical structure. The mapping of label indices to structures is provided below. |
|
|
| | Organ | Number of Volumes | Total Slices | Avg. Slices per Volume | % of Total Slices | |
| |----------------|-------------------|--------------|------------------------|-------------------| |
| | Prostate | 32 | 1204 | 37.625 | 1.26% | |
| | Heart | 20 | 2271 | 113.550 | 2.38% | |
| | Hippocampus | 40 | 2754 | 68.850 | 2.89% | |
| | HepaticVessel | 40 | 5796 | 144.900 | 6.08% | |
| | BrainTumour | 40 | 6200 | 155.000 | 6.51% | |
| | Spleen | 40 | 6964 | 174.100 | 7.31% | |
| | Pancreas | 40 | 7068 | 176.700 | 7.42% | |
| | Colon | 40 | 7344 | 183.600 | 7.71% | |
| | Lung | 40 | 22510 | 562.750 | 23.62% | |
| | Liver | 40 | 33200 | 830.000 | 34.83% | |
|
|
| ## Labels Mapping |
| ### BrainTumour |
| - 0: background |
| - 1: necrotic / non-enhancing tumor |
| - 2: edema |
| - 3: enhancing tumor |
|
|
| ### Heart |
| - 0: background |
| - 1: left atrium |
|
|
| ### Liver |
| - 0: background |
| - 1: liver |
| - 2: tumor |
|
|
| ### Hippocampus |
| - 0: background |
| - 1: anterior |
| - 2: posterior |
|
|
| ### Prostate |
| - 0: background |
| - 1: peripheral zone |
| - 2: transition zone |
|
|
| ### Lung |
| - 0: background |
| - 1: nodule |
|
|
| ### Pancreas |
| - 0: background |
| - 1: pancreas |
| - 2: tumor |
|
|
| ### HepaticVessel |
| - 0: background |
| - 1: vessel |
| - 2: tumor |
|
|
| ### Spleen |
| - 0: background |
| - 1: spleen |
|
|
| ### Colon |
| - 0: background |
| - 1: colon |
|
|
| ## Uses |
|
|
| <!-- Address questions around how the dataset is intended to be used. --> |
|
|
| ```python |
| from datasets import load_dataset |
| miniMSD244 = load_dataset("chehablaborg/miniMSD244", split="train") |
| |
| sample_id = 312 |
| organ = miniMSD244[sample_id]["organ"] |
| image = miniMSD244[sample_id]["image"] |
| binary_mask = miniMSD244[sample_id]["binary_mask"] |
| classes_mask = miniMSD244[sample_id]["classes_mask"] |
| plt.imshow(image, cmap="grey") |
| plt.show() |
| ``` |
|
|
| ## Authors |
|
|
| [Charbel Toumieh](https://www.linkedin.com/in/charbeltoumieh/) |
|
|
| [Ahmad Mustapha](https://www.linkedin.com/in/ahmad-mustapha-ml/) |
|
|
| [Ali Chehab](https://www.linkedin.com/in/ali-chehab-31b05a3/) |
|
|
|
|
| ## Citation |
|
|
| ``` |
| @dataset{minimsd2026, |
| title = {MiniMSD}, |
| author = {Toumieh, Charbel and Mustapha, Ahmad and Chehab, Ali}, |
| year = {2026}, |
| publisher = {Hugging Face}, |
| howpublished = {\url{https://huggingface.co/datasets/chehablaborg/miniMSD244}}, |
| } |
| ``` |
|
|
| ## Acknowledgment |
| [Chehab lab](https://chehablab.com) @ 2026 |
