SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
Paper
• 2310.15161 • Published
Datasets:
ArXiv:
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Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ImportError
Message: To support decoding NIfTI files, please install 'nibabel'.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2061, in __iter__
batch = formatter.format_batch(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
batch = self.python_features_decoder.decode_batch(batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2161, in decode_batch
decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1419, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/nifti.py", line 172, in decode_example
raise ImportError("To support decoding NIfTI files, please install 'nibabel'.")
ImportError: To support decoding NIfTI files, please install 'nibabel'.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.
SA-Med3D-140K [github]
Dataset Summary
SA-Med3D-140K is a large-scale, multi-modal, multi-anatomical volumetric medical image segmentation dataset. It was created to facilitate the development of general-purpose foundation models for 3D medical image segmentation. The dataset comprises 21,729 3D medical images and 143,518 corresponding masks. It was gathered from a combination of 70 public datasets and 8,128 privately licensed annotated cases from 24 hospitals.
Supported Tasks
The primary task supported by this dataset is general-purpose, promptable segmentation of volumetric medical images.
It is designed to train and evaluate models that can segment a wide variety of anatomical structures and lesions across different medical imaging modalities.
Citation
If you use this dataset, please cite the associated paper:
@misc{wang2024sammed3dgeneralpurposesegmentationmodels,
title={SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images},
author={Haoyu Wang and Sizheng Guo and Jin Ye and Zhongying Deng and Junlong Cheng and Tianbin Li and Jianpin Chen and Yanzhou Su and Ziyan Huang and Yiqing Shen and Bin Fu and Shaoting Zhang and Junjun He and Yu Qiao},
year={2024},
eprint={2310.15161},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2310.15161},
}
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