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Datasets:
radar-generalist
/
RADAR-auxiliary-data

Tasks:
Image Segmentation
Languages:
English
Size:
10K - 100K
Tags:
vision-language pretraining
medical
ct diagnosis
anatomical segmentation
TotalSegmentator
Libraries:
Datasets
License:
Dataset card Data Studio Files
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  # RADAR: Preprocessed Anatomical Masks for Merlin CT Data
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- [![Paper](https://img.shields.io/badge/Science-Paper-blue?logo=google-scholar)](https://www.science.org/doi/10.1126/science.aec6129)
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- [![GitHub](https://img.shields.io/badge/GitHub-Code-blue?logo=github)](https://github.com/alibaba-damo-academy/damo-radar)
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- [![Zenodo](https://img.shields.io/badge/Zenodo-Code-7B61FF?logo=zenodo&logoColor=white)](https://zenodo.org/records/21271172)
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- [![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC_BY--NC--SA_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
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  This dataset provides **preprocessed anatomical segmentation masks** for the [Merlin](https://github.com/StanfordMIMI/Merlin) abdominal CT training set, generated by [TotalSegmentator](https://github.com/wasserth/TotalSegmentator) and post-processed for use with the [RADAR](https://github.com/alibaba-damo-academy/damo-radar) framework. These masks enable anatomy-aware vision–language pretraining without any additional manual annotation.
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  # RADAR: Preprocessed Anatomical Masks for Merlin CT Data
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+ [![Paper](https://img.shields.io/badge/Science-Paper-2B6CB0?logo=google-scholar&logoColor=white)](https://www.science.org/doi/10.1126/science.aec6129)
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+ [![GitHub](https://img.shields.io/badge/GitHub-Code-B85C38?logo=github&logoColor=white)](https://github.com/alibaba-damo-academy/damo-radar)
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+ [![Zenodo](https://img.shields.io/badge/Zenodo-Code-0F766E?logo=zenodo&logoColor=white)](https://zenodo.org/records/21271172)
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+ [![License](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-7C3F58?logo=creativecommons&logoColor=white)](https://creativecommons.org/licenses/by-nc-sa/4.0/)
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  This dataset provides **preprocessed anatomical segmentation masks** for the [Merlin](https://github.com/StanfordMIMI/Merlin) abdominal CT training set, generated by [TotalSegmentator](https://github.com/wasserth/TotalSegmentator) and post-processed for use with the [RADAR](https://github.com/alibaba-damo-academy/damo-radar) framework. These masks enable anatomy-aware vision–language pretraining without any additional manual annotation.
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