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  3. BIMCV-R/README.md +58 -0
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+ ---
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+ license: mit
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+ task_categories:
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+ - text-generation
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+ - visual-question-answering
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+ language:
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+ - en
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+ tags:
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+ - biology
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+ - medical
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+ ---
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+ # MICCAI24 3D CT and Medical Annotation Dataset
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+
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+ This dataset is derived from the BIMCV database and has been curated for the MICCAI24 paper. The dataset consists of 8069 3D CT scans and associated medical annotations, providing a valuable resource for medical imaging research.
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+
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+ ## Dataset Overview
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+
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+ - **Source**: [BIMCV Database](https://bimcv.cipf.es/bimcv-projects/bimcv-covid19/#1590857662078-c30d2790-05dc)
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+ - **Paper**: [MICCAI24](https://link.springer.com/chapter/10.1007/978-3-031-72120-5_12)
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+ - **Content**: The dataset includes approximately 8,000 image-text pairs, with over 2 million 2D CT slices.
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+
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+ ## Structure
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+
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+ - **CT Scans**: Stored in folders prefixed with `CT`.
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+ - **Medical Reports**: Stored in the `BIMCV-R.csv` file.
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+
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+ ## Repository
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+
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+ The MedFinder source code is available on GitHub:
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+
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+ 🔗 **[MedFinder GitHub Repository](https://github.com/ydchen0806/MedFinder)**
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+
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+ ## License
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+
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+ This dataset is provided for academic research purposes only. The data has been anonymized and should not be used for any commercial purposes, such as instrument preparation, commercial algorithm development, etc. All uses must be approved through an application process.
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+
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+ By using this dataset, you agree to the following terms:
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+
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+ - The dataset is intended solely for academic research purposes.
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+ - Commercial use, including but not limited to instrument preparation and commercial algorithm development, is strictly prohibited.
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+ - The data has been anonymized to protect patient privacy.
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+ - Any use of the dataset must be approved through an application process.
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+
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+ For more information or to request access, please contact [[email protected]].
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+
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+ ## Citation
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+
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+ If you use this dataset in your research, please cite the MICCAI24 paper:
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+
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+ ```bibtex
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+ @inproceedings{chen2024bimcv,
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+ title={Bimcv-r: A landmark dataset for 3d ct text-image retrieval},
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+ author={Chen, Yinda and Liu, Che and Liu, Xiaoyu and Arcucci, Rossella and Xiong, Zhiwei},
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+ booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
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+ pages={124--134},
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+ year={2024},
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+ organization={Springer}
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+ }
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