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GITBOOK-352: change request with no subject merged in GitBook
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## Publications by the IDC team

1. Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. _National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence_. RadioGraphics (2023). [https://doi.org/10.1148/rg.230180](https://doi.org/10.1148/rg.230180)
2. Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S., Aerts, H. J. W. L., Homeyer, A., Lewis, R., Akbarzadeh, A., Bontempi, D., Clifford, W., Herrmann, M. D., Höfener, H., Octaviano, I., Osborne, C., Paquette, S., Petts, J., Punzo, D., Reyes, M., Schacherer, D. P., Tian, M., White, G., Ziegler, E., Shmulevich, I., Pihl, T., Wagner, U., Farahani, K. & Kikinis, R. NCI Imaging Data Commons. _Cancer Res._ 81, 4188–4193 (2021). [http://dx.doi.org/10.1158/0008-5472.CAN-21-0950](http://dx.doi.org/10.1158/0008-5472.CAN-21-0950)
3. Gorman, C., Punzo, D., Octaviano, I., Pieper, S., Longabaugh, W. J. R., Clunie, D. A., Kikinis, R., Fedorov, A. Y. & Herrmann, M. D. Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology. _Nat. Commun._ 14, 1–15 (2023). [http://dx.doi.org/10.1038/s41467-023-37224-2](http://dx.doi.org/10.1038/s41467-023-37224-2)
4. Bridge, C. P., Gorman, C., Pieper, S., Doyle, S. W., Lennerz, J. K., Kalpathy-Cramer, J., Clunie, D. A., Fedorov, A. Y. & Herrmann, M. D. Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology. _J. Digit. Imaging_ 35, 1719–1737 (2022). [http://dx.doi.org/10.1007/s10278-022-00683-y](http://dx.doi.org/10.1007/s10278-022-00683-y)
5. Schacherer, D. P., Herrmann, M. D., Clunie, D. A., Höfener, H., Clifford, W., Longabaugh, W. J. R., Pieper, S., Kikinis, R., Fedorov, A. & Homeyer, A. The NCI Imaging Data Commons as a platform for reproducible research in computational pathology. _Comput. Methods Programs Biomed._ 107839 (2023). doi:[10.1016/j.cmpb.2023.107839](https://dx.doi.org/10.1016/j.cmpb.2023.107839)
6. Krishnaswamy, D., Bontempi, D., Thiriveedhi, V., Punzo, D., Clunie, D., Bridge, C. P., Aerts, H. J., Kikinis, R. & Fedorov, A. Enrichment of the NLST and NSCLC-Radiomics computed tomography collections with AI-derived annotations. arXiv \[cs.CV] (2023). at <[http://arxiv.org/abs/2306.00150](http://arxiv.org/abs/2306.00150)>
7. Bontempi, D., Nuernberg, L., Krishnaswamy, D., Hosny, A., Farahani, K., Kikinis, R., Fedorov, A. & Aerts, H. J. Transparent and reproducible AI-based medical imaging pipelines using the cloud. _Research Square_ (2023). [https://dx.doi.org/10.21203/rs.3.rs-3142996/v1](https://dx.doi.org/10.21203/rs.3.rs-3142996/v1)
8. Krishnaswamy, D., Bontempi, D., Thiriveedhi, V. K., Punzo, D., Clunie, D., Bridge, C. P., Aerts, H. J. W. L., Kikinis, R. & Fedorov, A. Enrichment of lung cancer computed tomography collections with AI-derived annotations. _Sci. Data_ 11, 1–15 (2024). [https://www.nature.com/articles/s41597-023-02864-y](https://www.nature.com/articles/s41597-023-02864-y)
9. Murugesan, G. K., McCrumb, D., Aboian, M., Verma, T., Soni, R., Memon, F., Farahani, K., Pei, L., Wagner, U., Fedorov, A. Y., Clunie, D., Moore, S. & Van Oss, J. The AIMI Initiative: AI-Generated Annotations for Imaging Data Commons Collections. _arXiv \[eess.IV]_ (2023). at [http://arxiv.org/abs/2310.14897](http://arxiv.org/abs/2310.14897)
2. Thiriveedhi, V. K., Krishnaswamy, D., Clunie, D., Pieper, S., Kikinis, R. & Fedorov, A. Cloud-based large-scale curation of medical imaging data using AI segmentation. _Research Square_ (2024). [https://doi.org/10.21203/rs.3.rs-4351526/v1](https://doi.org/10.21203/rs.3.rs-4351526/v1)
3. Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S., Aerts, H. J. W. L., Homeyer, A., Lewis, R., Akbarzadeh, A., Bontempi, D., Clifford, W., Herrmann, M. D., Höfener, H., Octaviano, I., Osborne, C., Paquette, S., Petts, J., Punzo, D., Reyes, M., Schacherer, D. P., Tian, M., White, G., Ziegler, E., Shmulevich, I., Pihl, T., Wagner, U., Farahani, K. & Kikinis, R. NCI Imaging Data Commons. _Cancer Res._ 81, 4188–4193 (2021). [http://dx.doi.org/10.1158/0008-5472.CAN-21-0950](http://dx.doi.org/10.1158/0008-5472.CAN-21-0950)
4. Gorman, C., Punzo, D., Octaviano, I., Pieper, S., Longabaugh, W. J. R., Clunie, D. A., Kikinis, R., Fedorov, A. Y. & Herrmann, M. D. Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology. _Nat. Commun._ 14, 1–15 (2023). [http://dx.doi.org/10.1038/s41467-023-37224-2](http://dx.doi.org/10.1038/s41467-023-37224-2)
5. Bridge, C. P., Gorman, C., Pieper, S., Doyle, S. W., Lennerz, J. K., Kalpathy-Cramer, J., Clunie, D. A., Fedorov, A. Y. & Herrmann, M. D. Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology. _J. Digit. Imaging_ 35, 1719–1737 (2022). [http://dx.doi.org/10.1007/s10278-022-00683-y](http://dx.doi.org/10.1007/s10278-022-00683-y)
6. Schacherer, D. P., Herrmann, M. D., Clunie, D. A., Höfener, H., Clifford, W., Longabaugh, W. J. R., Pieper, S., Kikinis, R., Fedorov, A. & Homeyer, A. The NCI Imaging Data Commons as a platform for reproducible research in computational pathology. _Comput. Methods Programs Biomed._ 107839 (2023). doi:[10.1016/j.cmpb.2023.107839](https://dx.doi.org/10.1016/j.cmpb.2023.107839)
7. Krishnaswamy, D., Bontempi, D., Thiriveedhi, V., Punzo, D., Clunie, D., Bridge, C. P., Aerts, H. J., Kikinis, R. & Fedorov, A. Enrichment of the NLST and NSCLC-Radiomics computed tomography collections with AI-derived annotations. arXiv \[cs.CV] (2023). at <[http://arxiv.org/abs/2306.00150](http://arxiv.org/abs/2306.00150)>
8. Bontempi, D., Nuernberg, L., Krishnaswamy, D., Hosny, A., Farahani, K., Kikinis, R., Fedorov, A. & Aerts, H. J. Transparent and reproducible AI-based medical imaging pipelines using the cloud. _Research Square_ (2023). [https://dx.doi.org/10.21203/rs.3.rs-3142996/v1](https://dx.doi.org/10.21203/rs.3.rs-3142996/v1)
9. Krishnaswamy, D., Bontempi, D., Thiriveedhi, V. K., Punzo, D., Clunie, D., Bridge, C. P., Aerts, H. J. W. L., Kikinis, R. & Fedorov, A. Enrichment of lung cancer computed tomography collections with AI-derived annotations. _Sci. Data_ 11, 1–15 (2024). [https://www.nature.com/articles/s41597-023-02864-y](https://www.nature.com/articles/s41597-023-02864-y)
10. Murugesan, G. K., McCrumb, D., Aboian, M., Verma, T., Soni, R., Memon, F., Farahani, K., Pei, L., Wagner, U., Fedorov, A. Y., Clunie, D., Moore, S. & Van Oss, J. The AIMI Initiative: AI-Generated Annotations for Imaging Data Commons Collections. _arXiv \[eess.IV]_ (2023). at [http://arxiv.org/abs/2310.14897](http://arxiv.org/abs/2310.14897)

## Publications referencing IDC (a subset)

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