# Publications

## 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>
2. Weiss, J., Bernatz, S., Johnson, J., Thiriveedhi, V., Mak, R. H., Fedorov, A., Lu, M. T. & Aerts, H. J. W. Opportunistic assessment of steatotic liver disease in lung cancer screening eligible individuals. *J. Intern. Med.* (2025). <https://doi.org/10.1111/joim.20053>
3. 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>
4. 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>
5. 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>
6. 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>
7. 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)
8. 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>>
9. Bontempi, D., Nuernberg, L., Pai, S., Krishnaswamy, D., Thiriveedhi, V., Hosny, A., Mak, R. H., Farahani, K., Kikinis, R., Fedorov, A. & Aerts, H. J. W. L. End-to-end reproducible AI pipelines in radiology using the cloud. *Nat. Commun.* 15, 6931 (2024). <http://dx.doi.org/10.1038/s41467-024-51202-2>
10. 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>
11. 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>

## Publications referencing IDC (a subset)

{% hint style="info" %}
See the full list, as curated by Google Scholar, [here](https://scholar.google.com/scholar?oi=bibs\&hl=en\&cites=8052604365477078213).
{% endhint %}

1. Pai, S., Bontempi, D., Hadzic, I., Prudente, V., Sokač, M., Chaunzwa, T. L., Bernatz, S., Hosny, A., Mak, R. H., Birkbak, N. J. & Aerts, H. J. W. L. Foundation model for cancer imaging biomarkers. *Nature Machine Intelligence* 6, 354–367 (2024). <https://www.nature.com/articles/s42256-024-00807-9>
2. Murugesan, G. K., McCrumb, D., Aboian, M., Verma, T., Soni, R., Memon, F. & 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>>
3. Kulkarni, P., Kanhere, A., Yi, P. H. & Parekh, V. S. Text2Cohort: Democratizing the NCI Imaging Data Commons with natural language cohort discovery. *arXiv \[cs.LG]* (2023). at <<http://arxiv.org/abs/2305.07637>>
4. Jiang, P., Sinha, S., Aldape, K., Hannenhalli, S., Sahinalp, C. & Ruppin, E. Big data in basic and translational cancer research. *Nat. Rev. Cancer* 22, 625–639 (2022). <http://dx.doi.org/10.1038/s41568-022-00502-0>
5. Schapiro, D., Yapp, C., Sokolov, A., Reynolds, S. M., Chen, Y.-A., Sudar, D., Xie, Y., Muhlich, J., Arias-Camison, R., Arena, S., Taylor, A. J., Nikolov, M., Tyler, M., Lin, J.-R., Burlingame, E. A., Human Tumor Atlas Network, Chang, Y. H., Farhi, S. L., Thorsson, V., Venkatamohan, N., Drewes, J. L., Pe’er, D., Gutman, D. A., Herrmann, M. D., Gehlenborg, N., Bankhead, P., Roland, J. T., Herndon, J. M., Snyder, M. P., Angelo, M., Nolan, G., Swedlow, J. R., Schultz, N., Merrick, D. T., Mazzili, S. A., Cerami, E., Rodig, S. J., Santagata, S. & Sorger, P. K. MITI minimum information guidelines for highly multiplexed tissue images. *Nat. Methods* 19, 262–267 (2022). <http://dx.doi.org/10.1038/s41592-022-01415-4>
6. Wahid, K. A., Glerean, E., Sahlsten, J., Jaskari, J., Kaski, K., Naser, M. A., He, R., Mohamed, A. S. R. & Fuller, C. D. Artificial intelligence for radiation oncology applications using public datasets. *Semin. Radiat. Oncol.* 32, 400–414 (2022). <http://dx.doi.org/10.1016/j.semradonc.2022.06.009>
7. Hartley, M., Kleywegt, G. J., Patwardhan, A., Sarkans, U., Swedlow, J. R. & Brazma, A. The BioImage Archive - Building a Home for Life-Sciences Microscopy Data. *J. Mol. Biol.* 167505 (2022). doi:10.1016/j.jmb.2022.167505 <http://dx.doi.org/10.1016/j.jmb.2022.167505>
8. Diaz-Pinto, A., Alle, S., Nath, V., Tang, Y., Ihsani, A., Asad, M., Pérez-García, F., Mehta, P., Li, W., Flores, M., Roth, H. R., Vercauteren, T., Xu, D., Dogra, P., Ourselin, S., Feng, A. & Cardoso, M. J. MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images. *arXiv \[cs.HC]* (2022). at <<http://arxiv.org/abs/2203.12362>>
9. <br>


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