IDC User Guide
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Publications

Publications by the IDC team

  1. 1.
    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​
  2. 2.
    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​
  3. 3.
    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. arXiv [cs.CV] (2023). at <http://arxiv.org/abs/2303.09354>
  4. 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​
  5. 5.
    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>
  6. 6.
    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​
  7. 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​

Publications referencing IDC (a subset)

See the full list, as curated by Google Scholar, here.
  1. 1.
    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>
  2. 2.
    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>
  3. 3.
    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​
  4. 4.
    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​
  5. 5.
    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​
  6. 6.
    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​
  7. 7.
    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>
  8. 8.
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