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GITBOOK-308: change request with no subject merged in GitBook
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* [Frequently asked questions](frequently-asked-questions.md)
* [Support](support.md)
* [Key pointers](idc-key-pointers.md)
* [Publications](publications.md)
* [IDC team](idc-team.md)

## Introduction
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* Documentation: [https://learn.canceridc.dev/](https://learn.canceridc.dev/)
* GitHub organization: [https://github.com/ImagingDataCommons](https://github.com/ImagingDataCommons)
* Tutorials: [https://github.com/ImagingDataCommons/IDC-Tutorials/tree/master/notebooks/getting\_started](https://github.com/ImagingDataCommons/IDC-Tutorials/tree/master/notebooks/getting\_started)

## Publications by the IDC team

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](http://dx.doi.org/10.1158/0008-5472.CAN-21-0950)
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](http://dx.doi.org/10.1038/s41467-023-37224-2)
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](http://arxiv.org/abs/2303.09354)>&#x20;
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)

## 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. 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](http://arxiv.org/abs/2305.07637)> &#x20;
2. 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](http://dx.doi.org/10.1038/s41568-022-00502-0)
3. 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](http://dx.doi.org/10.1038/s41592-022-01415-4)
4. 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](http://dx.doi.org/10.1016/j.semradonc.2022.06.009)
5. 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](http://dx.doi.org/10.1016/j.jmb.2022.167505)
6. 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](http://arxiv.org/abs/2203.12362)>&#x20;
7.

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* [Publications](publications.md)
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# Publications

## Publications by the IDC team

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](http://dx.doi.org/10.1158/0008-5472.CAN-21-0950)
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](http://dx.doi.org/10.1038/s41467-023-37224-2)
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](http://arxiv.org/abs/2303.09354)>&#x20;
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. 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)>
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](https://dx.doi.org/10.21203/rs.3.rs-3142996/v1)

## 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. 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](http://arxiv.org/abs/2305.07637)> &#x20;
2. 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](http://dx.doi.org/10.1038/s41568-022-00502-0)
3. 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](http://dx.doi.org/10.1038/s41592-022-01415-4)
4. 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](http://dx.doi.org/10.1016/j.semradonc.2022.06.009)
5. 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](http://dx.doi.org/10.1016/j.jmb.2022.167505)
6. 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](http://arxiv.org/abs/2203.12362)>&#x20;
7.

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