DOI: 10.5281/zenodo.12666741
title: DICOM converted Slide Microscopy images for the CPTAC-AML collection

description: This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute
Imaging Data Commons (IDC) [1]. This dataset was converted
into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using
IDC Portal here: CPTAC-AML. You can use the manifests included in this
Zenodo record to download the content of the collection following the Download instructions below.

Collection description



    This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Acute Myeloid Leukemia (CPTAC-AML) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.


    Please see the CPTAC-AML  wiki page to learn more about the images and to obtain any supporting metadata for this collection.

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced.
For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the
collection_id collection introduced in IDC data
release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of
the corresponding collection was introduced.



cptac_aml-idc_v7-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets

cptac_aml-idc_v7-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets

cptac_aml-idc_v7-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids)


Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference
files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.


Download instructions

Each of the manifests include instructions in the header on how to download the included files.

To download the files using .s5cmd manifests:



install idc-index package: pip install --upgrade idc-index

download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd.


To download the files using .dcf manifest, see manifest header.


Acknowledgments

Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute,
National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l.


References

[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