DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative collections
Creators
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. You can use the manifests included in this Zenodo record to download the content of the collection following the Download instructions below.
Collection description
CMB program is organized into multiple cancer-specific collections. Digital pathology images for each of those collections were converted into DICOM representation by the IDC team and are shared via IDC.
1. CMB-AML (acute myeloid leukemia cancer)
2. CMB-CRC (colorectal cancer)
3. CMB-GEC (gastroesophageal cancer)
4. CMB-LCA (lung cancer)
5. CMB-MEL (melanoma)
6. CMB-MEL (multiple myeloma)
7. CMB-PCA (prostate cancer)
Digital pathology images, augmented with the metadata describing their content, were converted into DICOM Whole Slide Microscopy (SM) representation [2,3] using custom open source scripts and tools as described in [4].
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.
For each of the collections, the following manifest files are provided:
<collection_id>-idc_v19-aws.s5cmd
: manifest of files available for download from public IDC Amazon Web Services buckets<collection_id>-idc_v19-gcs.s5cmd
: manifest of files available for download from public IDC Google Cloud Storage buckets<collection_id>-idc_v19-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. L., 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 43, (2023).
[2] National Electrical Manufacturers Association (NEMA). DICOM PS3.3 - Information Object Definitions: A.32.8 VL Whole Slide Microscopy Image IOD. at <https://dicom.nema.org/medical/dicom/current/output/html/part03.html#sect_A.32.8>
[3] Herrmann, M. D., Clunie, D. A., Fedorov, A., Doyle, S. W., Pieper, S., Klepeis, V., Le, L. P., Mutter, G. L., Milstone, D. S., Schultz, T. J., Kikinis, R., Kotecha, G. K., Hwang, D. H., Andriole, K. P., John Lafrate, A., Brink, J. A., Boland, G. W., Dreyer, K. J., Michalski, M., Golden, J. A., Louis, D. N. & Lennerz, J. K. Implementing the DICOM standard for digital pathology. J. Pathol. Inform. 9, 37 (2018).
[4] Clunie, D., Fedorov, A. & Herrmann, M. D. ImagingDataCommons/idc-wsi-conversion: Initial release. (Zenodo, 2023). doi:10.5281/ZENODO.8240154
Files
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