Warning
This package is in its early development stages. Its functionality and API will change.
Stay tuned for the updates and documentation, and please share your feedback about it by opening issues in this repository, or by starting a discussion in IDC User forum.
idc-index
is a Python package that enables basic operations for working with
NCI Imaging Data Commons (IDC):
- subsetting of the IDC data using selected metadata attributes
- download of the files corresponding to selection
- generation of the viewer URLs for the selected data
Install the latest version of the package.
$ pip install --upgrade idc-index
Instantiate IDCClient
, which provides the interface for main operations.
from idc_index import IDCClient
client = IDCClient.client()
You can use IDC Portal to
browse collections, cases, studies and series, copy their identifiers and
download the corresponding files using idc-index
helper functions.
You can try this out with the rider_pilot
collection, which is just 10.5 GB in
size:
client.download_from_selection(collection_id="rider_pilot", downloadDir=".")
... or run queries against the "mini" index of Imaging Data Commons data, and download images that match your selection criteria! The following will select all Magnetic Resonance (MR) series, and will download the first 10.
from idc_index import index
client = index.IDCClient()
query = """
SELECT
SeriesInstanceUID
FROM
index
WHERE
Modality = 'MR'
"""
selection_df = client.sql_query(query)
client.download_from_selection(
seriesInstanceUID=list(selection_df["SeriesInstanceUID"].values[:10]),
downloadDir=".",
)
Please check out
this tutorial notebook
for the introduction into using idc-index
.
- Imaging Data Commons Portal can be used to explore the content of IDC from the web browser
- s5cmd is a highly efficient, open source, multi-platform S3 client that we use for downloading IDC data, which is hosted in public AWS and GCS buckets. Distributed on PyPI as s5cmd.
- SlicerIDCBrowser 3D
Slicer extension that relies on
idc-index
for search and download of IDC data
This software is maintained by the IDC team, which has been funded in whole or in part with Federal funds from the NCI, NIH, under task order no. HHSN26110071 under contract no. HHSN261201500003l.
If this package helped your research, we would appreciate if you could cite IDC paper below.
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