imaging-data-commons

To download public cancer imaging data, you can query and retrieve DICOM series from the Imaging Data Commons (IDC) using the idc-index Python API and CLI. It enables filtering by cancer type, modality, and anatomy for AI training datasets.

Yes, you can filter IDC radiology and pathology datasets by modality, anatomy, cancer type, and collection. The idc-index package enables targeted metadata queries to discover specific public cancer imaging data for reproducibility and benchmarking.

You can visualize DICOM series in-browser by retrieving viewer URLs through the IDC viewer interfaces. The idc-index workflow provides access to these visualization endpoints, allowing direct in-browser viewing of queried public cancer imaging data.

Handling licensing and citation when downloading IDC imaging data is built into the idc-index workflow. It provides license awareness during DICOM series downloads and manifest generation, ensuring proper attribution for public cancer imaging datasets used in AI training.

The best way to get manifests for public cancer imaging datasets is using idc-index to query the IDC. It generates manifests with directory templates and license awareness, streamlining the download of DICOM series for reproducible AI training and benchmarking.