Datasetpublic

aicentreflip/tutorials-arkplus-cxr-classification

FLIP Ark+ tutorial chest X-ray classification splits Synthetic chest X-ray DICOMs (768×768, 8-bit RGB) with Yes/No lesion labels, backing the Ark+ NVFLARE tutorials in FLIP (Federated Learning Interoperability Platform). Folder Role DICOMs site1/ Site-1 training split — arkplus_fine_tuning 1910 site2/ Site-2 training split — arkplus_fine_tuning 1872 site1_holdoff/ Site-1 hold-out split — evaluation tutorials 478 site2_holdoff/ Site-2 hold-out split — evaluation… See the full description on the dataset page: https://huggingface.co/datasets/aicentreflip/tutorials-arkplus-cxr-classification.

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FLIP Ark+ tutorial chest X-ray classification splits

Synthetic chest X-ray DICOMs (768×768, 8-bit RGB) with Yes/No lesion labels, backing the Ark+ NVFLARE tutorials in FLIP (Federated Learning Interoperability Platform).

Folder	Role	DICOMs
`site1/`	Site-1 training split — `arkplus_fine_tuning`	1910
`site2/`	Site-2 training split — `arkplus_fine_tuning`	1872
`site1_holdoff/`	Site-1 hold-out split — evaluation tutorials	478
`site2_holdoff/`	Site-2 hold-out split — evaluation tutorials	468

Each folder contains:

—accession-resources/<accession_id>/<accession_id>.dcm — one DICOM per accession.
—sample_get_dataframe_response.csv — cohort dataframe: an accession_id column plus the lesion label columns (Effusion, Edema, Consolidation, Infiltration, Lung Nodule or Mass, Pneumothorax, Lungs in normal arrangement), valued Yes/No.

All images are fully synthetic (DeCaf balanced_synthetic_split) — no patient data.

Usage

The FLIP tutorials fetch these splits with huggingface_hub.snapshot_download and normalise them into a gitignored local layout. From the FLIP repo root:

bash

make -C fl-tutorials download-arkplus-finetuning-data   # site1 + site2  → data/arkplus/site{1,2}/
make -C fl-tutorials download-arkplus-eval-data         # hold-out splits → data/arkplus/site{1,2}_holdoff/

Licensed Apache-2.0.