This repo gathers together the available open-source datasets suitable for radiomics research.
More information about each dataset and the extracted radiomics features as well as the labels can be accessed at https://radiomics.uk.
Dataset Name | Website | Task | Status |
---|---|---|---|
LIDC-IDRI | TCIA | binary classification | ✔️ |
LNDb | Zenodo | multiclass classification | ✔️ |
NSCLC-Radiogenomics | TCIA | survival analysis | ✔️ |
NSCLC-Radiomics | TCIA | survival analysis | ✔️ |
LUAD-CT-Survival | TCIA | binary classification | ✔️ |
RIDER-Lung-CT | TCIA | repeatability | ✔️ |
BraTS-2021 | Kaggle | binary classification | ✔️ |
UCSF-PDGM | TCIA | binary classification, survival analysis | ✔️ |
UPENN-GBM | TCIA | survival analysis | ✔️ |
Meningioma-SEG-CLASS | TCIA | binary classification | ✔️ |
LGG-1p19qDeletion | TCIA | binary classification | ✔️ |
PI-CAI | Grand Challenge | multiclass classification | ✔️ |
Prostate-MRI-US-Biopsy | TCIA | multiclass classification | ✔️ |
QIN-PROSTATE | TCIA | repeatability | ✔️ |
Head-Neck-Radiomics-HN1 | TCIA | survival analysis | ✔️ |
HNSCC | TCIA | survival analysis | ✔️ |
Head-Neck-PET-CT | TCIA | survival analysis | ✔️ |
OPC-Radiomics | TCIA | survival analysis | ✔️ |
QIN-HEADNECK | TCIA | repeatability | ✔️ |
Colorectal-Liver-Metastases | TCIA | survival analysis | ✔️ |
HCC-TACE-Seg | TCIA | survival analysis | ✔️ |
C4KC-KiTS | TCIA | survival analysis | ✔️ |
Soft-Tissue-Sarcoma | TCIA | binary classification | ✔️ |
WORC | GitHub | binary classification | ✔️ |
Each dataset adheres to the following structure, with minor variations:
<dataset_name>
├── raw
│ ├── dicom # depending on the format of the original dataset
│ └── tables
└── derived
├── nifti # converted to NIfTI format
└── tables