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Table 1 Core statistics of the datasets, including clinical tasks and imaging modalities used

From: Addressing challenges in radiomics research: systematic review and repository of open-access cancer imaging datasets

Dataset name

Task

Task type

Imaging modality

LIDC-IDRI [20, 21]

Lung nodule classification

Binary classification

CT

LNDb [22, 23]

Lung nodule classification (conformant to LIDC-IDRI)

Multi-class classification

CT

NSCLC-Radiogenomics [24, 25]

Outcome prediction for non-small cell lung cancer

Survival analysis

CT, PET/CT

NSCLC-Radiomics [2]

Outcome prediction for non-small cell lung cancer

Survival analysis

CT

LUAD-CT-Survival [26, 27]

Classification of lung cancer patients into long/short survival

Binary classification

CT

RIDER-Lung-CT [2]

Repeatability of radiomics features for non-small cell lung cancer

Repeatability

CT

BraTS-2021 [28]

Classification of MGMT promoter methylation status in brain tumor

Classification

MRI

UCSF-PDGM [29]

Classification of MGMT promoter methylation and IDH mutation status, and outcome prediction in brain tumor

Classification, survival analysis

MRI

UPENN-GBM [30]

Outcome prediction for glioblastoma

Survival analysis

MRI

Meningioma-SEG-CLASS [31]

Meningioma grading (grade I vs. II)

Classification

MRI

LGG-1p19qDeletion [32]

Classification of 1p/19q co-deletion status of low-grade glioma

Classification

MRI

PI-CAI [33]

Detection of clinically significant prostate cancer

Classification

MRI

Prostate-MRI-US-Biopsy [34]

Detection of clinically significant prostate cancer

Classification

MRI

QIN-PROSTATE [35, 36]

Repeatability of radiomics features in patients with prostate cancer

Repeatability

MRI

Head-Neck-Radiomics-HN1 [2]

Outcome prediction for head and neck squamous cell carcinoma

Survival analysis

CT

HNSCC [37, 38]

Outcome prediction for head and neck squamous cell carcinoma

Survival analysis

CT

Head-Neck-PET-CT [39]

Outcome prediction for head and neck cancers

Survival analysis

PET/CT

OPC-Radiomics [40]

Outcome prediction for oropharynx cancer

survival analysis

CT

QIN-HEADNECK [41]

Repeatability of radiomics features for head and neck cancers before and after therapy

Repeatability

PET/CT

Colorectal-Liver-Metastases [42]

Pre-operative outcome prediction for colorectal liver metastases

Survival analysis

CT

HCC-TACE-Seg [43]

Outcome prediction for hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE)

Survival analysis

CT

C4KC-KiTS [44]

Kidney tumor segmentation and outcome prediction

Survival analysis

CT

Soft-tissue-Sarcoma [45]

Lung metastasis detection for sarcoma of the extremity

Binary classification

PET/CT, MRI

WORC-Desmoid [46, 47]

Classification of desmoid-type fibromatosis vs. extremity soft tissue sarcoma

Classification

MRI

WORC-Liver [46, 47]

Classification of malignant vs. benign primary solid liver tumor

Classification

MRI

WORC-CRLM [46, 47]

Classification of desmoplastic vs. replacement growth pattern in colorectal liver metastases

Classification

CT

WORC-Melanoma [46, 47]

Classification of BRAF-mutated vs. BRAF-wild in lung metastases of melanoma

Classification

CT

WORC-Lipo [46, 47]

Classification of well-differentiated liposarcoma vs. lipoma

Classification

MRI

WORC-GIST [46, 47]

Classification of gastrointestinal stromal tumor (GIST) vs. tumor resembling GIST

Classification

CT