Table 1 Datasets used in the experiments
From: Predictive performance of radiomic models based on features extracted from pretrained deep networks
Dataset | Modality (weighting) | N | In-plane resolution | Slice thickness | Source |
|---|---|---|---|---|---|
C4KC-KiTS | CT | 203 | 0.8 (0.4–1.0) | 3.0 (1.0–5.0) | TCIA [14] |
CRLM | CT | 76 | 0.7 (0.6–0.9) | 5.0 (1.0–8.0) | WORC [12] |
Desmoid | MR (T1) | 195 | 0.7 (0.2–1.8) | 5.0 (1.0–10.0) | WORC [12] |
GIST | CT | 244 | 0.8 (0.6–1.0) | 3.0 (0.6–6.0) | WORC [12] |
HN | CT | 134 | 1.0 (1.0–1.1) | 3.0 (1.5–3.0) | TCIA [7] |
ISPY-1 | MR (DCE) | 157 | 0.8 (0.4–1.2) | 2.1 (1.5–3.4) | TCIA [15] |
Lipo | MR (T1) | 113 | 0.7 (0.2–1.4) | 5.5 (1.0–9.1) | WORC [12] |
Liver | MR (T2) | 186 | 0.8 (0.6–1.6) | 7.7 (1.0–11.0) | WORC [12] |
Melanoma | CT | 97 | 0.7 (0.5–1.0) | 1.2 (0.6–2.0) | WORC [12] |
TCGA-GBM | MR (T1) | 53 | 0.8 (0.4–1.0) | 5.0 (1.0–5.5) | TCIA [16] |