Table 3.
Detection of breast lesions in breast MRI using DL.
| DL technique | Evaluation results | Dataset | References |
|---|---|---|---|
| Model agnostic saliency | TPR = 80 FPs/image = 8 |
117 subjects DCE-MRI and T1W images |
[86] |
| U-net | Acc = 94.2 | 67 MR images T1W, T2W, DWI, and DCE-MRI | [87] |
| Patch-based analysis with ResNet50 backbone | AUC = 0.817 | 335 MR images of 17 different histological subtypes | [65] |
| Deep Q-network | Sn = 80 FPs/image = 3.2 |
117 DCE-MR and T1-weighted images | [63] |
| Unsupervised saliency analysis and CNN | Acc = 86 ± 2 AUC = 0.94 ± 0.01 |
193 DCE-MR images | [88] |
| Two-level U-net and dual-stream CNN | CPM = 64.29 | Training: 201 DCE-MR images Testing: 160 DCE-MR images |
[64] |