Table 4.
Summary of convolutional neural network–based methods for breast mass classification.
| Author | Method | Dataset/number | Task | Performance metric/s (value/s) | Code availability |
| Levy and Jain [97] | AlexNet and GoogleNet (transfer learning) | Public, DDSMa dataset/1820 images (multiview) | Breast mass classification | Accuracy (0.924), precision (0.924), and recall (0.934) | —b |
| Samala et al [98] | Multistage fine-tuned CNNc (transfer learning) | Private+public, University of Michigan and DDSM/4039 ROIsd (multiview) | Classification performance on varying sample sizes | AUCe (0.91) | [108] |
| Jadoon et al [99] | CNN- Discrete wavelet and CNN-curvelet transform | Public, image retrieval in medical applications dataset/2796 ROI patches | Classification | Accuracy (81.83 and 83.74) and receiver operating characteristic curve (0.831 and 0.836) for both methods | — |
| Huynh et al [100] | CNN (transfer learning) | Private, University of Chicago/219 images (multiview) | Classification of benign and malignant tumor | AUC (0.86) | — |
| Domingues and Cardoso [101] | Autoencoder | Public, INbreast/116 ROIs | Classification of mass vs normal | Accuracy (0.99) | [109] |
| Wu et al [102] | GANf and ResNet50 | Public, DDSM dataset/10,480 images (multiview) | Detection and classification of benign and malignant calcifications and masses | AUC (0.896) | [110] |
| Sarah et al [103] | CNN (transfer learning) | Public, Full-field digital mammography and DDSM/14,860 images (multiview) | Classification | AUC (0.91) | — |
| Wang et al [104] | CNN and long short-term memory | Public, Breast Cancer Digital Repository (BCDR-F03)/763 images (multiview) | Classification of breast masses using contextual information | AUC (0.89) | — |
| Shams et al [105] | CNN and GAN | Public, INbreast and DDSM (multiview) | Classification | AUC (0.925) | — |
| Gastounioti et al [106] | Texture feature+CNN | Private/106 cases (mediolateral oblique view only) | Classification | AUC (0.9) | — |
| Dhungel et al [107] | Multi-ResNet | Public, INbreast (multiview) | Classification | AUC (0.8) | — |
aDDSM: Digital Database for Screening Mammography.
bNot available.
cCNN: convolutional neural network.
dROIs: region of interest.
eAUC: area under the curve.
fGAN: generative adversarial network.