Review Article
Involvement of Machine Learning for Breast Cancer Image Classification: A Survey
Table 1
Available breast image database for biomedical investigation.
| Database | Number of images | Database size (GB) | Image capture technique | Image type | Total patients |
| MIAS | 322 | 2.3 | Mammogram | | 161 | DDSM | | | Mammogram | | 2620 | CBIS-DDSm | 4067 | 70.5 | MG | DICOM | 237 | ISPY1 | 386,528 | 76.2 | MR, SEG | | 237 | Breast-MRI-NACT-Pilot | 99,058 | 19.5 | MRI | | 64 | QIN-Breast | 100835 | 11.286 | PET/CT, MR | DICOM | 67 | Mouse-Mammary | 23487 | 8.6 | MRI | DICOM | 32 | TCGA-BRCA | 230167 | 88.1 | MR, MG | DICOM | 139 | QIN Breast DCE-MRI | 76328 | 15.8 | CT | DICOM | 10 | BREAST-DIAGNOSIS | 105050 | 60.8 | MRI/PET/CT | DICOM | 88 | RIDER Breast MRI | 1500 | .401 | MR | DICOM | 5 | BCDR | | | Mammogram | | 1734 | TCGA-BRCA | | 53.92 (TB) | Histopathology | | 1098 | BreakHis | 7909 | | Histopathology | | 82 | Inbreast | 419 | | Mammogram | | 115 |
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