|
Subcategory | Related works | Year | Technique | Filter | Database | Evaluation metric |
|
USML | [148] | 2012 | Clustering | 2-D median | MIAS | 90.0% sensitivity and 78.0% specificity |
USML | [140] | 2012 | Microcalcification clusters | | BNHMJ | 91.4% segmentation accuracy, false positive 96.5% |
USML | [142] | 2013 | FCM clustering | Morphological | MIAS | |
USML | [138] | 2013 | Microcalcification clusters | | DDSM | 93.2% positive rate and 0.73 false positive |
USML | [147] | 2014 | -means | median | MIAS | 94.4% sensitivity |
USML | [145] | 2015 | Fuzzy -means | | MIAS | 83.3% for class 1, 75.0% class 2, and 80.0% class 3 accuracy |
USML | [149] | 2017 | FCM clustering | | MIAS | 86.2% sensitivity, 96.4% specificity, and 94.6% accuracy |
USML | [139] | 2018 | MC clusters | Morphological | DDSM and MIAS | 94.48% classification accuracy for DDSM and 100.0% for MIAS |
USML | [136] | 2018 | Fuzzy -means clustering | | MIAS | 98.82% detection |
USML | [137] | 2018 | -means clustering | | MIAS | 98.1% accuracy |
USML | [141] | 2018 | Classic and fuzzy morphology | Gaussian | MIAS | 0.86 Dice, 66.0% recall and 20% precision |
USML | [144] | 2018 | -means | LoG | MIAS and PHP | 95.0% accuracy PHP and 94.0% MIAS |
USML | [143] | 2018 | | Morphological | DDSM and MIAS | 98.0% accuracy for MIAS and 97.0% for DDSM accuracy |
USML | [135] | 2018 | Hierarchical -means clustering | | DDSM | 38.8% accuracy and 61.1% testing error |
USML | [146] | 2018 | MC clusters | Morphological | DDSM | 96.57% sensitivity and 94.25% accuracy |
|
SML | [155] | 2011 | MLP | | DDSM | 68.2% sensitivity and 8.7% false positive per image |
SML | [156] | 2012 | ELM | | MIAS | 81.10% of accuracy |
SML | [150] | 2015 | Structure SVM | | DDSM and INbreast | 87.0% Dice |
SML | [152] | 2015 | SSVM and CRF | | DDSM and INbreast | 93.0% accuracy using CRF and 95.0% accuracy using SVM |
SML | [153] | 2015 | SVM | Median filter | SSPS | 96.0% correlation |
SML | [151] | 2016 | GGD and Bayesian back propagation | | MIAS | 97.08% detection for GGD and 97.0% for Bayesian |
SML | [154] | 2017 | CRF and SSVM | | DDSM and INbreast | 10.0% loss |
|