Holli-Helenius et al51
|
27 |
T1-weighted, nonfat-saturated DCE-MRI |
GLCM texture features |
Sum entropy and sum variance differentiate between luminal A and luminal B subtypes (AUC = 0.88) |
Waugh et al50
|
200 |
DCE-MRI |
GLCM texture features |
Entropy significantly different between ILC and IDC cancers |
Sutton et al52
|
178 |
T1-weighted fat suppressed MRI |
Gray-level histogram, GLCM texture features |
Features quantifying heterogeneity were able to classify between molecular subtypes |
Wang et al32
|
84 |
DCE-MRI |
Gray-level histogram, GLCM texture features |
Adding texture features quantifying tumor microenvironment heterogeneity to model with features quantifying lesion heterogeneity improved classification performance to identify TNBC. |
Chen et al48
|
121 |
T1-weighted DCE-MRI |
GLCM texture features |
3D texture features showed better performance than 2D texture features when classifying breast lesions as benign or malignant |