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Automatic Detection and Segmentation of Breast Cancer on MRI Using Mask R-CNN Trained on Non-Fat-Sat Images and Tested on Fat-Sat Images

Comparison of Breast Cancer Diagnostic Performance Using Radiomics Models Built Based on Features Extracted from DCE-MRI and Mammography

Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning with Consideration of Peri-Tumor Tissue

Diagnosis of Non-Mass-Like Enhancement Lesions on DCE-MRI by Using Quantitative Radiomics and Radiologists’ BI-RADS Reading

Differentiation of Breast Cancer Molecular Subtypes on DCE-MRI by Using Convolutional Neural Network with Transfer Learning