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Application of Two Deep Learning Networks for Diagnosis of Breast Cancer on MRI: Automatic Detection Using Mask R-CNN Followed by Classification Using ResNet50

BI-RADS Reading of Non-Mass Lesions on DCE-MRI and Differential Diagnosis Performed by Radiomics and Deep Learning

Classification of Breast Cancer Molecular Subtypes on DCE-MRI Using Radiomics Analysis with Various Machine Learning Algorithm

Diagnosis of Breast Cancer Using Radiomics Models Built Based on DCE-MRI and Mammography Compared to BI-RADS Reading