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A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms
Image augmentation techniques have been widely investigated to improve the performance of deep learning (DL) algorithms on mammography classification tasks.
A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms
The experimental results demonstrate that the proposed approach outperforms the single-view classification approach on two benchmark datasets by huge F1-score margins (+5% on the internal dataset and +10% on the DDSM dataset).
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