3260 papers • 126 benchmarks • 313 datasets
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Experimental results on the INbreast dataset demonstrate the robustness of proposed deep networks compared to previous work using segmentation and detection annotations in the training.
A unified mammogram analysis framework for both whole-mammogram classification and segmentation is presented, designed based on a deep U-Net with residual connections, and equipped with the novel hybrid deep supervision (HDS) scheme for end-to-end multi-task learning.
Adding a benchmark result helps the community track progress.