Whole Mammogram Classification
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Most implemented papers
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification
Inspired by the success of using deep convolutional features for natural image analysis and multi-instance learning (MIL) for labeling a set of instances/patches, we propose end-to-end trained deep multi-instance networks for mass classification based on whole mammogram without the aforementioned ROIs.
A Unified Mammogram Analysis Method via Hybrid Deep Supervision
In this work, we present a unified mammogram analysis framework for both whole-mammogram classification and segmentation.