M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification

arXiv:2609.27523 · cs.CV, cs.LG · Submitted 2026-09-23 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/YuZhengYYDS/M3D-Net

Terminology

• Accuracy — 10× in this paper · explained in 1 episode
• Adaptation — 7× in this paper · explained in 1 episode
• Transformer — 7× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Conditional Positional Encoding — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks
• Attend what matters: Leveraging vision foundational models for breast cancer classification using mammograms

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