الملخص
Breast image classification requires local detail and global tissue context, yet these cues can weaken as representations deepen. We present M3D-Net, a mammography encoder that hierarchically coordinates multi-scale coordinate attention, bounded dynamic feature reuse, and differential attention through resolution-aware operator placement. Within-stage retrieval preserves access to earlier features, coordinate-aware aggregation integrates local and global context, and differential attention operates at coarse resolutions. We evaluate image-only classification on AISSLab mammography and an adapted image--clinical model on BrEaST ultrasound. Against EdgeNeXt, RepViT, and TransXNet, the proposed implementations achieve the highest recorded validation accuracy and late-training accuracy, with the lowest endpoint cross-entropy loss. Validation accuracies reach 97.78\% and 80.39\%, respectively. These results support further evaluation of hierarchical coordination across breast imaging settings; repeated-seed, component-controlled, and independent evaluations remain necessary.
الكلمات المفتاحية
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Yu, Z., Li, X. H., Gao, J., Wang, B., & Li, X. (2026). M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification. https://omanscience.com/ar/articles/m3d-net-hierarchical-coordination-of-spatial-context-feature-reuse-and-differential-attention-for-mammography-classification
MLA 9
Yu, Zheng, et al. "M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification." https://omanscience.com/ar/articles/m3d-net-hierarchical-coordination-of-spatial-context-feature-reuse-and-differential-attention-for-mammography-classification.
شيكاغو (المؤلف–التاريخ)
Yu, Zheng, Xin-Hang Li, Jiabao Gao, Boyang Wang, and Xiang Li. 2026. "M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification." https://omanscience.com/ar/articles/m3d-net-hierarchical-coordination-of-spatial-context-feature-reuse-and-differential-attention-for-mammography-classification.
هارفارد
Yu, Z., Li, X. H., Gao, J., Wang, B. and Li, X. (2026) 'M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification', Available at: https://omanscience.com/ar/articles/m3d-net-hierarchical-coordination-of-spatial-context-feature-reuse-and-differential-attention-for-mammography-classification.
فانكوفر
Yu Z, Li XH, Gao J, Wang B, Li X. M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification. https://omanscience.com/ar/articles/m3d-net-hierarchical-coordination-of-spatial-context-feature-reuse-and-differential-attention-for-mammography-classification
IEEE
Z. Yu, X. H. Li, J. Gao, B. Wang, and X. Li, "M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification," https://omanscience.com/ar/articles/m3d-net-hierarchical-coordination-of-spatial-context-feature-reuse-and-differential-attention-for-mammography-classification.