MedCore achieves 60% parameter and 58.4% FLOP reduction on MedSAM with Dice 0.9549 and preserved boundary metrics via dual-intervention pruning and a new boundary leverage principle.
Javier Sánchez, Gloria Fernández-Esparrach, Antonio M
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MedCAGD introduces a context-aware gated decoder with channel recalibration, gated skip fusion, and global context aggregation that outperforms baselines on 11 medical segmentation benchmarks while remaining computationally practical.
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MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
MedCore achieves 60% parameter and 58.4% FLOP reduction on MedSAM with Dice 0.9549 and preserved boundary metrics via dual-intervention pruning and a new boundary leverage principle.
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MedCAGD: Context-Aware Gated Decoder for Efficient Medical Image Segmentation
MedCAGD introduces a context-aware gated decoder with channel recalibration, gated skip fusion, and global context aggregation that outperforms baselines on 11 medical segmentation benchmarks while remaining computationally practical.