Multi-Level Bidirectional Decoder Interaction for Uncertainty-Aware Breast Ultrasound Analysis

• URL: http://arxiv.org/abs/2603.01295v1
• Date: Sun, 01 Mar 2026 22:02:06 GMT
• Title: Multi-Level Bidirectional Decoder Interaction for Uncertainty-Aware Breast Ultrasound Analysis
• Abstract summary: Breast ultrasound interpretation requires simultaneous lesion segmentation and tissue classification.<n>We propose a multi-task framework addressing these limitations through multi-level decoder interaction and uncertainty-aware adaptive coordination.
• Score: 2.8218290601001854
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Breast ultrasound interpretation requires simultaneous lesion segmentation and tissue classification. However, conventional multi-task learning approaches suffer from task interference and rigid coordination strategies that fail to adapt to instance-specific prediction difficulty. We propose a multi-task framework addressing these limitations through multi-level decoder interaction and uncertainty-aware adaptive coordination. Task Interaction Modules operate at all decoder levels, establishing bidirectional segmentation-classification communication during spatial reconstruction through attention weighted pooling and multiplicative modulation. Unlike prior single-level or encoder-only approaches, this multi-level design captures scale specific task synergies across semantic-to-spatial scales, producing complementary task interaction streams. Uncertainty-Proxy Attention adaptively weights base versus enhanced features at each level using feature activation variance, enabling per-level and per-sample task balancing without heuristic tuning. To support instance-adaptive prediction, multi-scale context fusion captures morphological cues across varying lesion sizes. Evaluation on multiple publicly available breast ultrasound datasets demonstrates competitive performance, including 74.5% lesion IoU and 90.6% classification accuracy on BUSI dataset. Ablation studies confirm that multi-level task interaction provides significant performance gains, validating that decoder-level bidirectional communication is more effective than conventional encoder-only parameter sharing. The code is available at: https://github.com/C-loud-Nine/Uncertainty-Aware-Multi-Level-Decoder-Interaction.

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