Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation
Computer Methods and Programs in Biomedicine(2022)
摘要
•A novel channel enhanced module to extract contextual relationships between different deep image feature tensor channels by convolutional bi-directional GRU.•Region-level attention to distinguish the contribution of different local regions and associated features to the global learning process.•Integrating spatial and position dependencies by a new position enhanced self-attention mechanism.•The generalization ability of our new model is validated using multiple different 3D image segmentation backbones.
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关键词
Multi-channel contextual relation learning,Convolutional bi-directional gated recurrent unit,Cross-channel region-level attention mechanism,Position enhanced self-attention mechanism,Lung tumor segmentation from CT volumes
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