Pyramid Model of Parallel Fusion Attention Mechanism Based on Channel-Coordinates and Its Application in Medical Images

The deep residual network model currently used in the detection of small targets such as pulmonary nodules have the problem of the disappearance of small target features caused by the effective fusion of multiple attention mechanisms and the increase in depth. Based on this, "Research on the Pyramid Model of Parallel Fusion Attention Mechanism Based on Channel-Coordinates and Its Application in Medical Images" is proposed. The model proposes an attention mechanism for channel-coordinate parallel fusion, which combines channel attention and temporal attention in parallel, and forms two expressions of an attention mechanism based on the different coordinate embedding timings of channel attention, solving multiple problems. Attention fusion mode and fusion timing issues; Based on this mechanism, combined with the pyramid feature fusion mode, a pyramid model of a parallel fusion attention mechanism based on channel-coordinates is proposed, and the feasibility of the model is theoretically demonstrated. An experiment was organized on RUNA16. The experimental results show that the two attention models proposed for this problem are feasible, have comparative advantages, and the algorithm is stable.