Objective To observe the value of dynamic attention aggregation network(DAANet)for automatic segmentation of anomalous origin of the left coronary artery from the pulmonary artery(ALCAPA)in CT angiography(CTA).Methods CTA data in 30 patients with ALCAPA syndrome were retrospectively enrolled.ALCAPA were segmented in CTA with DAANet based on residual edge feature(REF),pyramid dynamic attention(PDA)and dynamic global feature aggregation(DGFA)modules.Taken physician manual segmentation results as references,the results were compared with those of other networks.Results Compared with other networks,DAANet had better value for automatic segmentation of ALCAPA in CTA,which could show the details of irregular margins of left coronary artery with good continuity and high clarity,and the performance parameters were overall better.Conclusion DAANet had better performance for automatic segmentation of ALCAPA in CTA.

Objective To observe the value of dynamic attention aggregation network(DAANet)for automatic segmentation of anomalous origin of the left coronary artery from the pulmonary artery(ALCAPA)in CT angiography(CTA).Methods CTA data in 30 patients with ALCAPA syndrome were retrospectively enrolled.ALCAPA were segmented in CTA with DAANet based on residual edge feature(REF),pyramid dynamic attention(PDA)and dynamic global feature aggregation(DGFA)modules.Taken physician manual segmentation results as references,the results were compared with those of other networks.Results Compared with other networks,DAANet had better value for automatic segmentation of ALCAPA in CTA,which could show the details of irregular margins of left coronary artery with good continuity and high clarity,and the performance parameters were overall better.Conclusion DAANet had better performance for automatic segmentation of ALCAPA in CTA.