Method for Lung Nodule Detection on CT Images Using Improved YOLOv5
To address the problem of poor detection results of lung nodules in CT images by YOLOv5 algorithm,an improved YOLOv5-based lung nodule detection method is proposed.The feature pyramid of the Neck part of the YOLOv5 network is im-proved to weighted bidirectional feature pyramid network.In the YOLOv5 network,the Backbone part adds an efficient channel attention mechanism and a coordinate attention mechanism.Experiments are conducted on the LIDC-IDRI dataset and the results show that the average detection accuracy id up to 80.2％,and the recall is up to 90.75％,so this method can effectively detect lung nodules.Compared with the YOLOv5 algorithm,the improved algorithm improves 7.7％in mAP and 5.5％in recall.
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