Computer-aided diagnosis technology plays a very important role in colon polyp image segmentation.In view of the problems of colon polyp segmentation such as complicated edge detection and segmentation and low contrast between polyps and normal tissue,an improved segmentation model based on DeepLabv3+is proposed.This model uses the residual network as the backbone network to extract feature information,introduces a feature enhancement module to process low-level features,and adds a hybrid attention mechanism to capture key information for high-level features.The average intersection and union ratios of this model reached 82.19%and 90.40%respectively in experiments on the Kvasir-SEG data set and the CVC-ClinicDB data set.Experimental results show that the polyp segmentation effect of the improved model is better than that of the initial DeepLabv3+model,and there has been a certain improvement in the accuracy of polyp segmentation and edge segmentation.
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