Polyp segmentation algorithm with interference mining
Polyps are abnormal tissue growths on the surface of the body that have the potential to become diseased and require long-term observation and monitoring.Polyp segmentation is an important tool for monitoring and subsequent treatment.Existing studies have shown that the main difficulties in accurate polyp segmentation are the low contrast of polyp boundaries,the many variations in appearance,and the presence of multiple polyps.To address this,a polyp seg-mentation algorithm with interference mining is proposed and implemented on the basis of the focusing multi-scale problem,influenced by biological vision,which simulates the process of tar-get discovery by biological vision,locates potential targets from images with interference from a global perspective,and then enters into the recognition process in order to mine the target infor-mation to get a preliminary prediction map by focusing on the fuzzy region,and then the pre-liminary prediction results as an attention map to guide the shallow features,and finally,the re-fined feature map is fed into the multiscale residual inference module to produce the final pre-diction.
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