Polyp segmentation method and device, computer equipment and storage medium

Abstract

The invention discloses a polyp segmentation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a to-be-segmented polyp image, carrying out the feature extraction of the polyp image through a Res2Net network, and obtaining a multi-layer feature map; performing refining processing on each layer of feature map by using a texture enhancement module, and then performing feature fusion on multiple layers of feature maps by using a cross-layer feature fusion module to obtain a target polyp segmentation rough prediction map; inputting each layer of feature map into a grouping supervision context module, and performing context combination on the target polyp segmentation rough prediction map and the multi-layer feature map through the grouping supervision context module; taking a context combination result as a final polyp segmentation prediction map so as to construct a polyp segmentation network; and performing segmentation processing on the polyp image by using the polyp segmentation network. According to the method, richer polyp features are extracted by considering information complementation between hierarchical feature maps and feature fusion under multiple views, so that the segmentation precision of the polyp image is improved.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a polyp segmentation method, device, computer equipment and storage medium. Background technique [0002] Colorectal cancer is the cancer with the third highest morbidity and the second highest death rate in the world, and has become one of the main killers threatening the safety of human life. Most colorectal cancers start as adenomatous polyps that, over time, transform from initially benign polyps to malignant tumors. Early screening of colorectal polyps can increase the survival rate of colorectal cancer to 90%, so early detection and removal of polyps is very important to curb the occurrence of colorectal cancer. In clinical work, endoscopy is helpful for doctors to visually observe the morphological characteristics of lesions, and is considered to be the gold standard for screening colorectal polyps. Accurate detection of colorectal polyps remains a chall...

AI Technical Summary

Problems solved by technology

However, the above methods only consider the context information of the feature map and ignore the information complementation and information transmission between the upper and lower feature maps, resulting in insufficient polyp features, which in turn leads to insufficient accuracy of polyp image segmentation.

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