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Deep-learning object detection is widely used, yet gastroscopic images often have weak contrast, making polyp sizes hard to separate from background. This study proposes an improved attentional feature fusion module to enhance contrast, suppress background interference, and emphasize effective target features across scales, improving detection accuracy and reducing missed or misdetected polyps on a gastric polyp dataset.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/gastric-polyp-detection-module-based-on-improved-attentional-feature-fusion/379055/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/gastric-polyp-detection-module-based-on-improved-attentional-feature-fusion/379055.png","ImageObject",300,407,{"name":92,"@type":93},"Sophia Brooks","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is timely gastric polyp detection important?","Question",{"text":112,"@type":113},"Gastric polyps are at high risk of becoming cancerous, and earlier detection helps reduce the incidence of gastric cancer by enabling timely treatment.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What problem do existing deep-learning detection methods face on gastroscopic images?",{"text":117,"@type":113},"Background-polyp contrast is weak, so it is difficult to distinguish polyps of different sizes from the background.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the proposed improved attentional feature fusion module help detection?",{"text":121,"@type":113},"It uses an attention module to leverage target location information, suppress background interference, highlight effective features, and then applies multi-scale feature fusion to produce more accurate attention weights, improving performance across polyp sizes.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},379055,1790305234,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962084925636,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","Xie etal. BioMedical Engineering OnLine (2023) 22:72  \n[https://doi.org/10.1186/s12938-023-01130-x](https://doi.org/10.1186/s12938-023-01130-x)  \nBioMedical Engineering OnLine  \nRESEARCH Open Access  \nGastric polyp detection module based on improved attentional feature fusion  \nYun Xie1, Yao Yu1*, Mingchao Liao 1 and Changyin Sun2  \n*Correspondence: [yuyao@ustb.edu.cn](yuyao@ustb.edu.cn)  \n1 School of Intelligence Science and technology, University of Science and Technology Beijing, Beijing, China  \n2 School of Artificial Intelligence, Anhui University, Anhui, China  \nAbstract  \nGastric cancer is a deadly disease and gastric polyps are at high risk of becoming cancerous. Therefore, the timely detection of gastric polyp is of great importance which can reduce the incidence of gastric cancer effectively. At present, the object detection method based on deep learning is widely used in medical images. However, as the contrast between the background and the polyps is not strong in gastroscopic image, it is difficult to distinguish various sizes of polyps from the background. In this paper, to improve the detection performance metrics of endoscopic gastric polyps, we propose an improved attentional feature fusion module. First, in order to enhance the contrast between the background and the polyps, we propose an attention module that enables the network to make full use of the target location information, it can suppress the interference of the background information and highlight the effective features. Therefore, on the basis of accurate positioning, it can focus on detecting whether the current location is the gastric polyp or background. Then, it is combined with our feature fusion module to form a new attentional feature fusion model that can mitigate the effects caused by semantic differences in the processing of feature fusion, using multi-scale fusion information to obtain more accurate attention weightsand improve the detection performance of polyps of different sizes. In this work, we conduct experiments on our own dataset of gastric polyps. Experimental results show that the proposed attentional feature fusion module is better than the common feature fusion module and can improve the situation where polyps are missed or misdetected.  \nKeywords: Gastric cancer, Deep learning, Polyp detection, Attention module, Feature fusion  \nBackground  \nAccording to the latest 2020 Global Cancer Statistics Report published by the 2021 IARC team in an authoritative journal owned by the American Institute on Cancer Society, gastric cancer ranks 5th on the global cancer spectrum and 4th on the cause of death spectrum. According to statistics, the global number about new cases of gastric cancer in 2020 is 1089103, and the number of deaths is 768793, accounting for 5.6 and 7.7 of the total number of cases and deaths, respectively [1]. Compared with the data of recent years, the incidence of gastric cancer is also increasing. And gastric polyps, as one of the  \n© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://](http://)[ ](http://)[creativecommons.org/licenses/by/4.0/](creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://crea","cbCaioDMc0hkyTIg","https://ap.wps.com/l/cbCaioDMc0hkyTIg","pdf",2580458,23,"English","# Abstract\n# Keywords\n# Background","[{\"question\":\"Why is timely gastric polyp detection important?\",\"answer\":\"Gastric polyps are at high risk of becoming cancerous, and earlier detection helps reduce the incidence of gastric cancer by enabling timely treatment.\"},{\"question\":\"What problem do existing deep-learning detection methods face on gastroscopic images?\",\"answer\":\"Background-polyp contrast is weak, so it is difficult to distinguish polyps of different sizes from the background.\"},{\"question\":\"How does the proposed improved attentional feature fusion module help detection?\",\"answer\":\"It uses an attention module to leverage target location information, suppress background interference, highlight effective features, and then applies multi-scale feature fusion to produce more accurate attention weights, improving performance across polyp sizes.\"}]","Gastric polyp detection module based on improved attentional feature fusion | PDF",1790233919,58]