{"title":"用于结肠NBI内镜诊断支持的两阶段病变识别系统","authors":"Yongfei Wu, Daisuke Katayama, Tetsushi Koide, Toru Tamaki, Shigeto Yoshida, Shin Morimoto, Yuki Okamoto, S. Oka, Shinji Tanaka","doi":"10.1109/ITC-CSCC58803.2023.10212618","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a two-stage Computer-Aided Diagnosis (CAD) system for lesion recognition using detecting and classifying method based on deep learning architecture. The proposed CAD system can presents quantitative inference results from images token by colorectal Narrow Band Imaging (NBI) endoscopy to clinical doctors, which aims to reduce the variation and burden of diagnoses due to the experience of diagnosing doctors. As a result, for our test dataset, the current accuracy has reached 67% for magnified images.","PeriodicalId":220939,"journal":{"name":"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Two-Stage Lesion Recognition System for Diagnostic Support in Colon NBI Endoscopy\",\"authors\":\"Yongfei Wu, Daisuke Katayama, Tetsushi Koide, Toru Tamaki, Shigeto Yoshida, Shin Morimoto, Yuki Okamoto, S. Oka, Shinji Tanaka\",\"doi\":\"10.1109/ITC-CSCC58803.2023.10212618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a two-stage Computer-Aided Diagnosis (CAD) system for lesion recognition using detecting and classifying method based on deep learning architecture. The proposed CAD system can presents quantitative inference results from images token by colorectal Narrow Band Imaging (NBI) endoscopy to clinical doctors, which aims to reduce the variation and burden of diagnoses due to the experience of diagnosing doctors. As a result, for our test dataset, the current accuracy has reached 67% for magnified images.\",\"PeriodicalId\":220939,\"journal\":{\"name\":\"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITC-CSCC58803.2023.10212618\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITC-CSCC58803.2023.10212618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Two-Stage Lesion Recognition System for Diagnostic Support in Colon NBI Endoscopy
In this paper, we propose a two-stage Computer-Aided Diagnosis (CAD) system for lesion recognition using detecting and classifying method based on deep learning architecture. The proposed CAD system can presents quantitative inference results from images token by colorectal Narrow Band Imaging (NBI) endoscopy to clinical doctors, which aims to reduce the variation and burden of diagnoses due to the experience of diagnosing doctors. As a result, for our test dataset, the current accuracy has reached 67% for magnified images.
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