Dimitrios K. Iakovidis, D. Maroulis, S. Karkanis, A. Brokos
{"title":"A comparative study of texture features for the discrimination of gastric polyps in endoscopic video","authors":"Dimitrios K. Iakovidis, D. Maroulis, S. Karkanis, A. Brokos","doi":"10.1109/CBMS.2005.6","DOIUrl":null,"url":null,"abstract":"In this paper, we extend the application of four texture feature extraction methods proposed for the detection of colorectal lesions, into the discrimination of gastric polyps in endoscopic video. Support Vector Machines have been utilized for the texture classification task. The polyp discrimination performance of the surveyed schemes is compared by means of Receiver Operating Characteristics (ROC). The results advocate the feasibility of a computer-based system for polyp detection in video gastroscopy that exploits the textural characteristics of the gastric mucosa in conjunction with its color appearance.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"82","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2005.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 82
Abstract
In this paper, we extend the application of four texture feature extraction methods proposed for the detection of colorectal lesions, into the discrimination of gastric polyps in endoscopic video. Support Vector Machines have been utilized for the texture classification task. The polyp discrimination performance of the surveyed schemes is compared by means of Receiver Operating Characteristics (ROC). The results advocate the feasibility of a computer-based system for polyp detection in video gastroscopy that exploits the textural characteristics of the gastric mucosa in conjunction with its color appearance.