内镜胶囊图像中结肠息肉的自动检测

International Symposium on Signals, Circuits and Systems ISSCS2013 Pub Date : 2013-07-11 DOI:10.1109/ISSCS.2013.6651196

E. David, Raluca Boia, Alexandru Malaescu, Mihai Carnu

{"title":"内镜胶囊图像中结肠息肉的自动检测","authors":"E. David, Raluca Boia, Alexandru Malaescu, Mihai Carnu","doi":"10.1109/ISSCS.2013.6651196","DOIUrl":null,"url":null,"abstract":"This paper presents a method of automatic detection of colon polyps in endoscopic capsule images. This approach uses color and geometrical analysis of the images and uses histogram of gradients features and multilayer perceptron neural networks for performing the detection at multiple scales. The detection performance is tested using a database of 30540 images, 540 of them containing at least one polyp.","PeriodicalId":260263,"journal":{"name":"International Symposium on Signals, Circuits and Systems ISSCS2013","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Automatic colon polyp detection in endoscopic capsule images\",\"authors\":\"E. David, Raluca Boia, Alexandru Malaescu, Mihai Carnu\",\"doi\":\"10.1109/ISSCS.2013.6651196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method of automatic detection of colon polyps in endoscopic capsule images. This approach uses color and geometrical analysis of the images and uses histogram of gradients features and multilayer perceptron neural networks for performing the detection at multiple scales. The detection performance is tested using a database of 30540 images, 540 of them containing at least one polyp.\",\"PeriodicalId\":260263,\"journal\":{\"name\":\"International Symposium on Signals, Circuits and Systems ISSCS2013\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Signals, Circuits and Systems ISSCS2013\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCS.2013.6651196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Signals, Circuits and Systems ISSCS2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2013.6651196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 11

摘要

本文提出了一种内镜下胶囊图像中结肠息肉的自动检测方法。该方法使用图像的颜色和几何分析，并使用梯度特征的直方图和多层感知器神经网络在多个尺度上执行检测。使用包含30540张图像的数据库测试检测性能，其中540张图像至少包含一个息肉。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Automatic colon polyp detection in endoscopic capsule images

This paper presents a method of automatic detection of colon polyps in endoscopic capsule images. This approach uses color and geometrical analysis of the images and uses histogram of gradients features and multilayer perceptron neural networks for performing the detection at multiple scales. The detection performance is tested using a database of 30540 images, 540 of them containing at least one polyp.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Symposium on Signals, Circuits and Systems ISSCS2013

自引率

0.00%

发文量