Automatic Segmentation of Polyps in Endoscopic Image Using Level-Set Formulation

Soumayan Dutta, Pradipta Sasmal, M. Bhuyan, Y. Iwahori
{"title":"Automatic Segmentation of Polyps in Endoscopic Image Using Level-Set Formulation","authors":"Soumayan Dutta, Pradipta Sasmal, M. Bhuyan, Y. Iwahori","doi":"10.1109/WISPNET.2018.8538615","DOIUrl":null,"url":null,"abstract":"Automatic segmentation of colorectal polyps from endoscopic images forms an interesting challenge in computer vision. The method proposed in this paper intends to segment colorectal polyp (abnormal) regions from normal regions from a given endoscopic image. Due to lack of any regular texture patterns in this kind of images and apparent visual similarity in background and foreground pixels, conventional texture feature extraction and classification methods do not always yield good results. Hence, active contour based method has been explored to automatically segment out probable abnormal region(s). Our aim is to automatically detect the probable polyp region(s) and then verify the results with respect to the ground truth. Due to lack of very definitive edge criteria along the boundaries of a polyp, we used “active contour without edges” instead of classical active contour.","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"36 9 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISPNET.2018.8538615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Automatic segmentation of colorectal polyps from endoscopic images forms an interesting challenge in computer vision. The method proposed in this paper intends to segment colorectal polyp (abnormal) regions from normal regions from a given endoscopic image. Due to lack of any regular texture patterns in this kind of images and apparent visual similarity in background and foreground pixels, conventional texture feature extraction and classification methods do not always yield good results. Hence, active contour based method has been explored to automatically segment out probable abnormal region(s). Our aim is to automatically detect the probable polyp region(s) and then verify the results with respect to the ground truth. Due to lack of very definitive edge criteria along the boundaries of a polyp, we used “active contour without edges” instead of classical active contour.
基于水平集的内镜图像息肉自动分割
从内镜图像中自动分割结肠直肠息肉是计算机视觉领域的一个有趣的挑战。本文提出的方法旨在从给定的内镜图像中分割结肠直肠息肉(异常)区域和正常区域。由于这类图像缺乏任何规则的纹理模式,背景和前景像素具有明显的视觉相似性,传统的纹理特征提取和分类方法往往效果不佳。为此,探索了基于活动轮廓线的自动分割可能异常区域的方法。我们的目标是自动检测可能的息肉区域,然后根据真实情况验证结果。由于缺乏非常明确的沿息肉边界的边缘标准,我们使用“无边缘的活动轮廓”代替经典的活动轮廓。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信