结核菌通过区域生长的自动颜色分割:一种新方法

Chayadevi M L, Raju G T
{"title":"结核菌通过区域生长的自动颜色分割:一种新方法","authors":"Chayadevi M L, Raju G T","doi":"10.1109/ICADIWT.2014.6814682","DOIUrl":null,"url":null,"abstract":"Medical image analysis is very challenging due to idiosyncrasies of medical profession. Object recognition with data mining techniques has helped doctors in case of medical emergencies for the image analysis, pattern identification and treatment. Over 180 million people died and more than one third of the population is carrier of Mycobacterium Tuberculosis (TB) bacteria as per the WHO statistics [1-5]. Segmentation of TB from the stained background is very challenging due to noise and debris in the image. In this paper, an automated segmentation of tuberculosis bacterium using image processing techniques is presented. Colour segmentation with region growing watershed algorithm is proposed for the bacterial identification.","PeriodicalId":339627,"journal":{"name":"The Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Automated colour segmentation of Tuberculosis bacteria thru region growing: A novel approach\",\"authors\":\"Chayadevi M L, Raju G T\",\"doi\":\"10.1109/ICADIWT.2014.6814682\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical image analysis is very challenging due to idiosyncrasies of medical profession. Object recognition with data mining techniques has helped doctors in case of medical emergencies for the image analysis, pattern identification and treatment. Over 180 million people died and more than one third of the population is carrier of Mycobacterium Tuberculosis (TB) bacteria as per the WHO statistics [1-5]. Segmentation of TB from the stained background is very challenging due to noise and debris in the image. In this paper, an automated segmentation of tuberculosis bacterium using image processing techniques is presented. Colour segmentation with region growing watershed algorithm is proposed for the bacterial identification.\",\"PeriodicalId\":339627,\"journal\":{\"name\":\"The Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014)\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICADIWT.2014.6814682\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICADIWT.2014.6814682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

由于医学专业的特殊性,医学图像分析具有很大的挑战性。物体识别结合数据挖掘技术,帮助医生在医疗紧急情况下进行图像分析、模式识别和处理。据世界卫生组织统计,超过1.8亿人死亡,超过三分之一的人口是结核分枝杆菌(TB)细菌的携带者[1-5]。由于图像中的噪声和碎片,从染色背景中分割TB非常具有挑战性。本文提出了一种基于图像处理技术的结核菌自动分割方法。提出了一种基于区域增长分水岭的细菌识别颜色分割算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated colour segmentation of Tuberculosis bacteria thru region growing: A novel approach
Medical image analysis is very challenging due to idiosyncrasies of medical profession. Object recognition with data mining techniques has helped doctors in case of medical emergencies for the image analysis, pattern identification and treatment. Over 180 million people died and more than one third of the population is carrier of Mycobacterium Tuberculosis (TB) bacteria as per the WHO statistics [1-5]. Segmentation of TB from the stained background is very challenging due to noise and debris in the image. In this paper, an automated segmentation of tuberculosis bacterium using image processing techniques is presented. Colour segmentation with region growing watershed algorithm is proposed for the bacterial identification.
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
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