Region growing segmentation using de-noising algorithm for medical ultrasound images

Harmeet Saini, V. Sahni
{"title":"Region growing segmentation using de-noising algorithm for medical ultrasound images","authors":"Harmeet Saini, V. Sahni","doi":"10.1109/CIACT.2017.7977313","DOIUrl":null,"url":null,"abstract":"Ultrasound pictures are hard to segment because of nearness of speckle noise and the limits of irregular areas. Additionally these are hard to perceive because of resemblance. It's quite difficult to get the desired result from the ultrasound images without improving their quality. Ultrasound images are usually in poor quality. In this paper, a technique to improve the quality of image using region growing segmentation and some other algorithm of image enhancement, de-noising etc. is presented. At the end of processing, the image is enhanced with clear boundaries of region of interest.","PeriodicalId":218079,"journal":{"name":"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIACT.2017.7977313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Ultrasound pictures are hard to segment because of nearness of speckle noise and the limits of irregular areas. Additionally these are hard to perceive because of resemblance. It's quite difficult to get the desired result from the ultrasound images without improving their quality. Ultrasound images are usually in poor quality. In this paper, a technique to improve the quality of image using region growing segmentation and some other algorithm of image enhancement, de-noising etc. is presented. At the end of processing, the image is enhanced with clear boundaries of region of interest.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于去噪算法的医学超声图像区域增长分割
超声图像由于散斑噪声的接近和不规则区域的限制而难以分割。此外,这些是很难察觉的,因为相似。如果不提高超声图像的质量,很难得到理想的结果。超声图像的质量通常很差。本文提出了一种利用区域增长分割和其他图像增强、去噪等算法来提高图像质量的方法。在处理结束时,图像被增强为清晰的感兴趣区域边界。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Smart solar tracking system for optimal power generation SVM with Gaussian kernel-based image spam detection on textual features Comparison between LDA & NMF for event-detection from large text stream data Research on the wisdom education platform of cloud computing architecture Robust TS fuzzy controller for helicopter via parallel distributed compensation
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1