Medical image series segmentation using watershed transform and active contour model

F. Zhu, Jie Tian, Xiping Luo, Xingfei Ge
{"title":"Medical image series segmentation using watershed transform and active contour model","authors":"F. Zhu, Jie Tian, Xiping Luo, Xingfei Ge","doi":"10.1109/ICMLC.2002.1174506","DOIUrl":null,"url":null,"abstract":"In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorithm with the watershed method. Then the computer will segment the nearby slice using the modified active contour model. We introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the grayscale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows. that our algorithm can obtain the boundary of the desired object from a series of medical images reliably with only little user intervention.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"23 1","pages":"865-870 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2002.1174506","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorithm with the watershed method. Then the computer will segment the nearby slice using the modified active contour model. We introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the grayscale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows. that our algorithm can obtain the boundary of the desired object from a series of medical images reliably with only little user intervention.
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
基于分水岭变换和活动轮廓模型的医学图像序列分割
本文提出了一种基于活线算法和活动轮廓模型相结合的医学图像序列半自动分割算法。首先,将livewire算法与分水岭法相结合,对医学图像序列中的一个或多个切片进行精确分割。然后利用改进的活动轮廓模型对附近的切片进行分割。我们在活动轮廓模型的边界点上引入灰度模型,记录分割切片中目标的局部区域特征,并用灰度模型的似然值决定的能量代替传统活动轮廓模型的外部能量。此外,我们还引入了蛇的活动区域概念来提高分割精度。实验显示。该算法可以在用户干预较少的情况下,从一系列医学图像中可靠地获得目标的边界。
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
Plenary Talk: Digital-Twin Fluid Engineering APPLYING MACHINE LEARNING TECHNIQUES IN DETECTING BACTERIAL VAGINOSIS. OPTICAL COHERENCE TOMOGRAPHY HEART TUBE IMAGE DENOISING BASED ON CONTOURLET TRANSFORM. The multistage support vector machine Anti-control of chaos based on fuzzy neural networks inverse system method
×
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