PDE-Based Parallel Deformable Registration on a Dual Core Cluster

Jiang Murong, Lin Yongyan, Zhou Jun, Chen Lin, Chang Baoji
{"title":"PDE-Based Parallel Deformable Registration on a Dual Core Cluster","authors":"Jiang Murong, Lin Yongyan, Zhou Jun, Chen Lin, Chang Baoji","doi":"10.1109/ICINIS.2008.131","DOIUrl":null,"url":null,"abstract":"Most numerical approaches for image registration with PDE method are based on the computing over the pixel matrices. As the image size increases, more time consuming is needed. Then, one of the most efficient solving methods is parallel computing. In this paper, we discuss the parallel deformable registration computing carried on the cluster. First, we present the diffusion PDE model to describe the registration problem, detail the sequential adaptive parameter computing method for searching the weight parameter correspond to the local degrees of variability in the match, then perform the parallel implementation on a 4 nodes cluster disposed by WCCS. Some experimental results show that this method can produce the large size parallel image registration and reduce the computation complexity.","PeriodicalId":185739,"journal":{"name":"2008 First International Conference on Intelligent Networks and Intelligent Systems","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2008.131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Most numerical approaches for image registration with PDE method are based on the computing over the pixel matrices. As the image size increases, more time consuming is needed. Then, one of the most efficient solving methods is parallel computing. In this paper, we discuss the parallel deformable registration computing carried on the cluster. First, we present the diffusion PDE model to describe the registration problem, detail the sequential adaptive parameter computing method for searching the weight parameter correspond to the local degrees of variability in the match, then perform the parallel implementation on a 4 nodes cluster disposed by WCCS. Some experimental results show that this method can produce the large size parallel image registration and reduce the computation complexity.
基于pde的双核簇并行可变形配准
大多数用PDE方法进行图像配准的数值方法都是基于像素矩阵的计算。随着图像大小的增加,需要花费更多的时间。其中,最有效的求解方法之一就是并行计算。本文讨论了在集群上进行的并行可变形配准计算。首先,提出了描述配准问题的扩散PDE模型,详细介绍了序列自适应参数计算方法,用于搜索匹配中局部变异度对应的权重参数,然后在WCCS配置的4节点集群上进行并行实现。实验结果表明,该方法可以实现大尺寸的并行图像配准,降低了计算复杂度。
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