基于多尺度Harris角点SAM的鲁棒医学图像配准算法

Ying Ding, Jingtao Fan, Huamin Yang
{"title":"基于多尺度Harris角点SAM的鲁棒医学图像配准算法","authors":"Ying Ding, Jingtao Fan, Huamin Yang","doi":"10.1109/BMEI.2009.5302680","DOIUrl":null,"url":null,"abstract":"To make up for the lack of concern on spatial information in conventional mutual information based image registration framework, this paper designs a novel registration algorithm based on the SAM information of multi-scale Harris corners (CSAM for short). First, the multi-scale contour is extracted, and multi-scale Harris corner detector is added to acquire the estimated transform parameters; and then CSAM is regarded as Similarity Measure function, several optimized match points are obtained, the finally registration parameters are resolved by using least squares method. This algorithm realizes registration of medical images with noise and multiresolutions, further more, it only matches corners and doesn’t need optimal searching, so it has reduced calculate time and avoided local extremum. Experimental results on clinical CT and T1-weighted MR images demonstrate that, as compared with the conventional mutual information based method, the proposed method consistently completes much higher precision, faster speed and better robustness. Keywords-image registration; square root arithmetic mean divergence(SAM); Harris corner; multi-scale","PeriodicalId":6389,"journal":{"name":"2009 2nd International Conference on Biomedical Engineering and Informatics","volume":"77 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Robust Medical Image Registration Algorithm Based on the SAM of Multi-Scale Harris Corners\",\"authors\":\"Ying Ding, Jingtao Fan, Huamin Yang\",\"doi\":\"10.1109/BMEI.2009.5302680\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To make up for the lack of concern on spatial information in conventional mutual information based image registration framework, this paper designs a novel registration algorithm based on the SAM information of multi-scale Harris corners (CSAM for short). First, the multi-scale contour is extracted, and multi-scale Harris corner detector is added to acquire the estimated transform parameters; and then CSAM is regarded as Similarity Measure function, several optimized match points are obtained, the finally registration parameters are resolved by using least squares method. This algorithm realizes registration of medical images with noise and multiresolutions, further more, it only matches corners and doesn’t need optimal searching, so it has reduced calculate time and avoided local extremum. Experimental results on clinical CT and T1-weighted MR images demonstrate that, as compared with the conventional mutual information based method, the proposed method consistently completes much higher precision, faster speed and better robustness. Keywords-image registration; square root arithmetic mean divergence(SAM); Harris corner; multi-scale\",\"PeriodicalId\":6389,\"journal\":{\"name\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"volume\":\"77 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2009.5302680\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2009.5302680","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

针对传统基于互信息的图像配准框架对空间信息关注不足的问题,本文设计了一种基于多尺度Harris角点SAM信息的图像配准算法。首先提取多尺度轮廓,加入多尺度Harris角点检测器获取估计的变换参数;然后将CSAM作为相似度度量函数,得到多个优化匹配点,最后利用最小二乘法求解配准参数。该算法实现了具有噪声和多分辨率的医学图像配准,并且只匹配角点,不需要最优搜索,减少了计算时间,避免了局部极值。在临床CT和t1加权MR图像上的实验结果表明,与传统的基于互信息的方法相比,本文方法具有更高的精度、更快的速度和更好的鲁棒性。Keywords-image登记;平方根算术平均散度;哈里斯角落;多尺度
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Robust Medical Image Registration Algorithm Based on the SAM of Multi-Scale Harris Corners
To make up for the lack of concern on spatial information in conventional mutual information based image registration framework, this paper designs a novel registration algorithm based on the SAM information of multi-scale Harris corners (CSAM for short). First, the multi-scale contour is extracted, and multi-scale Harris corner detector is added to acquire the estimated transform parameters; and then CSAM is regarded as Similarity Measure function, several optimized match points are obtained, the finally registration parameters are resolved by using least squares method. This algorithm realizes registration of medical images with noise and multiresolutions, further more, it only matches corners and doesn’t need optimal searching, so it has reduced calculate time and avoided local extremum. Experimental results on clinical CT and T1-weighted MR images demonstrate that, as compared with the conventional mutual information based method, the proposed method consistently completes much higher precision, faster speed and better robustness. Keywords-image registration; square root arithmetic mean divergence(SAM); Harris corner; multi-scale
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
期刊最新文献
A Novel Approach for Blood Vessel Edge Detection in Retinal Images Skin Response During Irradiation by Intense Pulsed Light Based on Optical Imaging Technology and Histology Physical Properties of LYSO Scintillator for NN-PET Detectors A High Security Framework for SMS An Efficient Antenna Selection Algorithm for MIMO Systems
×
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