多静态自适应超声成像的无用户参数方法

Lin Du, Jian Li, P. Stoica
{"title":"多静态自适应超声成像的无用户参数方法","authors":"Lin Du, Jian Li, P. Stoica","doi":"10.1109/ISBI.2008.4541239","DOIUrl":null,"url":null,"abstract":"Delay-and-sum (DAS) beamforming is the standard technique for ultrasound imaging applications. Due to its data independent property, DAS may suffer from poorer resolution and worse interference suppression capability than the adaptive standard Capon beamformer (SCB). However, the performance of SCB is sensitive to the errors in the sample covariance matrix and the signal steering vector. Therefore, robust adaptive beamforming techniques are desirable. In this paper, we consider ultrasound imaging via applying a user parameter free robust adaptive beamformer, which uses a shrinkage-based general linear combination (QLC) algorithm to obtain an enhanced estimate of the array covariance matrix. We present several multistatic adaptive ultrasound imaging (MAUI) approaches based on QLC to achieve high resolution and good interference suppression capability. The performance of the proposed MAUI approaches is demonstrated via an experimental example.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"User parameter free approaches to multistatic adaptive ultrasound imaging\",\"authors\":\"Lin Du, Jian Li, P. Stoica\",\"doi\":\"10.1109/ISBI.2008.4541239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Delay-and-sum (DAS) beamforming is the standard technique for ultrasound imaging applications. Due to its data independent property, DAS may suffer from poorer resolution and worse interference suppression capability than the adaptive standard Capon beamformer (SCB). However, the performance of SCB is sensitive to the errors in the sample covariance matrix and the signal steering vector. Therefore, robust adaptive beamforming techniques are desirable. In this paper, we consider ultrasound imaging via applying a user parameter free robust adaptive beamformer, which uses a shrinkage-based general linear combination (QLC) algorithm to obtain an enhanced estimate of the array covariance matrix. We present several multistatic adaptive ultrasound imaging (MAUI) approaches based on QLC to achieve high resolution and good interference suppression capability. The performance of the proposed MAUI approaches is demonstrated via an experimental example.\",\"PeriodicalId\":184204,\"journal\":{\"name\":\"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBI.2008.4541239\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2008.4541239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

延迟和(DAS)波束形成是超声成像应用的标准技术。由于其数据无关性,与自适应标准Capon波束形成器(SCB)相比,DAS波束形成器的分辨率较低,干扰抑制能力较差。然而,SCB的性能对样本协方差矩阵和信号转向向量的误差很敏感。因此,需要稳健的自适应波束形成技术。在本文中,我们考虑通过应用用户参数自由鲁棒自适应波束形成器,该波束形成器使用基于收缩的一般线性组合(QLC)算法来获得阵列协方差矩阵的增强估计。提出了几种基于QLC的多静态自适应超声成像(MAUI)方法,以达到高分辨率和良好的抗干扰能力。通过一个实验实例验证了所提出的MAUI方法的性能。
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
User parameter free approaches to multistatic adaptive ultrasound imaging
Delay-and-sum (DAS) beamforming is the standard technique for ultrasound imaging applications. Due to its data independent property, DAS may suffer from poorer resolution and worse interference suppression capability than the adaptive standard Capon beamformer (SCB). However, the performance of SCB is sensitive to the errors in the sample covariance matrix and the signal steering vector. Therefore, robust adaptive beamforming techniques are desirable. In this paper, we consider ultrasound imaging via applying a user parameter free robust adaptive beamformer, which uses a shrinkage-based general linear combination (QLC) algorithm to obtain an enhanced estimate of the array covariance matrix. We present several multistatic adaptive ultrasound imaging (MAUI) approaches based on QLC to achieve high resolution and good interference suppression capability. The performance of the proposed MAUI approaches is demonstrated via an experimental example.
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
EEG source localization by multi-planar analytic sensing 3D general lesion segmentation in CT Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features Iterative nonlinear least squares algorithms for direct reconstruction of parametric images from dynamic PET Pathological image segmentation for neuroblastoma using the GPU
×
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