• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

4D shape registration for dynamic electrophysiological cardiac mapping.

作者信息

Wilson Kevin, Guiraudon Gerard, Jones Doug, Peters Terry M

机构信息

Biomedical Engineering Program, The University of Western Ontario, Canada.

出版信息

Med Image Comput Comput Assist Interv. 2006;9(Pt 2):520-7. doi: 10.1007/11866763_64.

DOI:10.1007/11866763_64
PMID:17354812
Abstract

Registration of 3D segmented cardiac images with tracked electrophysiological data has been previously investigated for use in cardiac mapping and navigation systems. However, dynamic cardiac 4D (3D + time) registration methods do not presently exist. This paper introduces two new 4D registration methods based on the popular iterative closest point (ICP) algorithm that may be applied to dynamic 3D shapes. The first method averages the transformations of the 3D ICP on each phase of the dynamic data, while the second finds the closest point pairs for the data in each phase and performs a least squares fit between all the pairs combined. Experimental results show these methods yield more accurate transformations compared to using a traditional 3D approach (4D errors: Translation 0.4mm, Rotation 0.45 degrees vs. 3D errors: Translation 1.2mm, Rotation 1.3 degrees) while also increasing capture range and success

摘要

相似文献

1
4D shape registration for dynamic electrophysiological cardiac mapping.
Med Image Comput Comput Assist Interv. 2006;9(Pt 2):520-7. doi: 10.1007/11866763_64.
2
Three-dimensional cardiac tissue image registration for analysis of in vivo electrical mapping.三维心脏组织图像配准用于分析体内电映射。
Ann Biomed Eng. 2011 Jan;39(1):235-48. doi: 10.1007/s10439-010-0163-7. Epub 2010 Sep 18.
3
Estimation of cardiac electrical propagation from medical image sequence.从医学图像序列估计心脏电传播。
Med Image Comput Comput Assist Interv. 2006;9(Pt 2):528-35. doi: 10.1007/11866763_65.
4
Experimental validation of a 4D elastic registration algorithm.一种四维弹性配准算法的实验验证
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:3961-6. doi: 10.1109/IEMBS.2008.4650077.
5
A novel incremental technique for ultrasound to CT bone surface registration using Unscented Kalman Filtering.一种使用无迹卡尔曼滤波的超声到CT骨表面配准的新型增量技术。
Med Image Comput Comput Assist Interv. 2005;8(Pt 2):197-204. doi: 10.1007/11566489_25.
6
On averaging multiview relations for 3D scan registration.基于多视图关系的 3D 扫描配准平均化。
IEEE Trans Image Process. 2014 Mar;23(3):1289-302. doi: 10.1109/TIP.2013.2246517. Epub 2013 Feb 11.
7
Towards real-time registration of 4D ultrasound images.迈向四维超声图像的实时配准。
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:404-7. doi: 10.1109/IEMBS.2006.260658.
8
Atlas construction for dynamic (4D) PET using diffeomorphic transformations.使用微分同胚变换构建用于动态(4D)正电子发射断层扫描(PET)的图谱。
Med Image Comput Comput Assist Interv. 2013;16(Pt 2):35-42. doi: 10.1007/978-3-642-40763-5_5.
9
Shape registration by simultaneously optimizing representation and transformation.通过同时优化表示和变换进行形状配准。
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):809-17. doi: 10.1007/978-3-540-75759-7_98.
10
Integrated four dimensional registration and segmentation of dynamic renal MR images.动态肾脏磁共振图像的四维综合配准与分割
Med Image Comput Comput Assist Interv. 2006;9(Pt 2):758-65. doi: 10.1007/11866763_93.