• 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

[An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

作者信息

Xu Yonghong, Gao Shangce, Hao Xiaofei

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2016 Apr;33(2):362-7.

PMID:29708674
Abstract

Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.

摘要

相似文献

1
[An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2016 Apr;33(2):362-7.
2
A comparative study of different level interpolations for improving spatial resolution in diffusion tensor imaging.不同水平插补法提高弥散张量成像空间分辨率的对比研究。
IEEE J Biomed Health Inform. 2014 Jul;18(4):1317-27. doi: 10.1109/JBHI.2014.2306937.
3
Spectrum-sine interpolation framework for DTI processing.用于 DTI 处理的频谱正弦内插框架。
Med Biol Eng Comput. 2022 Jan;60(1):279-295. doi: 10.1007/s11517-021-02471-2. Epub 2021 Nov 29.
4
Feature-based interpolation of diffusion tensor fields and application to human cardiac DT-MRI.基于特征的扩散张量场插值及其在人体心脏 DT-MRI 中的应用。
Med Image Anal. 2012 Feb;16(2):459-81. doi: 10.1016/j.media.2011.11.003. Epub 2011 Nov 17.
5
Geodesic-loxodromes for diffusion tensor interpolation and difference measurement.用于扩散张量插值和差异测量的测地线斜航线
Med Image Comput Comput Assist Interv. 2007;10(Pt 1):1-9. doi: 10.1007/978-3-540-75757-3_1.
6
Statistical group comparison of diffusion tensors via multivariate hypothesis testing.通过多变量假设检验对扩散张量进行统计组比较。
Magn Reson Med. 2007 Jun;57(6):1065-74. doi: 10.1002/mrm.21229.
7
The direct tensor solution and higher-order acquisition schemes for generalized diffusion tensor imaging.广义扩散张量成像的直接张量解和高阶采集方案。
J Magn Reson. 2010 Sep;206(1):9-19. doi: 10.1016/j.jmr.2010.05.016. Epub 2010 May 26.
8
A note on the validity of statistical bootstrapping for estimating the uncertainty of tensor parameters in diffusion tensor images.关于统计自展法在估计扩散张量图像中张量参数不确定性方面有效性的一则注释。
IEEE Trans Med Imaging. 2008 Oct;27(10):1506-14. doi: 10.1109/TMI.2008.926069.
9
Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.用于定量扩散张量磁共振成像分析的纤维束取向统计方法。
Med Image Anal. 2006 Oct;10(5):786-98. doi: 10.1016/j.media.2006.07.003. Epub 2006 Aug 22.
10
Diffusion weighted imaging for the differentiation of breast tumors: From apparent diffusion coefficient to high order diffusion tensor imaging.用于乳腺肿瘤鉴别诊断的扩散加权成像:从表观扩散系数到高阶扩散张量成像
J Magn Reson Imaging. 2016 May;43(5):1111-21. doi: 10.1002/jmri.25067. Epub 2015 Oct 22.