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使用迭代互相关校正扩散张量成像中涡流诱导的伪影。

Correction of eddy current-induced artefacts in diffusion tensor imaging using iterative cross-correlation.

作者信息

Bastin M E

机构信息

Department of Medical Physics and Medical Engineering, University of Edinburgh, Western General Hospital, UK.

出版信息

Magn Reson Imaging. 1999 Sep;17(7):1011-24. doi: 10.1016/s0730-725x(99)00026-0.

Abstract

Geometric distortions of echo-planar images produced by the strong eddy currents present in the diffusion tensor imaging experiment are a major confound to the accurate quantification of diffusion coefficients, and measures of diffusion anisotropy based upon them. Here we investigate how the method of iterative cross-correlation (ICC) of baseline and diffusion-weighted images (DWIs) originally proposed by Haselgrove and Moore (Magn. Reson. Med. 36:960-964; 1996) can be extended to correct high b-value DWIs, without the need for extrapolation of distortion parameters determined from low b-value images. Monte Carlo simulations of synthetic brain images show that the maximum value of the trace of the b-matrix, Tr(b), at which distorted DWIs can be accurately corrected by direct comparison with the undistorted baseline image is approximately 300 s mm(-2). Removal of the cerebrospinal fluid signal greatly extends this value of Tr(b) (up to approximately 2000 s mm(-2)), thereby allowing direct comparison of baseline and distorted images. The use of ICC distortion parameters determined from separate calibrations of water phantom images is also investigated, and found to be effective in correcting geometric distortions observed in the DWIs collected as part of a human volunteer diffusion tensor imaging study. This work suggests that distorted DWIs acquired at high values of b may be corrected using the ICC algorithm without collecting additional low b-value images, thus allowing simplified methods of measuring the apparent diffusion tensor D, based on collecting a small number of DWIs, to be implemented in quantitative patient examinations.

摘要

扩散张量成像实验中存在的强涡流所产生的回波平面图像几何畸变,是准确量化扩散系数以及基于这些系数的扩散各向异性测量的主要干扰因素。在此,我们研究了最初由哈塞尔格罗夫和摩尔提出的(《磁共振医学》36:960 - 964;1996年)基线图像与扩散加权图像(DWI)的迭代互相关(ICC)方法如何能够扩展以校正高b值DWI,而无需外推从低b值图像确定的畸变参数。对合成脑图像的蒙特卡罗模拟表明,通过与未畸变的基线图像直接比较能够准确校正畸变DWI时,b矩阵迹的最大值Tr(b)约为300 s mm⁻²。去除脑脊液信号可大大扩展这个Tr(b)值(高达约2000 s mm⁻²),从而允许对基线图像和畸变图像进行直接比较。我们还研究了使用从水模图像单独校准确定的ICC畸变参数,发现其在校正作为人类志愿者扩散张量成像研究一部分所采集的DWI中观察到的几何畸变方面是有效的。这项工作表明,在不采集额外低b值图像的情况下,使用ICC算法可以校正高b值时采集的畸变DWI,从而使得基于采集少量DWI的简化表观扩散张量D测量方法能够应用于定量患者检查中。

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