Ricardo
(2022-01-22 16:40):
#paper doi:https://doi.org/10.1016/j.neuroimage.2014.11.042 DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions. 2015年发表在neuroimage。介绍一篇和我目前做的工作比较相关的一篇paper。弥散磁共振成像(dMRI)可以定量地测量活体脑白质结构,是一种研究人脑白质微观结构特性或脑区间通路的一种重要的神经成像技术。在过去的几十年里,由于回波平面成像(EPI)技术可以很快地对全脑进行成像,所以大部分dMRI都是基于EPI序列进行采集的。但是由于不同人脑组织(如骨、脑脊液)的磁化率不同,因此使得MRI腔体中的磁场呈现一定程度的不均匀性,从而影响磁共振图像体素的空间编码,并导致解剖结构上的畸变和磁共振信号的畸变。这种畸变也被称为磁敏感伪影(susceptibility artifact,SA)。03年的时候Oxford大学有一个大佬开发了用于消除这种畸变的影像算法(Topup),并且广泛应用于各种大型神经影像数据项目中。不过这篇文章的作者认为,topup算法仅仅使用了b0图像对不均匀场进行估计,并没有充分利用结构像和弥散加权图像的信息对不均匀场的求解空间进行约束。这篇工作从以下几个方面对SA矫正算法进行改进:1.使用一种对称的(symmetric)、微分同胚的(diffeomorphic)以及基于变换的速度场的配准模型构建优化模型;2.作者不仅仅使用一个constant的不均匀场,而是两个相互依赖的不均匀场来矫正成对图像间的扭曲;3.引入T2加权结构像引导图像畸变的恢复;4.引入弥散加权图像约束模型求解空间。结果表明DR-BUDDI算法在多个指标上均比目前广泛使用Topup算法表现更佳。
我最近做的工作也是类似的工作,在多个数据集上进行了验证测试,等文章发表出来我再做一些介绍。
DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions
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Abstract:
We propose an echo planar imaging (EPI) distortion correction method (DR-BUDDI), specialized for diffusion MRI, which uses data acquired twice with reversed phase encoding directions, often referred to as blip-up blip-down acquisitions. DR-BUDDI can incorporate information from an undistorted structural MRI and also use diffusion-weighted images (DWI) to guide the registration, improving the quality of the registration in the presence of large deformations and in white matter regions. DR-BUDDI does not require the transformations for correcting blip-up and blip-down images to be the exact inverse of each other. Imposing the theoretical "blip-up blip-down distortion symmetry" may not be appropriate in the presence of common clinical scanning artifacts such as motion, ghosting, Gibbs ringing, vibrations, and low signal-to-noise. The performance of DR-BUDDI is evaluated with several data sets and compared to other existing blip-up blip-down correction approaches. The proposed method is robust and generally outperforms existing approaches. The inclusion of the DWIs in the correction process proves to be important to obtain a reliable correction of distortions in the brain stem. Methods that do not use DWIs may produce a visually appealing correction of the non-diffusion weighted images, but the directionally encoded color maps computed from the tensor reveal an abnormal anatomy of the white matter pathways.
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