Volume 26, Issue 11

We propose a new white matter atlas creation method that learns a model of the common white matter structures present in a group of subjects. We demonstrate that our atlas creation method, which is based on group spectral clustering of tractography, discovers structures corresponding to expected white matter anatomy such as the corpus callosum, uncinate fasciculus, cingulum bundles, arcuate fasciculus, and corona radiata. The white matter clusters are augmented with expert anatomical labels and stored in a new type of atlas that we call a high-dimensional white matter atlas. We then show how to perform automatic segmentation of tractography from novel subjects by extending the spectral clustering solution, stored in the atlas, using the Nystrom method. We present results regarding the stability of our method and parameter choices. Finally we give results from an atlas creation and automatic segmentation experiment. We demonstrate that our automatic tractography segmentation identifies corresponding white matter regions across hemispheres and across subjects, enabling group comparison of white matter anatomy.

我们提出一种新的白质图谱创建方法，该方法学习一组受试者中常见白质结构的模型。我们证明了基于纤维束成像群体谱聚类的图谱创建方法能够发现与预期白质解剖结构相对应的结构，例如胼胝体、钩束、扣带束、弓状束和放射冠。白质簇附有专家解剖标签，并存储在我们称为高维白质图谱的新型图谱中。然后，我们展示了如何通过使用Nyström方法扩展图谱中存储的谱聚类解决方案，对新受试者的纤维束成像进行自动分割。我们给出了关于方法稳定性和参数选择的结果。最后，我们展示了图谱创建和自动分割实验的结果。我们证明，我们的自动纤维束成像分割能够识别跨半球和跨受试者的对应白质区域，从而实现白质解剖的组间比较。

Spatial normalization of diffusion tensor images plays a key role in voxel-based analysis of white matter (WM) group differences. Currently, it has been achieved using low-dimensional registration methods in the large majority of clinical studies. This paper aims to motivate the use of high-dimensional normalization approaches by generating evidence of their impact on the findings of such studies....

扩散张量图像的空间归一化在白质组差异的体素分析中起着关键作用。目前，在大多数临床研究中，它通过低维配准方法实现。本文旨在通过生成证据证明高维归一化方法对此类研究结果的影响，从而推动其使用。

Diffusion tensor magnetic resonance imaging (DT-MRI or DTI) is an imaging modality that is gaining importance in clinical applications. However, in a clinical environment, data have to be acquired rapidly, often at the expense of the image quality. This often results in DTI datasets that are not suitable for complex postprocessing like fiber tracking. We propose a new variational framework to impr...

扩散张量磁共振成像（DT-MRI或DTI）是一种在临床应用中日益重要的成像模态。然而，在临床环境中，数据必须快速采集，通常以牺牲图像质量为代价。这常常导致DTI数据集不适合进行复杂的后处理，如纤维追踪。我们提出了一种新的变分框架来改进...

Diffusion magnetic resonance imaging (MRI) is a relatively new imaging modality which is capable of measuring the diffusion of water molecules in biological systems noninvasively. The measurements from diffusion MRI provide unique clues for extracting orientation information of brain white matter fibers and can be potentially used to infer the brain connectivity in vivo using tractography techniqu...

扩散磁共振成像（MRI）是一种相对较新的成像模态，能够无创测量生物系统中水分子的扩散。扩散MRI的测量为提取脑白质纤维的定向信息提供了独特的线索，并可能通过纤维追踪技术推断体内脑连接性...

We propose a unified computational framework to build a statistical atlas of the cardiac fiber architecture from diffusion tensor magnetic resonance images (DT-MRIs). We apply this framework to a small database of nine ex vivo canine hearts. An average cardiac fiber architecture and a measure of its variability are computed using most recent advances in diffusion tensor statistics. This statistica...

我们提出了一个统一的计算框架，用于从扩散张量磁共振图像（DT-MRI）构建心脏纤维结构的统计图谱。我们将该框架应用于一个包含九只离体犬心脏的小型数据库。使用扩散张量统计学的最新进展，计算出平均心脏纤维结构及其变异性的度量。这种统计...

In this paper, a nonrigid coregistration algorithm based on a viscous fluid model is proposed that has been optimized for diffusion tensor images (DTI), in which image correspondence is measured by the mutual information criterion. Several coregistration strategies are introduced and evaluated both on simulated data and on brain intersubject DTI data. Two tensor reorientation methods have been inc...

本文提出了一种基于粘性流体模型的非刚性配准算法，该算法针对弥散张量图像（DTI）进行了优化，其中图像对应性通过互信息准则来衡量。介绍了多种配准策略，并在模拟数据和脑部跨对象DTI数据上进行了评估。两种张量重定向方法已被纳入...

In this paper, we present novel algorithms for statistically robust interpolation and approximation of diffusion tensors—which are symmetric positive definite (SPD) matrices—and use them in developing a significant extension to an existing probabilistic algorithm for scalar field segmentation, in order to segment diffusion tensor magnetic resonance imaging (DT-MRI) datasets. Using the Riemannian m...

本文提出了用于统计鲁棒插值和逼近扩散张量（即对称正定矩阵）的新算法，并将其用于扩展现有的标量场分割概率算法，以分割扩散张量磁共振成像（DT-MRI）数据集。利用黎曼度量...

Since the invention of diffusion magnetic resonance imaging (dMRI), currently the only established method for studying white matter connectivity in a clinical environment, there has been a great deal of interest in the effects of various pathologies on the connectivity of the brain. As methods for in vivo tractography have been developed, it has become possible to track and segment specific white ...

自从扩散磁共振成像（dMRI）发明以来，作为目前临床环境中研究白质连接性的唯一成熟方法，各种病理对大脑连接性的影响引起了广泛关注。随着体内纤维束追踪方法的发展，追踪和分割特定白质...

Guided by empirically established connections between clinically important tissue properties and diffusion tensor parameters, we introduce a framework for decomposing variations in diffusion tensors into changes in shape and orientation. Tensor shape and orientation both have three degrees-of-freedom, spanned by invariant gradients and rotation tangents, respectively. As an initial demonstration o...

基于临床重要组织特性与扩散张量参数之间经验确定的联系，我们引入了一个将扩散张量变化分解为形状和方向变化的框架。张量形状和方向各有三个自由度，分别由不变梯度和旋转正切张成。作为初步演示...

This paper presents a novel fuzzy-segmentation method for diffusion tensor (DT) and magnetic resonance (MR) images. Typical fuzzy-segmentation schemes, e.g., those based on fuzzy C means (FCM), incorporate Gaussian class models that are inherently biased towards ellipsoidal clusters characterized by a mean element and a covariance matrix. Tensors in fiber bundles, however, inherently lie on specif...

本文提出了一种用于扩散张量（DT）和磁共振（MR）图像的模糊分割新方法。典型的模糊分割方案，例如基于模糊C均值（FCM）的方案，采用了高斯类模型，这些模型固有地偏向于由均值和协方差矩阵表征的椭球簇。然而，纤维束中的张量本质上位于特定的...

A minimalist numerical model of white matter is presented, the objective of which is to help provide a biological basis for improved diffusion tensor imaging (DTI) analysis. Water diffuses, relaxes, and exchanges in three compartments—intracellular, extracellular, and myelin sheath. Exchange between compartments is defined so as to depend on the diffusion coefficients and the compartment sizes. Ba...

介绍了一个白质的极简数值模型，其目的是为改进扩散张量成像（DTI）分析提供生物学基础。水在三个隔室（细胞内、细胞外和髓鞘）中进行扩散、弛豫和交换。隔室之间的交换取决于扩散系数和隔室大小。

The accuracy of q-space measurements was evaluated at a 3.0-T clinical magnetic resonance imaging (MRI) scanner, as compared with a 4.7-T nuclear magnetic resonance (NMR) spectrometer. Measurements were performed using a stimulated-echo pulse-sequence on n-decane as well as on polyethylene glycol (PEG) mixed with different concentrations of water, in order to obtain bi-exponential signal decay cur...

在3.0T临床磁共振成像（MRI）扫描仪上与4.7T核磁共振（NMR）波谱仪相比，评估了q空间测量的准确性。使用受激回波脉冲序列对正癸烷以及混合不同浓度水的聚乙二醇（PEG）进行测量，以获得双指数信号衰减曲线。

One aim of this work is to investigate the feasibility of using a hierarchy of models to describe diffusion tensor magnetic resonance (MR) data in fixed tissue. Parsimonious model selection criteria are used to choose among different models of diffusion within tissue. Using this information, we assess whether we can perform simultaneous tissue segmentation and classification. Both numerical phanto...

本工作的一个目的是研究在固定组织中使用模型层次描述扩散张量磁共振（MR）数据的可行性。采用简约模型选择准则在组织内不同扩散模型中进行选择。利用这些信息，我们评估是否能够同时进行组织分割和分类。数值模...

We present a new five-dimensional (5-D) space representation of diffusion magnetic resonance imaging (dMRI) of high angular resolution. This 5-D space is basically a non-Euclidean space of position and orientation in which crossing fiber tracts can be clearly disentangled, that cannot be separated in three-dimensional position space. This new representation provides many possibilities for processi...

我们提出了一种新的高角度分辨率扩散磁共振成像的五维空间表示。这个五维空间基本上是一个位置和方向的非欧几里得空间，在其中交叉纤维束可以清晰地区分开来，而这些在三维位置空间中是无法分离的。这种新的表示为处理...提供了许多可能性。

We demonstrate a method for simulating restricted diffusion of hyperpolarized gases in lung airspaces that does not rely on an idealized analytic model of alveolar structure. Instead, the restricting geometry was generated from digital representations of histological sections of actual lung tissue obtained from a rabbit model of emphysema. Monte-Carlo simulations of restricted diffusion were perfo...

我们展示了一种模拟超极化气体在肺气腔中受限扩散的方法，该方法不依赖于理想的肺泡结构解析模型。相反，限制几何形状是从实际肺组织（来自兔肺气肿模型）的组织学切片的数字表示生成的。受限扩散的蒙特卡罗模拟...

An improved method for the combination of signals from array coils is presented as a way to reduce the influence of the noise floor on the estimation of diffusion tensor imaging (DTI) parameters. By an optimized combination of signals from the array channels and complex averaging of measurements, this method leads to a significant reduction of the noise bias. This combination algorithm allows comp...

提出了一种改进的阵列线圈信号组合方法，以减少噪声基底对扩散张量成像（DTI）参数估计的影响。通过优化阵列通道信号的组合和对测量值进行复平均，该方法显著降低了噪声偏差。该组合算法允许...

Diffusion-weighted magnetic resonance imaging (MRI) and especially diffusion tensor imaging (DTI) have proven to be useful for the characterization of the microstructure of brain white matter structures in vivo. However, DTI suffers from a number of limitations in characterizing more complex situations. The most notable problem occurs when multiple fibre bundles are present within a voxel. In this...

弥散加权磁共振成像（MRI），特别是弥散张量成像（DTI），已被证明对于表征体内脑白质结构的微观结构非常有用。然而，DTI在描述更复杂情况时存在一些局限性。最显著的问题出现在体素内存在多个纤维束时。在此...

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