Volume 21, Issue 5

We describe a method for automatically building statistical shape models from a training set of example boundaries/surfaces. These models show considerable promise as a basis for segmenting and interpreting images. One of the drawbacks of the approach is, however, the need to establish a set of dense correspondences between all members of a set of training shapes. Often this is achieved by locating a set of "landmarks" manually on each training image, which is time consuming and subjective in two dimensions and almost impossible in three dimensions. We describe how shape models can be built automatically by posing the correspondence problem as one of finding the parameterization for each shape in the training set. We select the set of parameterizations that build the "best" model. We define "best" as that which minimizes the description length of the training set, arguing that this leads to models with good compactness, specificity and generalization ability. We show how a set of shape parameterizations can be represented and manipulated in order to build a minimum description length model. Results are given for several different training sets of two-dimensional boundaries, showing that the proposed method constructs better models than other approaches including manual landmarking-the current gold standard. We also show that the method can be extended straightforwardly to three dimensions.

我们描述了一种从示例边界/表面训练集自动构建统计形状模型的方法。这些模型作为分割和解释图像的基础显示出相当大的前景。然而，该方法的一个缺点是需要在一组训练形状的所有成员之间建立一组密集的对应关系。这通常是通过在每个训练图像上手动定位一组“地标”来实现的，这在二维中耗时且主观，在三维中几乎不可能。我们描述了如何通过将对应问题转化为寻找训练集中每个形状的参数化来自动构建形状模型。我们选择构建“最佳”模型的参数化集合。我们将“最佳”定义为最小化训练集描述长度的参数化，认为这会导致模型具有良好的紧凑性、特异性和泛化能力。我们展示了如何表示和操作一组形状参数化以构建最小描述长度模型。给出了几个不同二维边界训练集的结果，表明所提出的方法构建的模型优于其他方法，包括当前金标准的手动地标定位。我们还表明该方法可以直接扩展到三维。

It has been shown that the difference of squares cost function used by standard realignment packages (SPM and AIR) can lead to the detection of spurious activations, because the motion parameter estimations are biased by the activated areas. Therefore, this paper describes several experiments aiming at selecting a better similarity measure to drive functional magnetic resonance image registration....

已经证明，标准重对齐软件包（SPM和AIR）使用的平方差代价函数可能导致检测到虚假激活，因为运动参数估计受到激活区域的影响。因此，本文描述了几个旨在选择更好的相似性度量来驱动功能磁共振图像配准的实验。

Two new consistent image registration algorithms are presented: one is based on matching corresponding landmarks and the other is based on matching both landmark and intensity information. The consistent landmark and intensity registration algorithm produces good correspondences between images near landmark locations by matching corresponding landmarks and away from landmark locations by matching ...

提出了两种新的一致图像配准算法：一种基于匹配对应地标，另一种基于匹配地标和强度信息。一致地标和强度配准算法通过匹配对应地标来产生地标位置附近图像之间的良好对应关系，并通过匹配强度信息来产生远离地标位置的对应关系。

A method is presented for determining paths of anatomical connection between regions of the brain using magnetic resonance diffusion tensor information. Level set theory, applied using fast marching methods, is used to generate three-dimensional time of arrival maps, from which connection paths between brain regions may be identified. The method is demonstrated in the normal brain and it is shown ...

提出了一种利用磁共振扩散张量信息确定大脑区域之间解剖连接路径的方法。采用快速行进法应用水平集理论，生成三维到达时间图，从中可以识别大脑区域之间的连接路径。该方法在正常大脑中得到验证，结果表明...

Dynamic systems have proven to be well suited to describe a broad spectrum of human coordination behavior such as synchronization with auditory stimuli. Simultaneous measurements of the spatiotemporal dynamics of electroencephalographic (EEG) and magnetoencephalographic (MEG) data reveals that the dynamics of the brain signals is highly ordered and also accessible by dynamic systems theory. Howeve...

动态系统已被证明非常适合描述人类协调行为的广泛谱系，例如与听觉刺激的同步。脑电图和脑磁图数据的时空动态同时测量表明，大脑信号的动态是高度有序的，并且也可以通过动态系统理论来解析。然而...

This paper presents a multiscale framework based on a medial representation for the segmentation and shape characterization of anatomical objects in medical imagery. The segmentation procedure is based on a Bayesian deformable templates methodology in which the prior information about the geometry and shape of anatomical objects is incorporated via the construction of exemplary templates. The anat...

本文提出了一种基于中轴表示的多尺度框架，用于医学图像中解剖对象的分割和形状表征。分割过程基于贝叶斯可变形模板方法，通过构建示例模板纳入关于解剖对象几何形状的先验信息。解剖...

A method for automated segmentation of major cortical sulci on the outer brain boundary is presented, with emphasis on automatically determining point correspondence and on labeling cortical regions. The method is formulated in a general optimization framework defined on the unit sphere, which serves as parametric domain for convoluted surfaces of spherical topology. A statistical shape model, whi...

提出了一种自动分割大脑外边界主要皮质沟的方法，重点在于自动确定点对应关系并标记皮质区域。该方法在单位球面上定义的一般优化框架中表述，该球面用作球形拓扑复杂表面的参数域。一个统计形状模型，其...

Automatic registration of multimodal images involves algorithmically estimating the coordinate transformation required to align the data sets. Most existing methods in the literature are unable to cope with registration of image pairs with large nonoverlapping field of view (FOV). We propose a robust algorithm, based on matching dominant local frequency image representations, which can cope with i...

自动多模态图像配准涉及算法估计坐标变换以对齐数据集。文献中大多数现有方法无法处理具有大非重叠视场（FOV）的图像对配准。我们提出了一种基于匹配主导局部频率图像表示的鲁棒算法，可以处理大非重叠视场的图像对配准。

Imaging is often used for the purpose of estimating the value of some parameter of interest. For example, a cardiologist may measure the ejection fraction (EF) of the heart in order to know how much blood is being pumped out of the heart on each stroke. In clinical practice, however, it is difficult to evaluate an estimation method because the gold standard is not known, e.g., a cardiologist does ...

影像学常用于估计某个感兴趣参数的值。例如，心脏病专家可能测量心脏的射血分数（EF），以了解每次心跳泵出的血量。然而，在临床实践中，由于金标准未知，评估一种估计方法很困难。例如，心脏病专家并不...

The understanding of brain networks becomes increasingly the focus of current research. In the context of functional magnetic resonance imagery (fMRI) data of the human brain, networks have been mostly detected using standard clustering approaches. In this work, we present a new method of detecting functional networks using fMRI data. The novelty of this method is that these networks have the prop...

脑网络的理解日益成为当前研究的焦点。在人脑功能磁共振成像（fMRI）数据的背景下，网络主要通过标准聚类方法检测。在这项工作中，我们提出了一种使用fMRI数据检测功能网络的新方法。该方法的新颖之处在于这些网络具有...

For performing simple detection and discrimination tasks in image noise, human observers are often modeled by a cross-correlation between the image and an observer template followed by the injection of the observer's internal noise. This paper is concerned with estimating this template using the two-alternative forced-choice (2AFC) experimental paradigm. The basic idea behind the estimation proced...

为了在图像噪声中执行简单的检测和辨别任务，人类观察者通常被建模为图像与观察者模板之间的互相关，随后注入观察者的内部噪声。本文关注使用两可选强制选择（2AFC）实验范式来估计这个模板。估计过程背后的基本思想...