Volume 23, Issue 2

We present an integrated approach to probabilistic independent component analysis (ICA) for functional MRI (FMRI) data that allows for nonsquare mixing in the presence of Gaussian noise. In order to avoid overfitting, we employ objective estimation of the amount of Gaussian noise through Bayesian analysis of the true dimensionality of the data, i.e., the number of activation and non-Gaussian noise sources. This enables us to carry out probabilistic modeling and achieves an asymptotically unique decomposition of the data. It reduces problems of interpretation, as each final independent component is now much more likely to be due to only one physical or physiological process. We also describe other improvements to standard ICA, such as temporal prewhitening and variance normalization of timeseries, the latter being particularly useful in the context of dimensionality reduction when weak activation is present. We discuss the use of prior information about the spatiotemporal nature of the source processes, and an alternative-hypothesis testing approach for inference, using Gaussian mixture models. The performance of our approach is illustrated and evaluated on real and artificial FMRI data, and compared to the spatio-temporal accuracy of results obtained from classical ICA and GLM analyses.

我们提出了一种用于功能磁共振成像（fMRI）数据的概率独立成分分析（ICA）集成方法，该方法允许在高斯噪声存在下进行非方形混合。为了避免过拟合，我们通过对数据真实维度的贝叶斯分析（即激活和非高斯噪声源的数量）来客观估计高斯噪声的量。这使我们能够进行概率建模，并实现数据的渐近唯一分解。它减少了解释问题，因为每个最终的独立成分现在更可能仅由一个物理或生理过程引起。我们还描述了标准ICA的其他改进，例如时间预白化和时间序列的方差归一化，后者在存在弱激活时的降维背景下特别有用。我们讨论了关于源过程时空性质的先验信息的使用，以及使用高斯混合模型进行推理的备择假设检验方法。我们通过在真实和人工fMRI数据上展示和评估我们方法的性能，并与经典ICA和GLM分析得到的时空准确性进行比较。

Reliable and efficient optic disk localization and segmentation are important tasks in automated retinal screening. General-purpose edge detection algorithms often fail to segment the optic disk due to fuzzy boundaries, inconsistent image contrast or missing edge features. This paper presents an algorithm for the localization and segmentation of the optic nerve head boundary in low-resolution imag...

可靠高效的视盘定位与分割是自动视网膜筛查中的重要任务。通用边缘检测算法由于边界模糊、图像对比度不一致或缺乏边缘特征，常无法分割视盘。本文提出了一种在低分辨率图像中定位和分割视神经头边界的算法...

We present a fully Bayesian approach to modeling in functional magnetic resonance imaging (FMRI), incorporating spatio-temporal noise modeling and haemodynamic response function (HRF) modeling. A fully Bayesian approach allows for the uncertainties in the noise and signal modeling to be incorporated together to provide full posterior distributions of the HRF parameters. The noise modeling is achie...

我们提出了一种在功能磁共振成像（FMRI）中建模的完全贝叶斯方法，结合了时空噪声建模和血流动力学响应函数（HRF）建模。完全贝叶斯方法允许将噪声和信号建模中的不确定性结合起来，以提供HRF参数的完整后验分布。噪声建模是通过...

The pectoral muscle represents a predominant density region in most medio-lateral oblique (MLO) views of mammograms; its inclusion can affect the results of intensity-based image processing methods or bias procedures in the detection of breast cancer. Local analysis of the pectoral muscle may be used to identify the presence of abnormal axillary lymph nodes, which may be the only manifestation of ...

胸肌在大多数乳腺X线摄影的内外侧斜位（MLO）视图中代表一个主要密度区域；其包含可能影响基于强度的图像处理方法的结果或使乳腺癌检测程序产生偏差。胸肌的局部分析可用于识别异常腋窝淋巴结的存在，这可能是...的唯一表现。

Elasticity imaging is based on the measurements of local tissue deformation. The approach to ultrasound elasticity imaging presented in this paper relies on the estimation of dense displacement fields by a coarse-to-fine minimization of an energy function that combines constraints of conservation of echo amplitude and displacement field continuity. The multiscale optimization scheme presents sever...

弹性成像基于局部组织变形的测量。本文提出的超声弹性成像方法通过粗到细的能量函数最小化来估计密集位移场，该能量函数结合了回波幅度守恒和位移场连续性的约束。多尺度优化方案呈现了若干优势...

Changes in vessel wall elasticity may be indicative of vessel pathologies. It is known, for example, that the presence of plaque stiffens the vascular wall, and that the heterogeneity of its composition may lead to plaque rupture and thrombosis. Another domain of application where ultrasound elastography may be of interest is the study of vascular wall elasticity to predict the risk of aneurysmal ...

血管壁弹性的变化可能指示血管病变。例如，已知斑块的存在会使血管壁变硬，而其成分的不均匀性可能导致斑块破裂和血栓形成。另一个可能感兴趣的应用领域是超声弹性成像研究血管壁弹性以预测动脉瘤风险...

In this paper, we explore the use of a content-adaptive mesh model (CAMM) for tomographic image reconstruction. In the proposed framework, the image to be reconstructed is first represented by a mesh model, an efficient image description based on nonuniform sampling. In the CAMM, image samples (represented as mesh nodes) are placed most densely in image regions having fine detail. Tomographic imag...

在本文中，我们探讨了使用内容自适应网格模型（CAMM）进行断层图像重建。在提出的框架中，待重建的图像首先由网格模型表示，这是一种基于非均匀采样的高效图像描述。在CAMM中，图像样本（表示为网格节点）最密集地放置在具有精细细节的图像区域。断层图像...

This paper is concerned with the detection of multiple small brain lesions from magnetic resonance imaging (MRI) data. A model based on the marked point process framework is designed to detect Virchow-Robin spaces (VRSs). These tubular shaped spaces are due to retraction of the brain parenchyma from its supplying arteries. VRS are described by simple geometrical objects that are introduced as smal...

本文关注于从磁共振成像（MRI）数据中检测多个小脑病变。设计了一个基于标记点过程框架的模型来检测Virchow-Robin间隙（VRSs）。这些管状间隙是由于脑实质从其供血动脉回缩所致。VRS由简单的几何对象描述，这些对象作为小...

Multi-angle spatial compound images are normally generated by averaging the recorded single-angle images (SAIs). To exploit possible advantages associated with alternative combination schemes, this paper investigates both the effect of number of angles (N/sub /spl theta//) as well as operator (mean, median, mean-excluding-maximum (mem), root-mean-square (rms), geometric mean and maximum) on image ...

多角度空间复合图像通常通过平均记录的单角度图像（SAI）生成。为了探索替代组合方案可能带来的优势，本文研究了角度数（N/sub /spl theta//）以及算子（均值、中位数、排除最大值均值（mem）、均方根（rms）、几何均值和最大值）对图像...的影响。

Level set methods offer highly robust and accurate methods for detecting interfaces of complex structures. Efficient techniques are required to transform an interface to a globally defined level set function. In this paper, a novel level set method based on an adaptive triangular mesh is proposed for segmentation of medical images. Special attention is paid to an adaptive mesh refinement and redis...

水平集方法为检测复杂结构的界面提供了高度鲁棒和精确的方法。需要高效的技术将界面转换为全局定义的水平集函数。本文提出了一种基于自适应三角网格的新型水平集方法，用于医学图像分割。特别注意自适应网格细化和重...

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

请潜在作者提交新的、未发表的手稿，以纳入本次征稿启事中描述的即将举行的活动。

Presents the table of contents for this issue of the periodical.

提供本期期刊的目录。

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming special issue described in this call for papers.

诚邀潜在作者提交新的、未发表的手稿，以纳入本征稿通知所述即将出版的专刊中。

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

要求潜在作者提交未发表的新稿件，以便纳入本次征稿通知中描述的活动。

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

为有意投稿的潜在作者提供说明和指导。

Provides a listing of current committee members and society officers.

提供当前委员会成员和学会官员的列表。