Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector

We propose a method for extracting the left ventricular (LV) contours from left ventriculograms by means of a neural edge detector (NED) in order to extract the contours which accord with those traced by a cardiologist. The NED is a supervised edge detector based on a modified multilayer neural network, and is trained by use of a modified back-propagation algorithm. The NED can acquire the function of a desired edge detector through training with a set of input images and the desired edges obtained from the contours traced by a cardiologist. The proposed contour-extraction method consists of 1) detection of "subjective edges" by use of the NED; 2) extraction of rough contours by use of low-pass filtering and edge enhancement; and 3) a contour-tracing method based on the contour candidates synthesized from the edges detected by the NED and the rough contours. Through experiments, it was shown that the proposed method was able to extract the contours in agreement with those traced by an experienced cardiologist, i.e., we achieved an average contour error of 6.2% for left ventriculograms at end-diastole and an average difference between the ejection fractions obtained from the manually traced contours and those obtained from the computer-extracted contours of 4.1%.     

一种等高线自动加密算法

本文给出的算法可以在间距较大的等高线之间形成新的等高线，该算法以任意直线与B-样条曲线求变算法为基础。新等高践的形成建立在原有等高线和已知的离散点等客观信息基础之上，等高线加密效果好。     

数字空间轮廓的小波描述子

为了描述数字空间目标轮廓,便于计算机图形表达,提出一种适于描述序列点轮廓的小波描述子。将数字空间轮廓视为周期序列,并基于离散小波变换给出序列点轮廓小波描述子的具体表达。结合具体医学图像轮廓进行相应的应用研究,并与Fourier轮廓描述子进行了对比,研究结果表明,在具有相同比特率的情况下,序列点轮廓小波描述子具有更好的保形性,同时实现了对轮廓数据的压缩。     

基于改进的level set方法的雷达图像跟踪

对多普勒雷达图像中的风暴进行准确的识别和跟踪,是下一步进行天气预报的前提.目前雷达图像的主要跟踪方法是进行相邻时刻图像中风暴的匹配,这些匹配方法会产生一定的误差,特别是在风暴分裂与合并的时候.基于这一问题,将一种改进的level set方法用于雷达图像中风暴的跟踪.首先在第一幅雷达图像中识别出风暴的初始轮廓,利用改进的...     

Contour extraction from cardiac MRI studies using snakes

The author investigated automatic extraction of left ventricular contours from cardiac magnetic resonance imaging (MRI) studies. The contour extraction algorithms were based on active contour models, or snakes. Based on cardiac MR image characteristics, the author suggested algorithms for extracting contours from these large data sets. The author specifically considered contour propagation methods to make the contours reliable enough despite noise, artifacts, and poor temporal resolution. The emphasis was on reliable contour extraction with a minimum of user interaction. Both spin echo and gradient echo studies were considered. The extracted contours were used for determining quantitative measures for the heart and could also be used for obtaining graphically rendered cardiac surfaces.     

基于Kinect传感器的近场手势识别追踪系统的实现

利用Kinect深度传感器所获取的图像深度信息实现手部从背景中的分割,并通过零均值离散高斯滤波、二值化、取最小外包矩形、欧式距离变换等一系列过程对手势目标进行识别,最后把得到的识别结果显示在电脑上,实现实时追踪。该系统相较其它类似系统具有算法简单,实时性好,实现成本低等特点。     

Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part I, Methodology and validation on normal subjects

The study presented in this paper tests the hypothesis that the combination of a global similarity transformation and local free-form deformations can be used for the accurate segmentation of internal structures in MR images of the brain. To quantitatively evaluate our approach, the entire brain, the cerebellum, and the head of the caudate have been segmented manually by two raters on one of the volumes (the reference volume) and mapped back onto all the other volumes, using the computed transformations. The contours so obtained have been compared to contours drawn manually around the structures of interest in each individual brain. Manual delineation was performed twice by the same two raters to test inter- and intrarater variability. For the brain and the cerebellum, results indicate that for each rater, contours obtained manually and contours obtained automatically by deforming his own atlas are virtually indistinguishable. Furthermore, contours obtained manually by one rater and contours obtained automatically by deforming this rater's own atlas are more similar than contours obtained manually by two raters. For the caudate, manual intra- and interrater similarity indexes remain slightly better than manual versus automatic indexes, mainly because of the spatial resolution of the images used in this study. Qualitative results also suggest that this method can be used for the segmentation of more complex structures, such as the hippocampus.     

基于链码匹配的断层间复杂轮廓线的三角片曲面重构

基于断层间轮廓线进行曲面重构是科学计算可视化的一个重要内容。本文利用链码理论对已获取的层间轮廓线进行编码,将二维的轮廓曲线转化为包含轮廓形状信息的一维链码;采用链码匹配技术完成相邻层轮廓特征点的匹配,将复杂轮廓线分割为若干简单的曲线段,最后,重构的曲面由这些分片构造的三角片曲面拼接而成。我们首先对模式识别中链码的串匹配算法作一个简要介绍,并详细分析讨论了其中的关键难点:编码,代价函数,链间距离,使其能够适用于我们的工作。实验表明该算法能够找出复杂轮廓线上恰当的对应特征点,从而构造出较真实的曲面。     

SAR图像不确定轮廓相似度及其可信度构建方法

SAR图像相似度准则是目标识别、图像匹配等研究内容的基础,定义合理可靠的相似度将极大地提高SAR图像解译能力。该文针对SAR图像轮廓特点,提出一种基于不确定轮廓的相似度置信区间及其可信度构建方法。首先将SAR图像不确定轮廓模糊化得到相似度定义,进而通过分析模糊模型分布函数,在给定显著性水平下得到相似度置信区间,并给出可信度定义。实验结果表明,该方法对轮廓定位有一定容错性,对一定程度的断裂轮廓及多边缘轮廓也能得到合理的相似度范围和可信度,符合人眼视觉感知。     

基于轮廓和链码表示的高效形状编码

提出一种基于轮廓和链码表示的高效无损形状编码方法。首先提取对象轮廓并细化成单像素宽度;然后将其转换成链码表示并基于方向相关性分割成若干子段,使每个子段最多包含2个基本方向码,同时结合线性检测,分离出对象轮廓中的长线性子段;最后对线性子段和非线性子段结合链码的空域相关性进行差异化编码以获得最佳编码性能。实验结果显示,所提算法的性能优于现有的常用方法,与最新的同类方法相比能平均提高压缩效率36.5%左右。     

基于自动机的围线树生成与Euler数的计算

利用边界自动机跟踪图像所有区域边界,在自动机跟踪所有边界的同时生成围线的树结构,并基于围线的树结构给出了Euler数的计算方法.跟踪算法复杂度是线性的,能跟踪任意复杂图像区域.计算Euler数的算法不仅适用于整幅图像,而且适用于局部图像.     

Polygonal modeling of contours of breast tumors with the preservation of spicules

Malignant breast tumors typically appear in mammograms with rough, spiculated, or microlobulated contours, whereas most benign masses have smooth, round, oval, or macrolobulated contours. Several studies have shown that shape factors that incorporate differences as above can provide high accuracies in distinguishing between malignant tumors and benign masses based upon their contours only. However, global measures of roughness, such as compactness, are less effective than specially designed features based upon spicularity and concavity. We propose a method to derive polygonal models of contours that preserve spicules and details of diagnostic importance. We show that an index of spiculation derived from the turning functions of the polygonal models obtained by the proposed method yields better classification accuracy than a similar measure derived using a previously published method. The methods were tested with a set of 111 contours of 65 benign masses and 46 malignant tumors. A high classification accuracy of 0.94 in terms of the area under the receiver operating characteristics curve was obtained.     

基于链码的肿瘤CT图象层间轮廓线最佳点匹配技术的研究

本文利用链码理论对已获取的肿瘤层间轮廓线进行编码,将二维轮廓线转化为包含轮廓形状信息的一维链码;采用一种基于链码的匹配技术来完成相邻层轮廓线点匹配,从而建立起其间的对应关系并用于后期的三维重建.本文首先对模式识别中链码的串匹配算法作了一个简要的介绍,并详细分析了应用链码技术获取相邻轮廓间点对应关系的关键难点,使其能够适用于本文的工作.该方法的计算复杂度近似于M*N(M和N分别为相邻轮廓线顶点的数目).并用实际的肿瘤图象进行实验,结果表明了该方法的有效性.     

Three-dimensional statistical model for gingival contour reconstruction

Optimal gingival contours around restored teeth and implants are of critical importance for restorative success and esthetics. This paper describes a novel computer-aided methodology for building a 3-D statistical model of gingival contours from a 3-D scan dental dataset and reconstructing missing gingival contours in partially edentulous patients. The gingival boundaries were first obtained from the 3-D dental model through a discrete curvature analysis and shortest path searching algorithm. Based on the gingival shape differential characteristics, the boundaries were demarcated to construct the gingival contour of each individual tooth. Through B-spline curve approximation to each gingival contour, the control points of the B-spline curves are used as the shape vector for training the model. Statistical analysis results demonstrate that the method can give a simple but compact model that effectively capture the most important variations in arch width and shape as well as gingival morphology and position. Within this statistical model, the morphologically plausible missing contours can be inferred based on a nonlinear optimization fitting from the global similarity transformation, the model shape deformation and a Mahalanobis prior. The reconstruction performance is evaluated through large simulated experimental data and a real patient case, which demonstrates the effectiveness of this approach.     

A measurement-based model for predicting coverage areas of urbanmicrocells

The authors have performed data reductions on 900 MHz signal attenuations measured on numerous streets in Manhattan. The database consists of both local spatial averages of signal attenuation and the short-term fluctuations about this average. The former, which is termed the local mean attenuation (LMA), is the primary focus. The database is used to obtain contours of constant LMA for two neighborhoods. It is shown that the contours have the shapes of convex diamonds. The authors propose that squares inscribed within these contours be used as the building blocks of microcellular environments. A theory is developed that explains the contours and predicts, with reasonable accuracy, the sizes of the inscribed squares. It is also shown that the prediction method can be applied without the need for measured data. The short-term fluctuation statistics of the signal attenuation are examined. They are shown to be Rayleigh-like in the non-line-of-sight regions of a microcell and Rice-like in the line-of-sight region. Possible extensions to other frequency bands and other urban environments are discussed     

Study and comparison of certain shape measures

The aim of this work is a study and a comparison of certain global shape measures: squared perimeter/area, mean vector radius divided by its standard deviation, bending energy of the contour, elongation, roughness, deviation from circle, contour energy. These measures are often used in applications, for example cytology, without deep knowledge about: (i) the error made when computing the shape measures on discrete or digitized contours, (ii) the relation of the shape measures with physical properties of the shape such as elongation, number of lobes, depth of the lobes, (iii) the intercorrelations of the shape measures, and (iv) their discriminating power. This involves the building of a family of contours, which are first geometrically defined, and then subsequently discretized and digitized. These contours depend on three variables which permit the physical properties mentioned above to be controlled. A study has been made of the way various sets of three or four measures individualize the elements of the family. The result is expressed as the percentage of elements which are not confused with others when computing the measures on digitized contours (and taking into account the inherent error).     

Automatic detection of myocardial contours in cine-computed tomographic images

Quantitative evaluation of cardiac function from cardiac images requires the identification of the myocardial walls. This generally requires the clinician to view the image and interactively trace the contours. This method is susceptible to great variability that depends on the experience and knowledge of the particular operator tracing the contours. The particular imaging modality that is used may also add tracing difficulties. Cine-computed tomography (cine-CT) is an imaging modality capable of providing high quality cross-sectional images of the heart. CT images, however, are cluttered, i.e., objects that are not of interest, such as the chest wall, liver, stomach, are also visible in the image. To decrease this variability, investigators have developed computer-assisted or near-automatic techniques for tracing these contours. All of these techniques, however, require some operator intervention to confidently identify myocardial borders. The authors present a new algorithm that automatically finds the heart within the chest, and then proceeds to outline (detect) the myocardial contours. Information at each tomographic slice is used to estimate the contours at the next tomographic slice, thus allowing the algorithm to work in near-apical cross-sectional images where the myocardial borders are often difficult to identify. The algorithm does not require operator input and can be used in a batch mode to process large quantities of data. An evaluation and correction phase is included to allow an operator to view the results and selectively correct portions of contours. The authors tested the algorithm by automatically identifying the myocardial borders of 27 cardiac images obtained from three human subjects and quantitatively comparing these automatically determined borders with those traced by an experienced cardiologist.     

Estimation of the contouring error vector for the cross-coupledcontrol design

In biaxial motion systems, applying the cross-coupled control (CCC) significantly improves contouring accuracy for linear and circular contours. As geometrical and parametric curves become more popular in modern manufacturing, machining processes with multiaxis motion systems are required, however, the available biaxial CCC cannot be directly applied to arbitrary contours with multiaxis machining systems. In this paper, we propose a novel approach for arbitrary contours by estimating the contouring error vector to efficiently determine the variable gains for CCC. Experimental results for a biaxial motion system indicate that the proposed approach efficiently yields variable gains similar to those in traditional CCC. Furthermore, results on a three-axis CNC machining center show that the present approach significantly improves motion accuracy in multiaxis motion systems     

复杂背景下多运动目标轮廓检测

该文在研究多种运动目标轮廓检测算法的基础上,提出了一种新的复杂背景下基于连续3帧即可精确检测多运动目标轮廓的算法。分析和实验表明,该算法抗干扰能力强,可以有效地消除被运动目标遮挡和重现的纹理背景,对复杂背景及不重叠多目标运动情况,可以精确地定位各个运动目标的外轮廓。此外,该算法具有潜在的并行机制,易于实现实时运动图像处理。