Spatio-temporal tracking of myocardial deformations with a 4-D B-spline model from tagged MRI

Accurate delineation of the volumetric motion of the left ventricle (LV) of the heart from tagged magnetic resonance imaging (MRI) is an important area of research. We have built a system that takes extracted tag line features from short axis (SA) and long axis (LA) image sequences as input and fits a four-dimensional (4-D) time-varying B-spline model to the data by simultaneously fitting the model knot solids to MRI frames via matching three sequences of solid knot planes to the LV tag planes for 4-D tracking. Important advantages of the model are that reconstruction of tag surfaces, three-dimensional (3-D) material point localization, as well as displacement reconstruction are all achieved in a single step. The generated 3-D displacement fields are validated with a cardiac motion simulator, and 3-D motion fields capturing in vivo deformations in a porcine model with posterolateral myocardial infarction are illustrated.     

Three-dimensional myocardial strain reconstruction from tagged MRI using a cylindrical B-spline model

In this paper, we present a new method for reconstructing three-dimensional (3-D) left ventricular myocardial strain from tagged magnetic resonance (MR) image data with a 3-D B-spline deformation model. The B-spline model is based on a cylindrical coordinate system that more closely fits the morphology of the myocardium than previously proposed Cartesian B-spline models and does not require explicit regularization. Our reconstruction method first fits a spatial coordinate B-spline displacement field to the tag line data. This displacement field maps each tag line point in the deformed myocardium back to its reference position (end-diastole). The spatial coordinate displacement field is then converted to material coordinates with another B-spline fit. Finally, strain is computed by analytically differentiating the material coordinate B-spline displacement field with respect to space. We tested our method with strains reconstructed from an analytically defined mathematical left ventricular deformation model and ten human imaging studies. Our results demonstrate that a quadratic cylindrical B-spline with a fixed number of control points can accurately fit a physiologically realistic range of deformations. The average 3-D reconstruction computation time is 20 seconds per time frame on a 450 MHz Sun Ultra80 workstation.     

Adaptive MLSE equalizers with parametric tracking for multipathfast-fading channels

We use the parametric channel identification algorithm proposed by Chen and Paulraj (see Proc. IEEE Vehicular Technology Conf., p.710-14, 1997) and by Chen, Kim and Liang (see IEEE Trans. Veh. Technol., p.1923-35, 1999) to adaptively track the fast-fading channels for the multichannel maximum likelihood sequence estimation (MLSE) equalizer using multiple antennas. Several commonly-used channel tracking schemes, decision-directed recursive least square (DD/RLS), per-survivor processing recursive least square (PSP/RLS) and other reduced-complexity MLSE algorithms are considered. An analytic lower bound for the multichannel MLSE equalizer with no channel mismatch in the time-varying specular multipath Rayleigh-fading channels is derived. Simulation results that illustrate the performance of the proposed algorithms working with various channel tracking schemes are presented, and then these results are compared with the analytic bit error rate (BER) lower bound and with the conventional MLSE equalizers directly tracking the finite impulse response (FIR) channel tap coefficients. We found that the proposed algorithm always performs better than the conventional adaptive MLSE algorithm, no matter what channel tracking scheme is used. However, which is the best tracking scheme to use depends on the scenario of the system     

利用B样条实现基于等高线的三维地形图

利用B样条曲线将等高线光栅图矢量化。根据B样条曲线插值公式得到等高线与纵横网格线的交点;根据这些史点的三维坐标值,利用线形插值分别得到纵横网格交点的高程,其均值作为网格变点的最终高程;最后利用OpenGL中的NURBS曲面接口生成三维地形图。该方法输入工作量小．数据存储量少。模拟效果较好。     

Three-dimensional surface reconstruction from multistatic SAR images

This paper discusses reconstruction of three-dimensional surfaces from multiple bistatic synthetic aperture radar (SAR) images. Techniques for surface reconstruction from multiple monostatic SAR images already exist, including interferometric processing and stereo SAR. We generalize these methods to obtain algorithms for bistatic interferometric SAR and bistatic stereo SAR. We also propose a framework for predicting the performance of our multistatic stereo SAR algorithm, and, from this framework, we suggest a metric for use in planning strategic deployment of multistatic assets.     

Band partitioning algorithm for surface reconstruction from planarcontours

A heuristic contour triangulation method is proposed for reconstructing a facet model from a set of wire-frame contours. The proposed band partitioning algorithm (BPA) compensates for the disadvantages of optimal and heuristic methods, and produces an improved reconstructed surface. Furthermore, the maximum deviation criterion in span selection prohibits drastic error propagation in the surface definition procedure. Experimental results show that the proposed method is very stable and efficient, making it suitable for a wide range of applications     

Microcomputer-based interactive tracking of blood cells atbiomaterial surfaces

A microcomputer-based system for analyzing the motion of human platelets and leukocytes at synthetic surfaces from a sequence of video frames on tape is described. The software is designed to provide convenient interaction with an operator to reduce the burden of manual analysis. In addition, the system computes and stores the cell movement data on disk for subsequent statistical analysis. Measurement include the number and nature of cell-to-surface collisions, residence times, and distances traveled.     

Vessel surface reconstruction with a tubular deformable model

Three-dimensional (3-D) angiographic methods are gaining acceptance for evaluation of atherosclerotic disease. However, measurement of vessel stenosis from 3-D angiographic methods can be problematic due to limited image resolution and contrast. We present a method for reconstructing vessel surfaces from 3-D angiographic methods that allows for objective measurement of vessel stenosis. The method is a deformable model that employs a tubular coordinate system. Vertex merging is incorporated into the coordinate system to maintain even vertex spacing and to avoid problems of self-intersection of the surface. The deformable model was evaluated on clinical magnetic resonance (MR) images of the carotid (n=6) and renal (n=2) arteries, on an MR image of a physical vascular phantom and on a digital vascular phantom. Only one gross error occurred for all clinical images. All reconstructed surfaces had a realistic, smooth appearance. For all segments of the physical vascular phantom, vessel radii from the surface reconstruction had an error of less than 0.2 of the average voxel dimension. Variability of manual initialization of the deformable model had negligible effect on the measurement of the degree of stenosis of the digital vascular phantom     

Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces.

Cell migrations and deformations play essential roles in biological processes, such as parasite invasion, immune response, embryonic development, and cancer. We describe a fully automatic segmentation and tracking method designed to enable quantitative analyses of cellular shape and motion from dynamic three-dimensional microscopy data. The method uses multiple active surfaces with or without edges, coupled by a penalty for overlaps, and a volume conservation constraint that improves outlining of cell/cell boundaries. Its main advantages are robustness to low signal-to-noise ratios and the ability to handle multiple cells that may touch, divide, enter, or leave the observation volume. We give quantitative validation results based on synthetic images and show two examples of applications to real biological data.     

Viewpoint invariant reconstruction of visible surfaces usingfirst-order regularisation

The application of a first-order regularisation technique to the problem of reconstruction of visible surfaces is described. The approach is a computationally efficient first-order method that achieves approximate invariance. The results indicate that the proposed method for surface reconstruction performs well on sparse noisy range data     

Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: a tool for cell-based drug testing

This paper presents a segmentation and tracking method for quantitative analysis of cell dynamics from in vitro videomicroscopy data. The method is based on parametric active contours and includes several adaptations that address important difficulties of cellular imaging, particularly the presence of low-contrast boundary deformations known as pseudopods, and the occurence of multiple contacts between cells. First, we use an edge map based on the average intensity dispersion that takes advantage of relative background homogeneity to facilitate the detection of both pseudopods and interfaces between adjacent cells. Second, we introduce a repulsive interaction between contours that allows correct segmentation of objects in contact and overcomes the shortcomings of previously reported techniques to enforce contour separation. Our tracking technique was validated on a realistic data set by comparison with a manually defined ground-truth and was successfully applied to study the motility of amoebae in a biological research project.     

Pattern tracking and 3-D motion reconstruction of a rigid body from a 2-D image sequence

This paper presents an integrated method to identify an object pattern from an image, and track its movement over a sequence of images. The sequence of images comes from a single perspective video source, which is capturing data from a precalibrated scene. This information is used to reconstruct the scene in three-dimension (3-D) within a virtual environment where a user can interact and manipulate the system. The steps that are performed include the following: i) Identify an object pattern from a two-dimensional perspective video source. The user outlines the region of interest (ROI) in the initial frame; the procedure builds a refined mask of the dominant object within the ROI using the morphological watershed algorithm. ii) The object pattern is tracked between frames using object matching within the mask provided by the previous and next frame, computing the motion parameters. iii) The identified object pattern is matched with a library of shapes to identify a corresponding 3-D object. iv) A virtual environment is created to reconstruct the scene in 3-D using the 3-D object and the motion parameters. This method can be applied to real-life application problems, such as traffic management and material flow congestion analysis.     

Patch-based reconstruction of surfaces undergoing different types of deformations

We deal with the reconstruction of surfaces that deform under a variety of conditions. The deformation can range from no extension to a certain degree of extensibility. The deformed surface is reconstructed from a single image, given a 3D reference shape. This shape corresponds to the undeformed state of the surface and can be computed using any appropriate technique. In particular, we use homographies defined from two views of the surface. To proceed with the 3D reconstruction of the deformed surface, we assume that the deformations are locally homogeneous and that the overall surface deformation can be obtained by combining the local homogeneous deformations. For this purpose, the surface is split into small patches. For each patch, a mapping between the undeformed and the deformed shapes is computed. The mapping is specified by using the quadratic deformation model Fayad et al. (Proceedings of British Machine Vision Conference (BMVC), 2004). As a result, given the undeformed shape, we define an optimization procedure whose goal is to estimate the 3D positions of deformed points in each image. The optimization is performed on each patch, independently of the others. The experimental results show that this approach allows precise reconstruction of a wide class of real deformations.     

Semi-automatic tracking of myocardial motion in MR tagged images

Tissue tagging using magnetic resonance (MR) imaging has enabled quantitative noninvasive analysis of motion and deformation in vivo. One method for MR tissue tagging is Spatial Modulation of Magnetization (SPAMM). Manual detection and tracking of tissue tags by visual inspection remains a time-consuming and tedious process. The authors have developed an interactively guided semi-automated method of detecting and tracking tag intersections in cardiac MR images. A template matching approach combined with a novel adaptation of active contour modeling permits rapid analysis of MR images. The authors have validated their technique using MR SPAMM images of a silicone gel phantom with controlled deformations. Average discrepancy between theoretically predicted and semi-automatically selected tag intersections was 0.30 mm+/-0.17 [mean+/-SD, NS (P<0.05)]. Cardiac SPAMM images of normal volunteers and diseased patients also have been evaluated using the authors' technique.     

Application of autoregressive moving average parametric modeling in magnetic resonance image reconstruction

The modeling of data is an alternative to conventional use of the fast Fourier transform (FFT) algorithm in the reconstruction of magnetic resonance (MR) images. The application of the FFT leads to artifacts and resolution loss in the image associated with the effective window on the experimentally-truncated phase encoded MR data. The transient error modeling method treats the MR data as a subset of the transient response of an infinite impulse filter (H(z) = B(z)IA(z)). Thus, the data are approximated by a deterministic autoregressive moving average (ARMA) model. The algorithm for calculating the filter coefficients is described. It is demonstrated that using the filter coefficients to reconstruct the image removes the truncation artifacts and improves the resolution. However, determining the autoregressive (AR) portion of the ARMA filter by algorithms that minimize the forward and backward prediction errors (e.g., Burg) leads to significant image degradation. The moving average (MA) portion is determined by a computationally efficient method of solving a finite difference equation with initial values. Special features of the MR data are incorporated into the transient error model. The sensitivity to noise and the choice of the best model order are discussed. MR images formed using versions of the transient error reconstruction (TERE) method and the conventional FFT algorithm are compared using data from a phantom and a human subject. Finally, the computational requirements of the algorithm are addressed.     

Physics-based ball tracking and 3D trajectory reconstruction with applications to shooting location estimation in basketball video

The demand for computer-assisted game study in sports is growing dramatically. This paper presents a practical video analysis system to facilitate semantic content understanding. A physics-based algorithm is designed for ball tracking and 3D trajectory reconstruction in basketball videos and shooting location statistics can be obtained. The 2D-to-3D inference is intrinsically a challenging problem due to the loss of 3D information in projection to 2D frames. One significant contribution of the proposed system lies in the integrated scheme incorporating domain knowledge and physical characteristics of ball motion into object tracking to overcome the problem of 2D-to-3D inference. With the 2D trajectory extracted and the camera parameters calibrated, physical characteristics of ball motion are involved to reconstruct the 3D trajectories and estimate the shooting locations. Our experiments on broadcast basketball videos show promising results. We believe the proposed system will greatly assist intelligence collection and statistics analysis in basketball games.     

Three-dimensional surface reconstruction and fluorescent visualization of cardiac activation

Optical imaging of transmembrane potentials in cardiac tissue is a rapidly growing technique in cardiac electrophysiology. Traditional studies typically use a monocular imaging setup, thus limiting investigation to a restricted region of tissue. However, studies of large-scale wavefront dynamics, especially those during fibrillation and defibrillation, would benefit from visualization of the entire epicardial surface. To solve this problem, a panoramic cardiac visualization algorithm was developed which performs the two tasks of reconstruction of the surface geometry of the heart, and representation of the panoramic fluorescence information as a texture mapping onto the geometry that was previously created. This system permits measurement of epicardial electrodynamics over a geometrically realistic representation of the actual heart being studied. To verify the accuracy of the algorithm, the procedure was applied to synthetic images of a patterned ball; further verification was provided by application of the algorithm to a model heart placed in the experimental setup. Both sets of images produced mean registration image errors on the order of 2 pixels, corresponding to roughly 3 mm on the geometry. We demonstrate the algorithm by visualizing epicardial wavefronts on an isolated, perfused rabbit heart.     

Statistical characteristics of simulated radar imagery from baresoil surfaces: effects of surface roughness and soil moisturevariability

The potential of high-resolution radar imagery to estimate various hydrological parameters, such as soil moisture, has long been recognized. Image simulation is one approach to study the interrelationships between the radar response and the underlying ground parameters. In order to perform realistic simulations, the authors incorporated the effects of naturally occurring spatial variability and spatial correlations of those ground parameters that affect the radar response, primarily surface roughness and soil moisture. Surface roughness and soil moisture images were generated for a hypothetical 100×100 m bare soil surface area at 1 m resolution using valid probability distributions and correlation lengths. These values were then used to obtain copolarized radar scattering coefficients at 2 GHz (L band) and 10 GHz (X band) frequencies using appropriate backscatter models, which were then converted to a digital number within 0-255 gray scale in order to generate radar images. The effect of surface roughness variability causes variability in the radar image, which is more apparent under smooth soil conditions. On the other hand, the inherent spatial pattern in soil moisture tends to cause similar patterns in the radar image under rougher soil conditions. The maximum difference between contrast-enhanced mean values of the radar image digital number due to moisture variations occurs at surface roughness values in the 1.5-2.0 cm range     

Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces

A semiempirical polarimetric backscattering model for bare soil surfaces is inverted directly to retrieve both the volumetric soil moisture content M/sub v/ and the rms surface height s from multipolarized radar observations. The rms surface height s and the moisture content M/sub v/ can be read from inversion diagrams using the measurements of the cross-polarized backscattering coefficient /spl sigma//sub vh//sup 0/ and the copolarized ratio p(=/spl sigma//sub hh//sup 0///spl sigma//sub vv//sup 0/). Otherwise, the surface parameters can be estimated simply by solving two equations (/spl sigma//sub vh//sup 0/ and p) in two unknowns (M/sub v/ and s). The inversion technique has been applied to the polarimetric backscattering coefficients measured by ground-based polarimetric scatterometers and the Jet Propulsion Laboratory airborne synthetic aperture radar. A good agreement was observed between the values of surface parameters (the rms height s, roughness parameter ks, and the volumetric soil moisture content M/sub v/) estimated by the inversion technique and those measured in situ.     

基于Kalman滤波与Camshift算法的水面目标跟踪

根据水面监控图像的特点,对运动载体采集到的水面视频图像进行处理,从而实现对运动目标的跟踪。首先,利用Haar分类器检测出水面的运动目标,并用检测结果初始化Camshift跟踪器的搜索窗口;然后,运用Kalman滤波器与Camshift组合算法实现对运动目标的跟踪。其中,利用Kalman滤波算法预测目标在下一帧中出现的位置,Camshift算法用来跟踪目标,以此减小搜索范围,提高跟踪效率。实验结果表明,该算法能够实现对水面运动舰船的检测并进行有效跟踪。