A quantitative analysis of 3-D coronary modeling from two or more projection images

A method is introduced to examine the geometrical accuracy of the three-dimensional (3-D) representation of coronary arteries from multiple (two and more) calibrated two-dimensional (2-D) angiographic projections. When involving more then two projections, (multiprojection modeling) a novel procedure is presented that consists of fully automated centerline and width determination in all available projections based on the information provided by the semi-automated centerline detection in two initial calibrated projections. The accuracy of the 3-D coronary modeling approach is determined by a quantitative examination of the 3-D centerline point position and the 3-D cross sectional area of the reconstructed objects. The measurements are based on the analysis of calibrated phantom and calibrated coronary 2-D projection data. From this analysis a confidence region (alpha degrees approximately equal to [35 degrees - 145 degrees]) for the angular distance of two initial projection images is determined for which the modeling procedure is sufficiently accurate for the applied system. Within this angular border range the centerline position error is less then 0.8 mm, in terms of the Euclidean distance to a predefined ground truth. When involving more projections using our new procedure, experiments show that when the initial pair of projection images has an angular distance in the range alpha degrees approximately equal to [35 degrees - 145 degrees], the centerlines in all other projections (gamma = 0 degrees - 180 degrees) were indicated very precisely without any additional centering procedure. When involving additional projection images in the modeling procedure a more realistic shape of the structure can be provided. In case of the concave segment, however, the involvement of multiple projections does not necessarily provide a more realistic shape of the reconstructed structure.     

基于投影的运动目标跟踪研究

在运动目标跟踪方面,运动目标跟踪算法直接影响着运动目标跟踪的准确性和稳定性,现有的目标跟踪算法大多是基于特征或运动信息的,虽然能够完成对运动目标的可靠跟踪,但是需要处理的数据量大,运算复杂,很难达到实时跟踪的要求。本文首先阐述了跟踪算法中模板相关匹配算法的基本原理,然后跟踪系统的实际需求,详述了投影法快速定位目标跟踪的方法,并给出了投影算法跟踪的实验结果,该算法基本能满足跟踪系统中运算量小和实时性的要求。     

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.     

3-D tracking and motion estimation using hierarchical Kalman filter

The authors present a novel approach to the problem of tracking and reconstructing articulated objects in 3-D space. The newly conceived computational process and its supporting data structure, the hierarchical Kalman filter (HKF) and the adaptive hierarchical structure (AHS). Allow the problem to be treated in a singlet unified framework. There are three novelties in the authors' formulation: reducing the 3-D tracking problem to 2-D tracking; incorporating the kinematic and the dynamic properties of object; and tracking nonrigid objects. To demonstrate the appropriateness of the proposed method, the authors present some of the experimental results on both synthetic and real images     

Registration of real-time 3-D ultrasound images of the heart for novel 3-D stress echocardiography

Stress echocardiography is a routinely used clinical procedure to diagnose cardiac dysfunction by comparing wall motion information in prestress and poststress ultrasound images. Incomplete data, complicated imaging protocols and misaligned prestress and poststress views, however, are known limitations of conventional stress echocardiography. We discuss how the first two limitations are overcome via the use of real-time three-dimensional (3-D) ultrasound imaging, an emerging modality, and have called the new procedure "3-D stress echocardiography." We also show that the problem of misaligned views can be solved by registration of prestress and poststress 3-D image sequences. Such images are misaligned because of variations in placing the ultrasound transducer and stress-induced anatomical changes. We have developed a technique to temporally align 3-D images of the two sequences first and then to spatially register them to rectify probe placement error while preserving the stress-induced changes. The 3-D spatial registration is mutual information-based. Image registration used in conjunction with 3-D stress echocardiography can potentially improve the diagnostic accuracy of stress testing.     

Concurrent 3-D motion segmentation and 3-D interpretation of temporal sequences of monocular images.

The purpose of this study is to investigate a variational method for joint multiregion three-dimensional (3-D) motion segmentation and 3-D interpretation of temporal sequences of monocular images. Interpretation consists of dense recovery of 3-D structure and motion from the image sequence spatiotemporal variations due to short-range image motion. The method is direct insomuch as it does not require prior computation of image motion. It allows movement of both viewing system and multiple independently moving objects. The problem is formulated following a variational statement with a functional containing three terms. One term measures the conformity of the interpretation within each region of 3-D motion segmentation to the image sequence spatiotemporal variations. The second term is of regularization of depth. The assumption that environmental objects are rigid accounts automatically for the regularity of 3-D motion within each region of segmentation. The third and last term is for the regularity of segmentation boundaries. Minimization of the functional follows the corresponding Euler-Lagrange equations. This results in iterated concurrent computation of 3-D motion segmentation by curve evolution, depth by gradient descent, and 3-D motion by least squares within each region of segmentation. Curve evolution is implemented via level sets for topology independence and numerical stability. This algorithm and its implementation are verified on synthetic and real image sequences. Viewers presented with anaglyphs of stereoscopic images constructed from the algorithm's output reported a strong perception of depth.     

Passive markers for tracking surgical instruments in real-time 3-D ultrasound imaging

A family of passive echogenic markers is presented by which the position and orientation of a surgical instrument can be determined in a 3-D ultrasound volume, using simple image processing. Markers are attached near the distal end of the instrument so that they appear in the ultrasound volume along with the instrument tip. They are detected and measured within the ultrasound image, thus requiring no external tracking device. This approach facilitates imaging instruments and tissue simultaneously in ultrasound-guided interventions. Marker-based estimates of instrument pose can be used in augmented reality displays or for image-based servoing. Design principles for marker shapes are presented that ensure imaging system and measurement uniqueness constraints are met. An error analysis is included that can be used to guide marker design and which also establishes a lower bound on measurement uncertainty. Finally, examples of marker measurement and tracking algorithms are presented along with experimental validation of the concepts.     

心脏图像三维运动与材料信息的提取和重建

针对传统心脏图像分析方法将运动分析和材料分析作为两个独立过程带来的弊端,本文基于心脏连续生物力学模型,利用有限元方法和扩展卡尔曼滤波器(EKF),将运动分析和材料分析作为一个问题来解决,取得了较好的结果。仿真实验验证了本文方法的有效性,给出了利用真实病人心脏图像实现三维运动和材料信息的同时重建的结果。     

MONO－PULSE RADAR 3－D IMAGING TECHNIQUES FOR TARGET IN STEPPED TRACKING MODE

A method for mono-pulse radar 3-D imaging in stepped tracking mode is presented and the amplitude linear modulation of error signals in stepped tracking mode is analyzed with its compensation method followes,so the problem of precisely tracking of target is solved.Finally the validity of these methods is proven by the simulation results.     

Lung motion correction on respiratory gated 3-D PET/CT images

Motion is a source of degradation in positron emission tomography (PET)/computed tomography (CT) images. As the PET images represent the sum of information over the whole respiratory cycle, attenuation correction with the help of CT images may lead to false staging or quantification of the radioactive uptake especially in the case of small tumors. We present an approach avoiding these difficulties by respiratory-gating the PET data and correcting it for motion with optical flow algorithms. The resulting dataset contains all the PET information and minimal motion and, thus, allows more accurate attenuation correction and quantification.     

Registration and real-time visualization of transcranial magnetic stimulation with 3-D MR images

This paper describes a method for registering and visualizing in real-time the results of transcranial magnetic stimulations (TMS) in physical space on the corresponding anatomical locations in MR images of the brain. The method proceeds in three main steps. First, the patient scalp is digitized in physical space with a magnetic-field digitizer, following a specific digitization pattern. Second, a registration process minimizes the mean square distance between those points and a segmented scalp surface extracted from the magnetic resonance image. Following this registration, the physician can follow the change in coil position in real-time through the visualization interface and adjust the coil position to the desired anatomical location. Third, amplitude of motor evoked potentials can be projected onto the segmented brain in order to create functional brain maps. The registration has subpixel accuracy in a study with simulated data, while we obtain a point to surface root-mean-square error of 1.17+/-0.38 mm in a 24 subject study.     

Convolution backprojection formulas for 3-D vector tomography withapplication to MRI

Vector tomography is the reconstruction of vector fields from measurements of their projections. In previous work, it has been shown that the reconstruction of a general three-dimensional (3-D) vector field is possible from the so-called inner product measurements. It has also been shown how the reconstruction of either the irrotational or solenoidal component of a vector field can be accomplished with fewer measurements than that required for the full field. The present paper makes three contributions. First, in analogy to the two-dimensional (2-D) approach of Norton (1988), several 3-D projection theorems are developed. These lead directly to new vector field reconstruction formulas that are convolution backprojection formulas. It is shown how the local reconstruction property of these 3-D reconstruction formulas permits reconstruction of point flow or of regional flow from a limited data set. Second, simulations demonstrating 3-D reconstructions, both local and nonlocal, are presented. Using the formulas derived herein and those derived in previous work, these results demonstrate the reconstruction of the irrotational and solenoidal components, their potential functions, and the field itself from simulated inner product measurement data. Finally, it is shown how 3-D inner product measurements can be acquired using a magnetic resonance scanner     

复杂背景下兼顾跟踪实时性和跟踪精度的目标跟踪技术研究

由于将CamShift算法在复杂背景和操作条件下应用于视频跟踪,跟踪失败和目标损失的现象将非常容易发生。为了提高复杂环境条件下目标跟踪的精度及实时性,本论文提出了一种能够在复杂环境条件下及时对目标对象进行追踪的技术。以颜色、纹理、目标动作信息的全面特性为基础对CamShift算法作出整改完善,通过组合Kalman过滤器预评估目标对象的动作情况,在目标对象受到制约的情况下,使用运转前的目标对象预先信息,对目标对象物体的动作轨迹执行最小平方运算以及外穿推进,同时基于对象物体的位移情况进行定位信息的预测评估,以助于恢复目标的定位信息直到制约情况结束。经多次实验,相关统计数据表明,这一算法能够用于复杂情形的环境条件下,且当目标对象处于短期闭塞情况下依然能达成目标的连续稳定追踪,在性能上具备出色的实时性。     

Estimating 3-D respiratory motion from orbiting views by tomographic image registration

Respiratory motion remains a significant source of errors in treatment planning for the thorax and upper abdomen. Recently, we proposed a method to estimate two-dimensional (2-D) object motion from a sequence of slowly rotating X-ray projection views, which we called deformation from orbiting views (DOVs). In this method, we model the motion as a time varying deformation of a static prior of the anatomy. We then optimize the parameters of the motion model by maximizing the similarity between the modeled and actual projection views. This paper extends the method to full three-dimensional (3-D) motion and cone-beam projection views. We address several practical issues for using a cone-beam computed tomography (CBCT) scanner that is integrated in a radiotherapy system, such as the effects of Compton scatter and the limited gantry rotation for one breathing cycle. We also present simulation and phantom results to illustrate the performance of this method.     

Multiresolution 3-D reconstruction from side-scan sonar images.

In this paper, a new method for the estimation of seabed elevation maps from side-scan sonar images is presented. The side-scan image formation process is represented by a Lambertian diffuse model, which is then inverted by a multiresolution optimization procedure inspired by expectation-maximization to account for the characteristics of the imaged seafloor region. On convergence of the model, approximations for seabed reflectivity, side-scan beam pattern, and seabed altitude are obtained. The performance of the system is evaluated against a real structure of known dimensions. Reconstruction results for images acquired by different sonar sensors are presented. Applications to augmented reality for the simulation of targets in sonar imagery are also discussed.     

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.     

Analysis of 3-D myocardial motion in tagged MR images using nonrigid image registration

Tagged magnetic resonance imaging (MRI) is unique in its ability to noninvasively image the motion and deformation of the heart in vivo, but one of the fundamental reasons limiting its use in the clinical environment is the absence of automated tools to derive clinically useful information from tagged MR images. In this paper, we present a novel and fully automated technique based on nonrigid image registration using multilevel free-form deformations (MFFDs) for the analysis of myocardial motion using tagged MRI. The novel aspect of our technique is its integrated nature for tag localization and deformation field reconstruction using image registration and voxel based similarity measures. To extract the motion field within the myocardium during systole we register a sequence of images taken during systole to a set of reference images taken at end-diastole, maximizing the normalized mutual information between the images. We use both short-axis and long-axis images of the heart to estimate the full four-dimensional motion field within the myocardium. We also present validation results from data acquired from twelve volunteers.     

Reconstruction of 3-D left ventricular motion from planar tagged cardiac MR images: an estimation theoretic approach

Magnetic resonance (MR) tagging has shown great potential for noninvasive measurement of the motion of a beating heart. In MR tagged images, the heart appears with a spatially encoded pattern that moves with the tissue. The position of the tag pattern in each frame of the image sequence can be used to obtain a measurement of the 3-D displacement field of the myocardium. The measurements are sparse, however, and interpolation is required to reconstruct a dense displacement field from which measures of local contractile performance such as strain can be computed. Here, the authors propose a method for estimating a dense displacement field from sparse displacement measurements. Their approach is based on a multidimensional stochastic model for the smoothness and divergence of the displacement field and the Fisher estimation framework. The main feature of this method is that both the displacement field model and the resulting estimate equation are defined only on the irregular domain of the myocardium. The authors' methods are validated on both simulated and in vivo heart data.     

考虑目标运动状态的激光在线跟踪标刻方法

为了解决传统方法容易受到噪声、光照等因素影响,导致目标检测精度与标刻效果降低的问题,在考虑目标运动状态基础上提出一种激光在线跟踪标刻方法.首先根据激光点构建对应运动模型,并通过迭代计算求解获取出目标运动激光点和实际像素坐标,实现激光对实际目标的自主瞄准,并得出目标运动粗略范围;使用改进粒子滤波法进一步精细定位,由此计算...     

Boundary tracking in 3-D binary images to produce rhombic faces for a dodecahedral model

An algorithm is presented for tracking boundaries in three-dimensional binary images based on rhombic dodecahedral voxels. The algorithm produces a list of all the rhombic voxel faces in such a boundary.