基于B样条的冠状动脉树骨架三维重建方法

以B样条曲线为基元，根据两幅不同角度的冠脉造影图像重建冠状动脉树的三维骨架。首先采用B样条曲线的“迭代最近点拟合算法”拟合二维血管中心线，由二维控制点计算三维控制点，然后根据曲线拟合误差和对应点匹配误差优化三维B样条控制点，最后得到冠状动脉树三维骨架的B样条描述。利用临床冠脉造影图像进行冠脉树骨架的三维重建实验，结果表明本重建方法比传统方法在重建精度和算法复杂性上都有较大的改善。     

基于变形模型的心血管三维运动跟踪

提出一种心血管造影图像序列的三维运动跟踪方法。按照自顶向下的方式,采用三维变形模型,通过使适当的能量函数最小,表示血管骨架的曲线直接在三维空间中变形,完成血管骨架序列的三维重建。该方法将序列图像中血管的二维中心线提取、三维重建和运动跟踪集成到一个框架中完成,提高了重建精度和运算速度。     

弹性配准在冠状动脉三维运动分析中的应用

针对冠状动脉的运动分析问题,本文提出基于弹性配准的血管骨架三维运动估计方法.在对X射线冠脉造影图像序列进行三维血管骨架序列重建的基础上,寻找两个时刻同一血管分支上点之间的对应关系,得到各点的运动向量.通过使适当的目标函数最小化,运用动态规划算法,得到最优匹配.通过采用运动场已知的模拟数据对算法精度进行定量估计,并采用临床图像序列进行实验,结果表明,算法具有较高的精度和较快的运算速度.     

变形模型技术在冠状动脉造影图像序列后处理中的应用

以冠状动脉血管轴线的三维运动跟踪和心脏的形状建模为例,论述了变形模型在X射线心血管造影图像序列后处理中的应用.首先采用3D snake模型,表示血管轴线的曲线在三维空间中的变形,完成对血管骨架的序列重建.然后以各时刻的血管骨架点作为采样点,采用基于扩展超二次曲面的变形模型,建立心脏形状模型,通过分析不同时刻模型参数的变化,获得心脏变形参数的估计.     

冠状动脉树三维重建理论模型的研究

冠状动脉树的三维信息对于心血管疾病的评价和诊断具有十分重要的意义，研究了基于两幅冠脉造影图像重建三维冠状动脉树的理论模型，首先根据透视投影原理建立一个双平面冠脉造影系统的投影模型．并分析两幅不同角度的造影图像之间的几何变换关系。然后提出一种新型的深度求解方法．最后给出冠状动脉树模型的三维重建结果。     

造影图像序列中动脉血管的三维测量

针对X射线心血管造影图像的后处理问题,本文提出一种采用两个近似正交的单面X射线造影图像序列对冠状动脉的三维形状和运动参数进行定量测量的方法.该方法首先采用snake技术从两个角度的图像中重建出各时刻的三维血管轴线.根据三维重建和二维提取的结果,完成对血管形状参数(如长度和腔径)的测量.然后将血管运动场的估计转化为对相邻时刻间血管分支轴线的逐点匹配,并获得位移幅值和运动轨迹等重要参数.最后分别采用模型的X射线图像、计算机模拟数据和临床图像对该方法进行了验证.实验结果表明,该方法是可行的.     

应用血管内超声与X射线造影图像融合的血管三维重建

针对X射线血管造影和血管内超声各自显示血管形态的局限以及互补性问题,提出将两种数据进行融合,准确重建血管的方法。首先从在超声导管回撤路径起点拍摄的两个角度的造影图像对中提取出导管并进行三维重建。然后采用基于snake模型的半自动方法从各帧超声图像中提取出血管壁的内外膜边缘。最后,在Frenet-Serret标架中确定各相邻帧超声图像间的相对方位后,利用非迭代的统计优化方法确定各帧超声图像沿导管轴向的绝对方位,完成两种数据的融合。采用临床数据的实验结果验证了算法的可行性,并分析了可能存在的误差和计算成本。     

冠状动脉造影图像序列中估计二维运动及变形的弹性配准算法

提出一种由单面血管造影图像序列分析心脏冠状动脉运动和变形的方法，即利用弹性配准算法，将动脉运动的估计简化为对连续两帧图像的骨架像素的匹配．采用动态规划的方法进行配准，同时引入自回归建模，二者结合起来互相作用：动态规划为自回归模型参数的估计提供样本值；自回归模型为动态规划提供适当的成本函数。采用临床得到的单面冠状动脉造影图像序列对该算法进行了验证。实验结果表明应用该方法计算血管骨架图像中各点的光滑移动向量场，能够得到精确的结果。     

基于RGB-D值的三维图像重建系统研究

针对目前视频画面角度固定、缺乏深度和人机互动的问题,本文利用Microsoft Kinect体感摄像机可以同时获得彩色图像和深度图像的特点,搭建了基于多台Kinect的三维图像重建系统,实现了在DepthOfField10.1环境中可以手动旋转,看到不同视角的三维图像.本系统首先通过校准得到相机标定参数,然后将获取的彩色图像和深度图像进行自身数据融合生成一组三维点云数据,同时通过坐标转换将三维数据在世界坐标系中表示,再将多组点云数据进行融合重建,在进行重建的过程中运用纹理贴图技术进行渲染,得到3D图像.由此得到的立体图像可以通过旋转看到各个角度的三维图像,具有很强的立体感.通过对系统的初步实验验证了本系统的可行性.实验结果表明:本系统可以实现手动旋转三维图像,获取不同角度的三维画面,增强人机互动.     

基于51duino智能小车的三维场景重建

为了解决光学单目拍摄图像的物体相互遮挡、深度信息缺乏等问题,研究了基于51duino智能小车的三维场景重建方法.智能小车的核心控制器采用开源51duino开发平台,并搭载有单目光学摄像头、超声避障模块、光电寻迹模块与wifi传输模块.小车在行驶过程中,由不同角度拍下被测场景图像,经wifi模块将图像传回用户终端,并在用户终端采用SFM (Structure from Motion)算法得到场景的稀疏点云,再经CMVS (Cluster Multi-View Stereo)/PMVS (Patch-based Multi-View Stereo)稠密重建与泊松表面重建,得到场景的三维图像.通过两组测试验证了所提方法的正确性与可行性,获得了信息更丰富、可读性更强的场景三维图像.     

冠脉造影图像最佳造影角度的研究

冠心病是目前危害人类健康的首要疾病。在冠心病的临床诊断中,由于透视投影成像导致的血管缩短会引起血管段长度、血管直径和血管狭窄百分比等参数的二维定量分析结果错误,而血管缩短与造影角度的选择有关。因此,作者在冠状动脉树三维重建的基础上,利用平面拟合法计算感兴趣血管段最佳造影角度,并通过冠状动脉树实物模型进行实验。实验结果表明,最佳造影角度下的定量分析能够有效地提高临床医学参数的测量精度,用于指导介入性治疗。     

Digital holographic microtomography with few angle data-sets

In this paper, we report the experimental implementation of handling the reconstruction problem from few angle data-sets for digital holographic microtomography. First, the digital holographic microscopy with sample-rotating scheme is established and few holograms with regularly spaced angle steps are recorded. Then, an algebraic iterative reconstruction algorithm with non-positivity constraint and a smoothing operator is applied to reconstruct three-dimensional refractive index distribution of the measured sample from the few angle data-sets. The experimental results demonstrate that the algebraic iterative technique can accurately reconstruct refractive index distribution from few angle data-sets in digital holographic microtomography. The technique is easy to implement and reduces greatly the required recording times.     

On the phase interpolation problem — A brief review and some new results

Reconstruction of a signal from the phase of its Fourier transform is important and useful in a variety of practical applications. In this paper, we give a brief review of the previous results and develop some new ones pertaining to the phase-only reconstruction problem. The review includes conditions under which the signal is uniquely specified by its Fourier transform phase and some algorithms for performing the reconstruction. New results consist of an extension of a previous technique and an explicit formula for reconstruction. A number of potential applications of the reconstruction techniques are briefly mentioned in the concluding section. Throughout this paper, reference to the phase or magnitude of the signal should be interpreted, respectively, as the phase or magnitude of theft of the signal.     

Influence of the quantum uncertainty on the two-beams approach of reconstruction for one-photon mixed states of partially polarised light

Abstract

In this paper we discuss the reconstruction process of one-photon mixed states of partially polarised light. To solve this issue, we obtain the Stokes parameters by means of the degree of polarisation. The density operator describing the examined state is represented with these parameters. In the proposed two-beams method the degree of polarisation is measured on the analysed beam combined with reference beams containing photons with a settled state of polarisation. Coupling these beams allows one to obtain the Stokes parameters from the intensity contrast behind the rotating polariser. We discuss the influence of the quantum uncertainty on this technique of one-photon states reconstruction and we consider it for three aspects – the possibility of reducing the number of reference beams that are needed, the optimal state of polarisation of reference beams and the accuracy of the reconstruction method.     

Dual imaging modality of granular flow based on ECT sensors

In this study, a previously developed dual modality imaging system is applied to image the flow of granular matter with different electrical properties in cylindrical vessels. The imaging system is based on both capacitance and power measurements acquired by an electrical capacitance tomography (ECT) sensor located around the vessel. The measurement data are then used to reconstruct cross-sectional images of both permittivity and conductivity distributions. A neural network multi-criterion optimization reconstruction technique (NN-MOIRT) is used for the inverse (reconstruction) problem. The contribution of this technology to the field of granular matters is explored through review of research articles that can be a direct application of this development. We discuss the capabilities of this dual-modality acquisition system using synthetic data for granular matter with different electrical properties.     

A finite difference approach to acoustic tomography in anisotropic media

In this paper, a finite difference formulation for acoustic wave propagation is used as the basis for tomographic reconstruction. This approach offers some interesting advantages over traditional, ray based methods; particularly for anisotropic media. Since this approach provides information on the full acoustic field (not individual rays), it offers a conventional way to incorporate beam skew and ray bending phenomena directly into the problem formulation. Here, we present a tomographic reconstruction algorithm which is adapted from the algebraic reconstruction technique (ART) to take full advantage of the finite difference formulation of the problem. Results are presented to illustrate the utility of this approach.     

Electrical Capacitance Volume Tomography

A dynamic volume imaging based on the principle of electrical capacitance tomography (ECT), namely, electrical capacitance volume tomography (ECVT), has been developed in this study. The technique generates, from the measured capacitance, a whole volumetric image of the region enclosed by the geometrically three-dimensional capacitance sensor. This development enables a real-time, 3-D imaging of a moving object or a real-time volume imaging (4-D) to be realized. Moreover, it allows total interrogation of the whole volume within the domain (vessel or conduit) of an arbitrary shape or geometry. The development of the ECVT imaging technique primarily encloses the 3-D capacitance sensor design and the volume image reconstruction technique. The electrical field variation in three-dimensional space forms a basis for volume imaging through different shapes and configurations of ECT sensor electrodes. The image reconstruction scheme is established by implementing the neural-network multicriterion optimization image reconstruction (NN-MOIRT), developed earlier by the authors for the 2-D ECT. The image reconstruction technique is modified by introducing into the algorithm a 3-D sensitivity matrix to replace the 2-D sensitivity matrix in conventional 2-D ECT, and providing additional network constraints including 3-to-2-D image matching function. The additional constraints further enhance the accuracy of the image reconstruction algorithm. The technique has been successfully verified over actual objects in the experimental conditions     

Image reconstruction in three-dimensional magnetostatic permeability tomography

Magnetostatic permeability tomography is an imaging technique that attempts to reconstruct the permeability distribution of an object using magnetostatic measurement data. The data for image reconstruction are external magnetic field measurements on the surface of the object due to an applied magnetostatic field. Theoretically, the normal and tangential components of the magnetic field in the surface uniquely define the internal isotropic permeability distributions. However, the inverse permeability problem is an ill-posed nonlinear problem. Regularization is needed for a stable solution. In this paper, we present a numerical method to solve the reconstruction problem in three dimensions using a regularized Gauss-Newton scheme. We have solved the forward problem using an edge finite-element method and we have employed an efficient technique to calculate the Jacobian matrix. The permeability of the object is assumed to be linear and isotropic. We present the reconstruction results for the permeability using synthetically generated data with additive noise.