Fully automated motion correction in first-pass myocardial perfusion MR image sequences

This paper presents a novel method for registration of cardiac perfusion magnetic resonance imaging (MRI). The presented method is capable of automatically registering perfusion data, using independent component analysis (ICA) to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of that ICA. This reference image is used in a two-pass registration framework. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Despite varying image quality and motion patterns in the evaluation set, validation of the method showed a reduction of the average right ventricle (LV) motion from ${1.26}pm{0.87}$ to ${0.64}pm{0.46}$ pixels. Time-intensity curves are also improved after registration with an average error reduced from ${2.65}pm {7.89}%$ to ${0.87}pm {3.88}%$ between registered data and manual gold standard. Comparison of clinically relevant parameters computed using registered data and the manual gold standard show a good agreement. Additional tests with a simulated free-breathing protocol showed robustness against considerable deviations from a standard breathing protocol. We conclude that this fully automatic ICA-based method shows an accuracy, a robustness and a computation speed adequate for use in a clinical environment.      

Estimating motion in image sequences

We have reviewed the estimation of 2D motion from time-varying images, paying particular attention to the underlying models, estimation criteria, and optimization strategies. Several parametric and nonparametric models for the representation of motion vector fields and motion trajectory fields have been discussed. For a given region of support, these models determine the dimensionality of the estimation problem as well as the amount of data that has to be interpreted or transmitted thereafter. Also, the interdependence of motion and image data has been addressed. We have shown that even ideal constraints may not provide a well-defined estimation criterion. Therefore, the data term of an estimation criterion is usually supplemented with a smoothness term that can be expressed explicitly or implicitly via a constraining motion model. We have paid particular attention to the statistical criteria based on Markov random fields. Because the optimization of an estimation criterion typically involves a large number of unknowns, we have presented several fast search strategies     

Simultaneous motion estimation and filtering of image sequences

We present an algorithm to simultaneously estimate multiple-frame motions and filter image sequences. The relative motion d(k)(x) between the reference frame s(x) and the kth frame s(x-d(k)(x)) in the presence of additive white Gaussian noise (AWGN) is estimated using the maximum-likelihood (ML) principle. The reference frame is also filtered in the linear minimum mean square error (LMMSE) sense during the process of motion estimation. Simulation experiments are performed using the affine motion model to illustrate the performance of this method.     

气泡尾流光束衰减测量中的复散射校正

为了分析复散射对气泡尾流衰减测量的影响,采用小角度辐射传输方程,引入了表征复散射效应强弱的校正因子,通过数值求解分析了典型的尾流气泡尺度分布和数密度条件下复散射校正因子与接收视场角、光学厚度、光束大小和接收截面大小等参量之间的关系。结果表明,接收视场角在前向小角度范围内的变化对复散射校正因子的影响很大,而视场角较大时对复散射校正因子的影响基本相同;光学厚度的变化对复散射校正因子的影响显著,且在光学厚度小于1时,影响更明显;接收截面大小的变化在光学厚度小于1时对复散射校正因子的影响很小,但在光学厚度较大时,对复散射校正因子的影响比较明显;光束大小的变化对复散射因子的影响相对较小,且在光束束腰较大时对复散射因子的影响基本不变。该研究为尾流光束衰减测量条件的选择和优化提供了理论依据。     

采用序列图像的被动光学测速技术

在获取无人机等飞行器的飞行速度时,自主、隐蔽性好的测量技术具有重要的应用价值。提出了一种利用光学相机拍摄的地面景象进行飞行器速度测量的技术。文中详细阐述了该项技术的工作原理,利用同一景物在两幅有重叠区域的图像中的位移量及间隔时间计算飞行器的运动速度。并且分析了其中关键的图像匹配技术,采用SIFT算法获得抗旋转、尺度变化的稳定特征点。重点对测速精度的各个影响因素进行了理论分析,给出了利用多帧图像进行测速提高测速精度的方法,综合分析了速度测量中的误差来源和各影响因素。理论研究和分析结果表明:利用光学图像进行速度测算的方案正确,精度能够满足飞行器速度测量的要求。     

Nonuniformity correction of infrared image sequences using theconstant-statistics constraint

Using clues from neurobiological adaptation, we have developed the constant-statistics (CS) algorithm for nonuniformity correction of infrared focal point arrays (IRFPAs) and other imaging arrays. The CS model provides an efficient implementation that can also eliminate much of the ghosting artifact that plagues all scene-based nonuniformity correction (NUC) algorithms. The CS algorithm with deghosting is demonstrated on synthetic and real infrared (IR) sequences and shown to improve the overall accuracy of the correction procedure.     

Rigid and non-rigid 3D motion estimation from multiview image sequences

Multiview image sequence processing has been the focus of considerable attention in recent literature. This paper presents an efficient technique for object-based rigid and non-rigid 3D motion estimation, applicable to problems occurring in multiview image sequence coding applications. More specifically, a neural network is formed for the estimation of the rigid 3D motion of each object in the scene, using initially estimated 2D motion vectors corresponding to each camera view. Non-linear error minimization techniques are adopted for neural network weight update. Furthermore, a novel technique is also proposed for the estimation of the local non-rigid deformations, based on the multiview camera geometry. Experimental results using both stereoscopic and trinocular camera setups illustrate and evaluate the proposed scheme.     

Noise reduction of image sequences using motion compensation andsignal decomposition

In this paper, a new spatio-temporal filtering method for removing noise from image sequences is proposed. This method combines the use of motion compensation and signal decomposition to account for the effects of object motion. Because of object motion, image sequences are temporally nonstationary, which requires the use of adaptive filters. By motion compensating the sequence prior to filtering, nonstationarities, i.e., parts of the signal that are momentarily not stationary, can be reduced significantly. However, since not all nonstationarities can be accounted for by motion, a motion-compensated signal still contains nonstationarities. An adaptive algorithm based on order statistics is described that decomposes the motion-compensated signal into a noise-free nonstationary part and a noisy stationary part. An RLS filter is then used to filter the noise from the stationary signal. Our new method is experimentally compared with various noise filtering approaches from literature.     

Iso-shaping rigid bodies for estimating their motion from image sequences

In many medical imaging applications, due to the limited field of view of imaging devices, acquired images often include only a part of a structure. In such situations, it is impossible to guarantee that the images will contain exactly the same physical extent of the structure at different scans, which leads to difficulties in registration and in many other tasks, such as the analysis of the morphology, architecture, and kinematics of the structures. To facilitate such analysis, we developed a general method, referred to as iso-shaping, that generates structures of the same shape from segmented image sequences. The basis for this method is to automatically find a set of key points, called shape centers, in the segmented partial anatomic structure such that these points are present in all images and that they represent the same physical location in the object, and then trim the structure using these points as reference. The application area considered here is the analysis of the morphology, architecture, and kinematics of the joints of the foot from magnetic resonance images acquired at different joint positions and load conditions. The accuracy of the method is analyzed by utilizing ten data sets for iso-shaping the tibia and the fibula via four evaluative experiments. The analysis indicates that iso-shaping produces results as predicted by the theoretical framework.     

Semi-automatic foreground/background segmentation of motion picture images and image sequences

Segmentation of images into foreground (an actor) and background is required for many motion picture special effects. To produce these shots, the unwanted background must be removed so that none of it appears in the final composite shot. The standard approach requires the background to be a blue screen. Systems that are capable of segmenting actors from more natural backgrounds have been proposed, but many of these are not readily adaptable to the resolution involved in motion picture imaging. An algorithm is presented that requires minimal human interaction to segment motion picture resolution images. Results from this algorithm are quantitatively compared with alternative approaches. Adaptations to the algorithm, which enable segmentation even when the foreground is lit from behind, are described. Segmentation of image sequences normally requires manual creation of a separate hint image for each frame of a sequence. An algorithm is presented that generates such hint images automatically, so that only a single input is required for an entire sequence. Results are presented that show that the algorithm successfully generates hint images where an alternative approach fails.     

数字全变分滤波在红外图像序列非均匀校正中的应用

红外焦平面阵列上的空间非均匀性,即固定图案噪声,严重影响了红外系统的成像质量。为此提出了一种新的非均匀校正算法,它借鉴了图像处理中的图像去噪思想,把数字全变分滤波器引入非均匀校正。鉴于数字全变分滤波的执行过程一般都是自我迭代,而考虑到校正算法的实时性要求,无法对单帧图像实施多次处理。故而将以前的空间迭代形式转化为时间递推,以达到逐帧去除固定图案噪声的目的。使用仿真和真实红外图像序列对算法性能进行验证,实验结果表明:该算法从第15帧开始就能够达到较好的校正水平,并且在未优化条件下,每秒钟处理30帧图像仅需300M个指令周期。因此具有收敛速度快、计算复杂度低等优点。     

A digital video system for the automated measurement of repetitive joint motion

Automated measurement and analysis of human motion during performance of workplace tasks are desirable for ergonomic studies. While numerous technologies exist for accurate measurement of biomechanical data, their use is often not feasible in the workplace environment. We present a digital-video based system suitable for measuring human motion of repetitive workplace tasks. Due to practical considerations, a single-camera solution is exploited by adding some control over the environment. We present an analysis of experiments demonstrating the accuracy of our system.     

利用码分多址联合变换相关器实现亚像元像移测量

光学联合变换器(JTC)是实现空间相机推扫成像时像移实时测量的有效技术手段。JTC-CDMA是一种改进的光学联合变换相关器。它通过码分多址技术能够有效降低整个JTC系统的空间带宽积,并实现自相关峰和互相关峰影像的分离,有利于系统的小型化。对JTC-CDMA的基本工作原理进行了分析,并讨论了该技术用于像移测量时所存在的问题。针对这些问题,提出了新的像移测量方法。通过计算机仿真实验对新方法的可行性进行了评估,结果表明:在沿航和穿航两个方向的像移测量RMS误差均低于0.1个像元,完全能够满足空间相机对像移测量低于0.2个像元的要求。     

A Robust hierarchical motion estimation algorithm in noisy image sequences in the bispectrum domain

The present study describes a robust hierarchical motion estimation algorithm in noisy image sequences using the bispectrum. The motion can be characterized by an affine model and the parameters of an affine motion model are estimated by means third-order auto-bispectrum and cross-bispectrum measures. The basic components of this framework to obtain motion vectors are (i) pyramid construction, (ii) motion estimation and (iii) coarse-to-fine refinement. The entire motion is decomposed as a global and a local motion field, which helps accurately obtain high resolution estimates for the local motion field. Simulation results are presented and compared to those obtained from the phase correlation algorithm. The results demonstrate that the proposed method is more suited than the phase correlation algorithm to analyses complex noisy image sequences. On the other hand, our method produces smoother displacement vector field with a more accurate measure of object motion in different signal-to-noise ratio scenarios.     

Optimal search in Hough parameter hyperspace for estimation of complex motion in image sequences

The paper is a contribution to the theory of multiparameter motion estimation using the Hough transform technique and its main feature is the analytic development of closed-form solutions for the optimal estimation strategy. Motion estimation in image sequences using the Hough transform is reviewed. Various motion models are considered offering a more realistic portrayal of camera and scene motion compared with the purely translational models adopted by standardised video coding algorithms. Since the computational complexity arising from the use of such sophisticated models is prohibitive, standard optimisation techniques are used for the search of minima of the motion estimation error function in the Hough parameter hyperspace. In contrast to previously published work, second-order Taylor expansions of the error function are considered. By taking into account such second-order terms the optimal iterative step for a gradient search in the Hough parameter hyperspace is determined for all the motion models of interest. For a purely translational model it is demonstrated that the analysis provides a similar estimate to that of the well-known Netravali and Robbins algorithm. For more complex motion models it is shown that the computation of the optimal solution involves modest complexity.     

Automatic extraction and measurement of leukocyte motion inmicrovessels using spatiotemporal image analysis

This paper describes a computer vision system for the automatic extraction and velocity measurement of moving leukocytes that adhere to microvessel walls from a sequence of images. The motion of these leukocytes can be visualized as motion along the wall contours. The authors use the constraint that the leukocytes move along the vessel wall contours to generate a spatiotemporal image, and the leukocyte motion is then extracted using the methods of spatiotemporal image analysis. The generated spatiotemporal image is processed by a special-purpose orientation-selective filter and a subsequent grouping process newly developed for this application. The orientation-selective filter is designed by considering the particular properties of the spatiotemporal image in this application in order to enhance only the traces of leukocytes. In the subsequent grouping process, leukocyte trace segments are selected and grouped among all the segments obtained by simple thresholding and skeletonizing operations. The authors show experimentally that the proposed method can stably extract leukocyte motion     

顾及BRDF和大气影响的摆扫式航空高光谱边缘辐射畸变校正

讨论了顾及传输路径差异和方向性反射差异的边缘辐射校正方法,并根据POS数据改正了由于姿态变化引起的边缘畸变.以实用型模块化成像光谱仪(Operational Modular Imaging Spectrometer,OMIS-Ⅲ)影像为例,采用上述方法进行边缘校正,最后采用近似同一扫描行上的同类地物光谱进行对比,得出校正后的光谱吻合度比校正前更高.     

Point-tracked quantitative analysis of left ventricular surface motion from 3-D image sequences

We propose and validate the hypothesis that we can use differential shape properties of the myocardial surfaces to recover dense field motion from standard three-dimensional (3-D) image sequences (MRI and CT). Quantitative measures of left ventricular regional function can be further inferred from the point correspondence maps. The noninvasive, algorithm-derived results are validated on two levels. First, the motion trajectories are compared to those of implanted imaging-opaque markers of a canine model in two imaging modalities, where subpixel accuracy is achieved. Second, the validity of using motion parameters (path length and thickness changes) for detecting myocardial injury area is tested by comparing algorithms derived results to postmortem analysis TTC staining of myocardial tissue, where the achieved Pearson product-moment correlation value is 0.968.