Contour reconstruction in 3-D X-ray CT

The authors derives an algorithm for reconstructing contours of an object from 3D cone beam X-ray data. By reducing the amount of the searched-for information, contours, or density jumps instead of the densities themselves, the authors are able to develop fast algorithms for data incomplete with respect to both the movement of the X-ray source and the detector reading. The method is related to local or Lambda tomography. Numerical simulations show the efficiency of the algorithm.     

A multichannel pipeline analog-to-digital converter for an integrated 3-D ultrasound imaging system

An 8-channel 10-bit pipeline analog-to-digital converter, designed for use in an integrated three-dimensional ultrasound imaging system, has been implemented in a 0.25-/spl mu/m CMOS technology. Two parallel multiplexing sample-and-hold stages are employed to multiplex a total of eight adjacent ultrasound channels, each sampled at 20 MHz. The sampled and multiplexed signals are fed into two parallel time-interleaved pipeline paths, each operating at 80 MHz. The two parallel pipelines are subsequently multiplexed into a single pipeline operating at 160 MHz to conserve area and reduce complexity. An experimental prototype of the proposed architecture occupies less than 4 mm/sup 2/ of active silicon area and shows a peak signal-to-noise-plus-distortion ratio more than 54 dB for a 2.1-MHz input signal, while dissipating only 20 mW of analog power per input channel from a 2.5-V supply.     

A novel system for thE 3-D reconstruction of the human spine and rib cage from biplanar X-ray images

The main objective of this study was to develop a 3-D X-ray reconstruction system of the spine and rib cage for an accurate 3-D clinical assessment of spinal deformities. The system currently used at Sainte-Justine Hospital in Montreal is based on an implicit calibration technique based on a direct linear transform (DLT), using a sufficiently large rigid object incorporated in the positioning apparatus to locate any anatomical structure to be reconstructed within its bounds. During the time lapse between the two successive X-ray acquisitions required for the 3-D reconstruction, involuntary patient motion introduce errors due to the incorrect epipolar geometry inferred from the stationary object. An approach using a new calibration jacket and explicit calibration algorithm is proposed in this paper. This approach yields accurate results and compensates for involuntary motion occurring between X-ray exposures.     

Rapid 3-D cone-beam reconstruction with the simultaneous algebraic reconstruction technique (SART) using 2-D texture mapping hardware

Algebraic reconstruction methods, such as the algebraic reconstruction technique (ART) and the related simultaneous ART (SART). reconstruct a two-dimensional (2-D) or three-dimensional (3-D) object from its X-ray projections. The algebraic methods have, in certain scenarios, many advantages over the more popular Filtered Backprojection approaches and have also recently been shown to perform well for 3-D cone-beam reconstruction. However, so far the slow speed of these iterative methods have prohibited their routine use in clinical applications. In this paper, we address this shortcoming and investigate the utility of widely available 2-D texture mapping graphics hardware for the purpose of accelerating the 3-D algebraic reconstruction. We find that this hardware allows 3-D cone-beam reconstructions to be obtained at almost interactive speeds, with speed-ups of over 50 with respect to implementations that only use general-purpose CPUs. However, we also find that the reconstruction quality is rather sensitive to the resolution of the framebuffer, and to address this critical issue we propose a scheme that extends the precision of a given framebuffer by 4 bits, using the color channels. With this extension, a 12-bit framebuffer delivers useful reconstructions for 0.5% tissue contrast, while an 8-bit framebuffer requires 4%. Since graphics hardware generates an entire image for each volume projection, it is most appropriately used with an algebraic reconstruction method that performs volume correction at that granularity as well, such as SART or SIRT. We chose SART for its faster convergence properties.     

双目下点云的三维人脸重建

提出一种在双目视觉系统下进行人脸重建的方法。首先,通过双目系统拍摄人脸的左右图像;其次,用Grab-Cut的方法的把人脸图像分割出来从而降低立体匹配的搜索范围;然后,用区域匹配算法得到人脸的视差图,从而得到人脸的三维点云;最后对不同角度的人脸图像进行SIFT特征提取和匹配。将提取的SIFT特征点和匹配关系反射到三维点云数据,获取不同角度人脸的三维点云数据的特征点和匹配关系,完成对不同角度的人脸进行粗配准。     

Interior-point methodology for 3-D PET reconstruction

Interior-point methods have been successfully applied to a wide variety of linear and nonlinear programming applications. This paper presents a class of algorithms, based on path-following interior-point methodology, for performing regularized maximum-likelihood (ML) reconstructions on three-dimensional (3-D) emission tomography data. The algorithms solve a sequence of subproblems that converge to the regularized maximum likelihood solution from the interior of the feasible region (the nonnegative orthant). We propose two methods, a primal method which updates only the primal image variables and a primal-dual method which simultaneously updates the primal variables and the Lagrange multipliers. A parallel implementation permits the interior-point methods to scale to very large reconstruction problems. Termination is based on well-defined convergence measures, namely, the Karush-Kuhn-Tucker first-order necessary conditions for optimality. We demonstrate the rapid convergence of the path-following interior-point methods using both data from a small animal scanner and Monte Carlo simulated data. The proposed methods can readily be applied to solve the regularized, weighted least squares reconstruction problem.     

Analysis of a 3-D system function measured for magnetic particle imaging

Magnetic particle imaging (MPI) is a new tomographic imaging approach that can quantitatively map magnetic nanoparticle distributions in vivo. It is capable of volumetric real-time imaging at particle concentrations low enough to enable clinical applications. For image reconstruction in 3-D MPI, a system function (SF) is used, which describes the relation between the acquired MPI signal and the spatial origin of the signal. The SF depends on the instrumental configuration, the applied field sequence, and the magnetic particle characteristics. Its properties reflect the quality of the spatial encoding process. This work presents a detailed analysis of a measured SF to give experimental evidence that 3-D MPI encodes information using a set of 3-D spatial patterns or basis functions that is stored in the SF. This resembles filling 3-D k-space in magnetic resonance imaging, but is faster since all information is gathered simultaneously over a broad acquisition bandwidth. A frequency domain analysis shows that the finest structures that can be encoded with the presented SF are as small as 0.6 mm. SF simulations are performed to demonstrate that larger particle cores extend the set of basis functions towards higher resolution and that the experimentally observed spatial patterns require the existence of particles with core sizes of about 30 nm in the calibration sample. A simple formula is presented that qualitatively describes the basis functions to be expected at a certain frequency.     

3-D reconstruction of 2-D crystals in real space

A new algorithm for three-dimensional reconstruction of two-dimensional crystals from projections is presented, and its applicability to biological macromolecules imaged using transmission electron microscopy (TEM) is investigated. Its main departures from the traditional approach is that it works in real space, rather than in Fourier space, and it is iterative. This has the advantage of making it convenient to introduce additional constraints (such as the support of the function to be reconstructed, which may be known from alternative measurements) and has the potential of more accurately modeling the TEM image formation process. Phantom experiments indicate the superiority of the new approach even without the introduction of constraints in addition to the projection data.     

三维封装中引线键合技术的实现与可靠性

结合半导体封装的发展,研究了低线弧、叠层键合、引线上芯片、外悬芯片、长距离键合和双面键合6种引线互连封装技术;分析了各种引线键合的技术特点和可靠性.传统的引线键合技术通过不断地改进,成为三维高密度封装中的通用互连技术,新技术的出现随之会产生一些新的可靠性问题;同时,对相应的失效分析技术也提出了更高的要求.多种互连引线键合技术的综合应用,满足了半导体封装的发展需求;可靠性是技术应用后的首要技术问题.     

Ray phase space approach for 3-D imaging and 3-D optical data representation

We propose a framework to model, analyze and design three-dimensional (3-D) imaging systems. A system engineering approach is adopted which relates 3-D images (real or synthesized) to 3-D objects (real or synthesized) using a novel representation of the optical data which we call "ray phase space". The framework provides a powerful tool for determining the performance of 3-D imaging systems, for generating computational reconstruction of 3-D images and for optimizing 3-D imaging systems.     

Vibrating varifocal mirrors for 3-D imaging

As technology advances, the interactions between man and machine become more complex. A reliable three-dimensional man-machine interface could help alleviate some of the complexity; but an effective 3-D display has, so far, eluded technologists. Thus, we have been forced to make unnatural compromises when dealing with data that are essentially three-dimensional in nature. This article describes a system that may meet the autostereoscopic display requirements in many situations.     

3-D reconstruction of microcalcification clusters using stereo imaging: algorithm and mammographic unit calibration

The three-dimensional (3-D) shape of microcalcification clusters is an important indicator in early breast cancer detection. In fact, there is a relationship between the cluster topology and the type of lesion (malignant or benign). This paper presents a 3-D reconstruction method for such clusters using two 2-D views acquired during standard mammographic examinations. For this purpose, the mammographic unit was modeled using a camera with virtual optics. This model was used to calibrate the acquisition unit and then to reconstruct the clusters in the 3-D space after microcalcification segmentation and matching. The proposed model is hardware independent since it is suitable for digital mammographic units with different geometries and with various physical acquisition principles. Three-dimensional reconstruction results are presented here to prove the validity of the method. Tests were first performed using a phantom with a well-known geometry. The latter contained X-ray opaque glass balls representing microcalcifications. The positions of these balls were reconstructed with a 16.25-microm mean accuracy. This very high inherent algorithm accuracy is more than enough for a precise 3-D cluster representation. Further validation tests were carried out using a second phantom including a spherical cluster. This phantom was built with materials simulating the behavior of both mammary tissue and microcalcifications toward Xrays. The reconstructed shape was effectively spherical. Finally, reconstructions were carried out for real clusters and their results are also presented.     

Planar mirrors for image-based robot localization and 3-D reconstruction

Planar catadioptric vision sensors consist of a pinhole camera observing a scene being reflected on two (or more) planar mirrors. These systems have recently received an increasing attention because, unlike stereo cameras, can capture two views of the same scene without the need of hardware multi-camera synchronization and calibration. In this paper we explore the original scenario in which a robot manipulator, equipped with a pinhole camera on its end-effector, observes an unknown 3-D scene both directly and reflected through multiple mirrors. We present new multiple-view properties for this scenario and, based on these theoretical results, we present new image-based camera localization and new 3-D scene reconstruction algorithms. Extensive simulation and real-data experiments illustrate the theory and show the effectiveness of the proposed designs.     

A 3-D reconstruction system for the human jaw using a sequence of optical images

This paper presents a model-based vision system for dentistry that will assist in diagnosis, treatment planning, and surgical simulation. Dentistry requires an accurate three-dimensional (3-D) representation of the teeth and jaws for diagnostic and treatment purposes. The proposed integrated computer vision system constructs a 3-D model of the patient's dental occlusion using an intraoral video camera. A modified shape from shading (SFS) technique, using perspective projection and camera calibration, extracts the 3-D information from a sequence of two-dimensional (2-D) images of the jaw. Data fusion of range data and 3-D registration techniques develop the complete jaw model. Triangulation is then performed, and a solid 3-D model is reconstructed. The system performance is investigated using ground truth data, and the results show acceptable reconstruction accuracy.     

A neural-learning-based reflectance model for 3-D shape reconstruction

In this letter, the limitation of the conventional Lambertian reflectance model is addressed and a new neural-based reflectance model is proposed of which the physical parameters of the reflectivity under different lighting conditions are interpreted by the neural network behavior of the nonlinear input-output mapping. The idea of this method is to optimize a proper reflectance model by a neural learning algorithm and to recover the object surface by a simple shape-from-shading (SFS) variational method with this neural-based model. A unified computational scheme is proposed to yield the best SFS solution. This SFS technique has become more robust for most objects, even when the lighting conditions are uncertain.     

Optimal CT scanning plan for long-bone 3-D reconstruction

Digital computed tomographic (CT) data are widely used in three-dimensional (3-D) construction of bone geometry and density features for 3-D modelling purposes. During in vivo CT data acquisition the number of scans must be limited in order to protect patients from the risks related to X-ray absorption. The aim of this work is to automatically define, given a finite number of CT slices, the scanning plan which returns the optimal 3-D reconstruction of a bone segment from in vivo acquired CT images. An optimization algorithm based on a Discard-Insert-Exchange technique has been developed. In the proposed method the optimal scanning sequence is searched by minimizing the overall reconstruction error of a two-dimensional (2-D) prescanning image: an anterior-posterior (AP) X-ray projection of the bone segment. This approach has been validated in vitro on 3 different femurs. The 3-D reconstruction errors obtained through the optimization of the scanning plan on the 3-D prescanning images and on the corresponding 3-D data sets have been compared. 2-D and 3-D data sets have been reconstructed by linear interpolation along the longitudinal axis. Results show that direct 3-D optimization yields root mean square reconstruction errors which are only 4%-7% lower than the 2-D-optimized plan, thus proving that 2-D-optimization provides a good suboptimal scanning plan for 3-D reconstruction. Further on, 3-D reconstruction errors given by the optimized scanning plan and a standard radiological protocol for long bones have been compared. Results show that the optimized plan yields 20%-50% lower 3-D reconstruction errors     

Coherent 3-D echo detection for ultrasonic imaging

The purpose of the present paper is to present an ultrasonic processing set-up by which three-dimensional (3-D) echo location can be computed more efficiently than by other one-dimensional (1-D) methods. This set-up contains three successive tasks. The first one deals with a model for representing echoes. This model is based on a generic wavelet, which is a cosine function with variable amplitude and phase. To estimate the wavelet, we propose to use a spline representation of its complex envelope in order to reduce amplitude and phase dimension. The second task deals with 1-D detection and is conducted within a Bayesian framework. Using an Ascan decomposition on a family of wavelets resulting from the first task, we propose a specific procedure to carry on constrained least-squares in order to alleviate the bias inherent to this criterion. The third task deals with the spatial regularization of the detected echo location field resulting from the second task. We propose a Bayes-Markov model for removing isolated wrong detections and simultaneously improving, under regularization constraint, the spatial location of the detected echoes. In fact, this model deals with the general problem of nonorganized point approximation. All the proposed techniques are illustrated on real ultrasonic data.     

X光序列图像三维动态滤波技术

对于静态X光图像序列,帧间滤波技术是抑制噪声、提高信噪比最为有效的方法之一。然而对于活动图像序列,该技术会使运动目标模糊,从而使图像质量更差。本文提出了一种X光序列图像的三维动态滤波技术,把图像序列作为二维空间数据流,在时间上采用先进先出的方式在整个积分周期内进行多帧平均,实现了沿着运动轨迹进行帧间滤波,从而使多帧平均技术对于活动X光图像序列同样具有较好的处理效果。     

Three-dimensional (3-D) reconstruction of the spine from a single X-ray image and prior vertebra models

The lateral bending test is routinely used by clinicians for the preoperative assessment of spinal mobility. The evaluation of bending motion is usually based on the qualitative analysis of a two-dimensional (2-D) antero-posterior X-ray image. The aim of this paper is to introduce a novel three-dimensional (3-D) reconstruction technique that is a prerequisite for the quantitative 3-D analysis of lateral bending motion. An algorithm was developed for the 3-D reconstruction of the spine from a single X-ray image. The X-ray is calibrated using a small calibration object and an explicit calibration algorithm. The information contained in the single X-ray is completed by registering a priori 3-D geometric models of individual vertebrae. Part of the error yielded by the 3-D/2-D registration is corrected by a vertebral alignment constraint that aims to minimize intervertebral dislocations. Three-dimensional models of 15 different scoliosis patients, obtained from a standard stereo-radiographic 3-D reconstruction, were used in simulation and validation experiments. Experimental results show that the new method is robust and accurate. With pessimistic levels of simulated noise, the average root mean square reconstruction error is 2.89 mm, which is appropriate for common clinical applications.