Parallel computing approach for efficient 3-D X-ray-simulated image reconstruction

Accurate 3-dimensional(3-D)reconstruction technology for nondestructive testing based on digital radiography(DR)is of great importance for alleviating the drawbacks of the existing computed tomography(CT)-based method.The commonly used Monte Carlo simulation method ensures well-performing imaging results for DR.However,for 3-D reconstruction,it is limited by its high time consumption.To solve this problem,this study proposes a parallel computing method to accelerate Monte Carlo simulation for projection images with a parallel interface and a specific DR application.The images are utilized for 3-D reconstruction of the test model.We verify the accuracy of parallel computing for DR and evaluate the performance of two parallel computing modes-multithreaded applications(G4-MT)and message-passing interfaces(G4-MPI)-by assessing parallel speedup and efficiency.This study explores the scalability of the hybrid G4-MPI and G4-MT modes.The results show that the two parallel computing modes can significantly reduce the Monte Carlo simulation time because the parallel speedup increment of Monte Carlo simulations can be considered linear growth,and the parallel efficiency is maintained at a high level.The hybrid mode has strong scalability,as the overall run time of the 180 simulations using 320 threads is 15.35 h with 10 billion particles emitted,and the parallel speedup can be up to 151.36.The 3-D reconstruction of the model is achieved based on the filtered back projection(FBP)algorithm using 180 projection images obtained with the hybrid G4-MPI and G4-MT.The quality of the reconstructed sliced images is satisfactory because the images can reflect the internal structure of the test model.This method is applied to a complex model,and the quality of the reconstructed images is evaluated.

Using on-site liver 3-D reconstruction and volumetric calculations in split liver transplantation

BACKGROUND： Split liver transplantation increases the number of grafts available for transplantation. Pre-recovery assessment of liver graft volume is essential for selecting suitable recipients. The purpose of this study was to determine the ability and feasibility of constructing a 3-D model to aid in surgical planning and to predict graft weight prior to an in situ division of the donor liver. METHODS： Over 11 months, 3-D volumetric reconstruction of 4 deceased donors was performed using Pathfinder Scout liver volumetric software. Demographic, laboratory, operative, perioperative and survival data for these patients along with donor demographic data were collected prospectively and analyzed retrospectively. RESULTS： The average predicted weight of the grafts from the adult donors obtained from an in situ split procedure were 1130 g （930-1458 g） for the extended right lobe donors and 312 g （222-396 g） for left lateral segment grafts. Actual adult graft weight was 92% of the predicted weight for both the extended right grafts and the left lateral segment grafts. The predicted and actual graft weights for the pediatric donors were 176 g and 210 g for the left lateral segment grafts and 308 g and 280 g for the extended right lobe grafts,respectively. All grafts were transplanted except for the right lobe from the pediatric donors due to the small graft weight.CONCLUSIONS： On-site volumetric assessment of donors provides useful information for the planning of an in situ split and for selection of recipients. This information may expand the donor pool to recipients previously felt to be unsuitable due to donor and/or recipient weight.

PCA-based 3D Shape Reconstruction of Human Foot Using Multiple Viewpoint Cameras

This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, which can characterize more than 92% of a foot, are defined by using the principal component analysis method. Then, using ＂active shape models＂, the initial 3D model is adapted to the real foot captured in multiple images by applying some constraints （edge points＇ distance and color variance）. We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and also on real human feet with various shapes. We propose and compare different ways of texturing the foot which is needed for reconstruction. We present an experiment performed on the plastic foot model and on human feet and propose two different ways to improve the final 3D shapers accuracy according to the previous experiments＇ results. The first improvement proposed is the densification of the cloud of points used to represent the initial model and the foot database. The second improvement concerns the projected patterns used to texture the foot. We conclude by showing the obtained results for a human foot with the average computed shape error being only 1.06 mm.

FEMUR SHAPE RECOVERY FROM VOLUMETRIC IMAGES USING 3-D DEFORMABLE MODELS

A new scheme for femur shape recovery from volumetric images using deformable models was proposed. First, prior 3 D deformable femur models are created as templates using point distribution models technology. Second, active contour models are employed to segment the magnetic resonance imaging (MRI) volumetric images of the tibial and femoral joints and the deformable models are initialized based on the segmentation results. Finally, the objective function is minimized to give the optimal results constraining the surface of shapes.

A 3-D RECONSTRUCTION METHOD BASED ON THE CONSTRAINT OF EPIPOLAR GEOMETRY

This paper combines the least-square method and iteration method to get the fundamental matrix and develops a new evaluation function based on the epipolar geometry. During the iteration, with the evaluation function as a measurment, the points which bring larger noise are deleted, and the points with smaller noise are retained, thus the precision of our method is increased. The experiment results indicate the new method is precise in calculation, stable in performance and resistant to noise.

EFFECT OF SUBMERGED ENTRY NOZZLE (SEN) PARAMETERS AND SHAPE ON 3-D FLUID FLOW IN MOULD FOR BEAM BLANK CONTINUOUS CASTING

According to turbulent theory and characteristics of beam blank continuous casting, 3-D model to represent the flow of beam blank mould is established. The predicted results indicate that the exit obliquity of up 15°(+15°) should be adopted, which will benefit the floatation of non-metallic inclusion and purification of the molten steel. When the nozzle angle is 120°, the flow pattern is reasonable. Proper nozzle depth can be 200mm. Turbulent kinetic of meniscus can be reduced by adopting the square nozzle and suitable area of side outlet when casting speed increases. The results are consistent with those of water model experiment, so the model is exact and reasonable. The model can provide important information for design of SEN and defining of immersion depth.

3-D Reconstruction and Visualization of Laser-Scanned Trees by Weighted Locally Optimal Projection and Accurate Modeling Method

This paper presents a method to reconstruct 3-D models of trees from terrestrial laser scan(TLS)point clouds.This method uses the weighted locally optimal projection(WLOP)and the AdTree method to reconstruct detailed 3-D tree models.To improve its representation accuracy,the WLOP algorithm is introduced to consolidate the point cloud.Its reconstruction accuracy is tested using a dataset of ten trees,and the one-sided Hausdorff distances between the input point clouds and the resulting 3-D models are measured.The experimental results show that the optimal projection modeling method has an average one-sided Hausdorff distance(mean)lower by 30.74%and 6.43%compared with AdTree and AdQSM methods,respectively.Furthermore,it has an average one-sided Hausdorff distance(RMS)lower by 29.95%and 12.28%compared with AdTree and AdQSM methods.Results show that the 3-D model generated fits closely to the input point cloud data and ensures a high geometrical accuracy.

Reconstruction of Temperature Field in 3-D, Absorbing, Emitting, and Anisotropically Scattering Medium

The soft measurement technology of flame temperature field is an efficient method to learn the combustion status in furnace. Generally, it reconstructs the temperature field in furnace through the image of flame, which is a process to solve radiative inverse problem. In this paper, the flame of pulverized coal is considered as 3-D, absorbing, emitting, and anisotropically scattering non-gray medium. Through the study on inverse problem of radiative heat transfer, the temperature field in this kind of medium has been reconstructed. The mechanism of 3-D radiative heat transfer in a rectangular media, which is 2 m×3 m× 5 m and full of CO2, N2 and carbon particles, is studied with Monte Carlo method. The 3-D temperature field in this rectangular space is reconstructed and the influence of particles density profile is discussed.

ACQUIREMENT AND COMPUTER PROCESSING OF 3-D SURFACE SHAPE DATA

The laser scanning and CCD image-transmitting measurement method and principle on acquiring 3-D curved surface shape data are discussed. Computer processing technique of 3-D curved surface shape(be called“ 3 - D surface shape”for short) data is analysed. This technique in- cludes these concrete methods and principles such as data smoothing, fitting, reconstructing ,elimi- nating and so on. The example and result about computer processing of 3- D surface shape data are given .

Part-level 3-D object classification with improved interpretation tree

For classifying unknown 3-D objects into a set of predetermined object classes, a part-level object classification method based on the improved interpretation tree is presented. The part-level representation is implemented, which enables a more compact shape description of 3-D objects. The proposed classification method consists of two key processing stages： the improved constrained search on an interpretation tree and the following shape similarity measure computation. By the classification method, both whole match and partial match with shape similarity ranks are achieved; especially, focus match can be accomplished, where different key parts may be labeled and all the matched models containing corresponding key parts may be obtained. A series of experiments show the effectiveness of the presented 3-D object classification method.

Dynamic 3D shape reconstruction under complex reflection and transmission conditions using multi-scale parallel single-pixel imaging

Depth measurement and three-dimensional(3D)imaging under complex reflection and transmission conditions are challenging and even impossible for traditional structured light techniques,owing to the precondition of point-to-point triangulation.Despite recent progress in addressing this problem,there is still no efficient and general solution.Herein,a Fourier dual-slice projection with depth-constrained localization is presented to separate and utilize different illumination and reflection components efficiently,which can significantly decrease the number of projection patterns in each sequence from thousands to fifteen.Subsequently,multi-scale parallel single-pixel imaging(MS-PSI)is proposed based on the established and proven position-invariant theorem,which breaks the local regional assumption and enables dynamic 3D reconstruction.Our methodology successfully unveils unseen-before capabilities such as(1)accurate depth measurement under interreflection and subsurface scattering conditions,(2)dynamic measurement of the time-varying high-dynamic-range scene and through thin volumetric scattering media at a rate of 333 frames per second;(3)two-layer 3D imaging of the semitransparent surface and the object hidden behind it.The experimental results confirm that the proposed method paves the way for dynamic 3D reconstruction under complex optical field reflection and transmission conditions,benefiting imaging and sensing applications in advanced manufacturing,autonomous driving,and biomedical imaging.

Panicle-3D: A low-cost 3D-modeling method for rice panicles based on deep learning, shape from silhouette, and supervoxel clustering

Self-occlusions are common in rice canopy images and strongly influence the calculation accuracies of panicle traits. Such interference can be largely eliminated if panicles are phenotyped at the 3 D level.Research on 3 D panicle phenotyping has been limited. Given that existing 3 D modeling techniques do not focus on specified parts of a target object, an efficient method for panicle modeling of large numbers of rice plants is lacking. This paper presents an automatic and nondestructive method for 3 D panicle modeling. The proposed method integrates shoot rice reconstruction with shape from silhouette, 2 D panicle segmentation with a deep convolutional neural network, and 3 D panicle segmentation with ray tracing and supervoxel clustering. A multiview imaging system was built to acquire image sequences of rice canopies with an efficiency of approximately 4 min per rice plant. The execution time of panicle modeling per rice plant using 90 images was approximately 26 min. The outputs of the algorithm for a single rice plant are a shoot rice model, surface shoot rice model, panicle model, and surface panicle model, all represented by a list of spatial coordinates. The efficiency and performance were evaluated and compared with the classical structure-from-motion algorithm. The results demonstrated that the proposed method is well qualified to recover the 3 D shapes of rice panicles from multiview images and is readily adaptable to rice plants of diverse accessions and growth stages. The proposed algorithm is superior to the structure-from-motion method in terms of texture preservation and computational efficiency. The sample images and implementation of the algorithm are available online. This automatic, cost-efficient, and nondestructive method of 3 D panicle modeling may be applied to high-throughput 3 D phenotyping of large rice populations.

Real-Time Characterization of Crystal Shape and Size Distribution Based on Moving Window and 3D Imaging in a Stirred Tank

Crystal shape distribution, i.e. the multidimensional size distribution of crystals, is of great importance to their down-stream processing such as in filtration as well as to the end-use properties including the dissolution rate and bioavailability for crystalline pharmaceuticals. Engineering crystal shape and shape distribution requires knowledge about the growth behavior of different crystal facets under varied operational conditions e.g. supersaturations. Measurement of the facet growth rates and growth kinetics of static crystals in a crystallizer without stirring has been reported previously. Here attention is given to study on real-time characterization of the 3D facet growth behavior of crystals in a stirred tank where crystals are constantly moving and rotating. The measurement technique is stereo imaging and the crystal shape reconstruction is based on a stereo imaging camera model. By reference to a case study on potash alum crystallization, it is demonstrated that the crystal size and shape distributions (CSSD) of moving and rotating potash alum crystals in the solution can be reconstructed. The moving window approach was used to correlate 3D face growth kinetics with supersaturation (in the range 0.04 - 0.12) given by an ATR FTIR probe. It revealed that {100} is the fastest growing face, leading to a rapid reduction of its area, while the {111} face has the slowest growth rate, reflected in its area continuously getting larger.

Survey on depth and RGB image-based 3D hand shape and pose estimation

The field of vision-based human hand three-dimensional(3D)shape and pose estimation has attracted significant attention recently owing to its key role in various applications,such as natural human computer interactions.With the availability of large-scale annotated hand datasets and the rapid developments of deep neural networks(DNNs),numerous DNN-based data-driven methods have been proposed for accurate and rapid hand shape and pose estimation.Nonetheless,the existence of complicated hand articulation,depth and scale ambiguities,occlusions,and finger similarity remain challenging.In this study,we present a comprehensive survey of state-of-the-art 3D hand shape and pose estimation approaches using RGB-D cameras.Related RGB-D cameras,hand datasets,and a performance analysis are also discussed to provide a holistic view of recent achievements.We also discuss the research potential of this rapidly growing field.

基于Shape-from-Shading的月球表面三维形状恢复算法研究

提出了一种基于Shape-from-Shading的月球表面三维形状恢复算法。首先分析了在太阳光照射下月球表面成像模型,建立了使用Lommel-Seeliger反射模型描述的反射图方程。然后用有限差分近似微分运算,将反射图方程所示的一阶变系数线性偏微分方程进行离散化处理,得到关于表面高度函数的代数方程。进而采用超松弛迭代法进行求解,获得月球表面三维高度函数值。最后使用合成图像和实际月球图像进行三维形状恢复仿真实验。实验结果表明提出的算法可以有效地恢复月球表面三维形状。

3D Surface Reconstruction of Coarse Aggregate Particles from Occlusion-Free Multi-View Images

Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.

RM-CSTV:An effective high-resolution method of non-line-of-sight millimeter-wave radar 3-D imaging

Non-line-of-sight(NLOS)imaging is a novel radar sensing technology that enables the reconstruction of hidden targets.However,it may suffer from synthetic aperture length reduction caused by ambient occlusion.In this study,a complex total variation(CTV)regularization-based sparse reconstruction method for NLOS three-dimensional(3-D)imaging by millimeter-wave(mm W)radar,named RM-CSTV method,is proposed to improve imaging quality and speed.In this scheme,the NLOS imaging model is first introduced,and associated geometric constraints for NLOS objects are established.Second,an effective high-resolution NLOS imaging method based on the range migration(RM)kernel and complex sparse joint total variation constraint,dubbed as modified RM-CSTV,is proposed for 3-D high-resolution imaging with edge information.The experiments with multi-type NLOS targets show that the proposed RM-CSTV method can provide effective and high-resolution NLOS targets 3-D imaging.

A Scheme for Reconstructing Free-form Surface from Shading with Cellular Automata

The reconstruction of free-form surface is a fundamental problem in digital manufacture.This article presents a novel solution to reconstructing free-form surface from an intensity image under the Lambertian reflection model,that is a method called shape from shading (SFS).Our approach is based on the two-dimensional cellular automata (CA),and fully uses the local information of both image and the reconstructed surface.After several iterations,the free-form surface corresponding to the input image is obtained.The encouraging results on both synthetic and real-world images are provided in this paper,and the perfor- mance of our algorithm is analyzed on synthetic images using mean and standard deviation of depth (Z) errors.

PC-BASED SURFACE RECONSTRUCTION OF MEDICAL CT IMAGES

It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the visible surfaces are discussed. A polygon approximation methodthat forms polygon with the same number of segment points and a fast interpolation method forcross-sectional contours are presented at first. Then the voxel set of a human liver is reconstructed.And then the liver voxel set is displayed using depth and gradient shading methods. The softwareis written in C programming language at a microcomputer image processing system with a PC/ATcomputer as the host and a PC-VISION board as the image processing unit. The result of theprocessing is satisfying.

A new navigation approach of terrain contour matching based on 3-D terrain reconstruction from onboard image sequence

This article presents a passive navigation method of terrain contour matching by reconstructing the 3-D terrain from the image sequence(acquired by the onboard camera).To achieve automation and simultaneity of the image sequence processing for navigation,a correspondence registration method based on control points tracking is proposed which tracks the sparse control points through the whole image sequence and uses them as correspondence in the relation geometry solution.Besides,a key frame selection method based on the images overlapping ratio and intersecting angles is explored,thereafter the requirement for the camera system configuration is provided.The proposed method also includes an optimal local homography estimating algorithm according to the control points,which helps correctly predict points to be matched and their speed corresponding.Consequently,the real-time 3-D terrain of the trajectory thus reconstructed is matched with the referenced terrain map,and the result of which provides navigating information.The digital simulation experiment and the real image based experiment have verified the proposed method.