3D view序列联合压缩感知技术精准诊断踝周韧带损伤

目的应用3 Dview序列联合压缩感知(Compressed Sensing,CS)技术观察踝关节扭伤患者韧带损伤情况,探讨3D view序列与常规2D序列相比能否提高诊断效能。方法前瞻性分析2021年2月至2021年11月来我院急诊就诊的踝关节急性扭伤患者共26例(26个踝关节)。上述受试均行MRI检查,扫描序列包括常规2D及3D view T2联合压缩感知序列。应用Mann-Whitney U检验评价常规序列及3D view序列的扫描时间、跟腱的信噪比及对比噪声比及评估患者在两序列下腓距前韧带、腓跟韧带、三角韧带、分歧韧带的损伤程度比较有无区别。应用Fisher确切概率法比较两序列对腓距前韧带、腓跟韧带、三角韧带、分歧韧带损伤的检出率有无差别。结果共纳入踝关节扭伤患者26例,3D view+CS序列的扫描时间为376.2±0s,略短于常规序列(381.479±7.3s),两者无明显差别(Z=-1.396,P=0.163)。3D view序列跟腱信噪比明显高于2D常规序列(Z=-3.441,P=0.001);对比噪声比明显高于2D常规序列(Z=-6.094,P<0.01);跟腓韧带和分歧韧带的损伤程度明显高于2D常规序列(Z=-2.67,P=0.008;Z=-2.67,P<0.001)。两序列对于距腓前韧带和内侧三角韧带的损伤程度差异无统计学差别(P<0.05)。3D View+CS序列对分歧韧带损伤的检出率明显高于2D常规序列(P<0.001)。3D View+CS序列较2D常规序列对距腓前韧带、跟腓韧带、内侧三角韧带损伤的检出率无明显差别(P>0.05)。结论在3D View+CS序列与常规2D序列扫描时间相当的情况下,3D View+CS序列图像质量较常规2D序列更高,踝周韧带的检出率更高,并更准确地评估韧带损伤程度。

Integral imaging-based tabletop light field 3D display with large viewing angle

Light field 3D display technology is considered a revolutionary technology to address the critical visual fatigue issues in the existing 3D displays.Tabletop light field 3D display provides a brand-new display form that satisfies multi-user shared viewing and collaborative works,and it is poised to become a potential alternative to the traditional wall and portable display forms.However,a large radial viewing angle and correct radial perspective and parallax are still out of reach for most current tabletop light field 3D displays due to the limited amount of spatial information.To address the viewing angle and perspective issues,a novel integral imaging-based tabletop light field 3D display with a simple flat-panel structure is proposed and developed by applying a compound lens array,two spliced 8K liquid crystal display panels,and a light shaping diffuser screen.The compound lens array is designed to be composed of multiple three-piece compound lens units by employing a reverse design scheme,which greatly extends the radial viewing angle in the case of a limited amount of spatial information and balances other important 3D display parameters.The proposed display has a radial viewing angle of 68.7°in a large display size of 43.5 inches,which is larger than the conventional tabletop light field 3D displays.The radial perspective and parallax are correct,and high-resolution 3D images can be reproduced in large radial viewing positions.We envision that this proposed display opens up possibility for redefining the display forms of consumer electronics.

Point Cloud Processing Methods for 3D Point Cloud Detection Tasks

Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.

3DV quality model based depth maps for view synthesis in FTV system

Depth maps are used for synthesis virtual view in free-viewpoint television （FTV） systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts in the synthesized views. To solve this problem, a 3D video quality model base depth maps （D-3DV） for virtual view synthesis and depth map coding in the FTV applications is proposed. First, the relationships between distortions in coded depth map and rendered view are derived. Then, a precisely 3DV quality model based depth characteristics is develop for the synthesized virtual views. Finally, based on D-3DV model, a multilateral filtering is applied as a pre-processed filter to reduce rendering artifacts. The experimental results evaluated by objective and subjective methods indicate that the proposed D-3DV model can reduce bit-rate of depth coding and achieve better rendering quality.

Application of Digital Technology in Road and Bridge Design

With the development and progress of science and technology,road and bridge design has experienced rapid development,from the initial manual drawing design to the popularity of Computer-Aided Design(CAD),and then to today’s digital software design era.Early designers relied on hand-drawn paper design forms which was time-consuming and error-prone.Digital support for road and bridge design not only saves the design time but the design quality has also achieved a qualitative leap.This paper engages in the application of digital technology in road and bridge design,to provide technical reference for China’s road and bridge engineering design units,to promote the popularity of Civil3D and other advanced design software in the field of engineering design and development,ultimately contributing to the sustainable development of China’s road and bridge engineering.

裸眼3DLED显示的全息透镜板在线拼接的检测方法

全息透镜板的高精度拼接与装配是基于全息透镜技术的大屏幕LED裸眼3D显示系统搭建巾的关键问题;理论计算与实验结果表明,全息透镜板与LED显示模组横向相对位置误差小于1.332 mm时,可以满足显示的要求;基于裸眼3D显示系统的投射条纹,提出了基于投射条纹的全息透镜板位置实时调整方法;依据此方法提出了基于极大值测量条纹中心间距的图像处理算法,并结合Lab—View编写了图像处理程序;实验结果表明,使用该方法测得的亮暗条纹间距的测量精度为0.1 mm,反算出全息透镜板与LED屏之间的位置误差小于0.03 mm,满足实时调整全息透镜板位置的要求,可以作为全息透镜板在线拼接的检测方法。

基于3DGMM的多视点视频直方图颜色校正

多视点视频在采集过程中,由于受到摄像机所处位置以及摄像机自身的参数设置等因素的影响,会造成视点间颜色的不一致,针对这一情况,提出基于三维高斯混合模型的多视点视频直方图颜色校正算法。算法首先获取源图像以及目标图像的直方图并检测直方图的峰值个数,然后结合三维高斯混合模型对源图像以及目标图像进行聚类分析,获取中心矢量,最后计算两图像中像素点距离中心矢量的最小欧几里得距离并分割图像,对源图像和目标图像的匹配区域进行直方图匹配校正。实验结果表明,该算法与传统直方图匹配算法相比,避免了校正过度的影响,校正效果较好。

Design of three-dimensional imaging lidar optical system for large field of view scanning

Three-dimensional(3D)lidar has been widely used in various fields.The MEMS scanning system is one of its most important components,while the limitation of scanning angle is the main obstacle to improve the demerit for its application in various fields.In this paper,a folded large field of view scanning optical system is proposed.The structure and parameters of the system are determined by theoretical derivation of ray tracing.The optical design software Zemax is used to design the system.After optimization,the final structure performs well in collimation and beam expansion.The results show that the scan angle can be expanded from±5°to±26.5°,and finally the parallel light scanning is realized.The spot diagram at a distance of 100 mm from the exit surface shows that the maximum radius of the spot is 0.506 mm with a uniformly distributed spot.The maximum radius of the spot at 100 m is 19 cm,and the diffusion angle is less than 2 mrad.The energy concentration in the spot range is greater than 90%with a high system energy concentration,and the parallelism is good.This design overcomes the shortcoming of the small mechanical scanning angle of the MEMS lidar,and has good performance in collimation and beam expansion.It provides a design method for large-scale application of MEMS lidar.

Adaptive luminance adjustment and neighborhood spreading strength information based view synthesis

View synthesis is an important building block in three dimension（3D） video processing and communications.Based on one or several views,view synthesis creates other views for the purpose of view prediction（for compression） or view rendering（for multiview-display）.The quality of view synthesis depends on how one fills the occlusion area as well as how the pixels are created.Consequently,luminance adjustment and hole filling are two key issues in view synthesis.In this paper,two views are used to produce an arbitrary virtual synthesized view.One view is merged into another view using a local luminance adjustment method,based on local neighborhood region for the calculation of adjustment coefficient.Moreover,a maximum neighborhood spreading strength hole filling method is presented to deal with the micro texture structure when the hole is being filled.For each pixel at the hole boundary,its neighborhood pixels with the maximum spreading strength direction are selected as candidates;and among them,the pixel with the maximum spreading strength is used to fill the hole from boundary to center.If there still exist disocclusion pixels after once scan,the filling process is repeated until all hole pixels are filled.Simulation results show that the proposed method is efficient,robust and achieves high performance in subjection and objection.

汽车360°环视系统发展研究

针对用于辅助驾驶的汽车360°环视系统业界普遍存在的重影错位、远端模糊、拼接缝模糊以及一些角度视野失真的问题,提出这些问题将随着未来算力的性价比提升和人工智能的发展,将可以被最终优化或解决。首先概述系统的工作原理和基本功能,然后解析系统的软硬件结构和每个功能模块的作用,同时描述过程的一些算法模型。最后指出系统的物理局限性:前后左右摄像头的安装位置和角度不可能是在同一高度,模型投影后存在差异,鱼眼摄像头原理光轴中心的像素较少。最后从问题机理上分析,高分辨率图像重建或更高像素的摄像头可以解决远端模糊问题,重影错位问题可以通过结构光相机或者3D重建算法获取深度信息进行解决。

自动3维重构中确定下一最优视点的方法研究

提出了基于牛顿万有引力定律矢量场的当前视点下曲面积分最大化的方法,以确定下一最优视点的3维空间位置.在该方法中采用斯托克斯公式计算边界曲线积分的途径间接获得曲面积分,从而方便地确定了视点的位置数据.实验结果表明:该文提出的下一最优视点的确定方法可使机器人自动实现多视点规划,同时解决了单视点规划下存在采集盲区的问题.

一种新的大场景3维重建算法

大场景图像集具有规模巨大、尺度多变、结构不整等特点。针对此类图像集,提出一种新的鲁棒稠密3维重建方法。该方法在选取图像的邻居图集时考虑了尺度鲁棒性,随后基于DAISY特征匹配和Patch Match信息传播计算深度图,然后利用深度一致性优化、融合深度图,最后利用重建3维点精度去除冗余点。深度图计算时相互独立,故提出的方法易在图像级并行,适合大场景3维重建。实验结果表明,该方法重建结果具有较高的精度和完整性。

Recent advances in 3D Gaussian splatting

The emergence of 3D Gaussian splatting(3DGS)has greatly accelerated rendering in novel view synthesis.Unlike neural implicit representations like neural radiance fields(NeRFs)that represent a 3D scene with position and viewpoint-conditioned neural networks,3D Gaussian splatting utilizes a set of Gaussian ellipsoids to model the scene so that efficient rendering can be accomplished by rasterizing Gaussian ellipsoids into images.Apart from fast rendering,the explicit representation of 3D Gaussian splatting also facilitates downstream tasks like dynamic reconstruction,geometry editing,and physical simulation.Considering the rapid changes and growing number of works in this field,we present a literature review of recent 3D Gaussian splatting methods,which can be roughly classified by functionality into 3D reconstruction,3D editing,and other downstream applications.Traditional point-based rendering methods and the rendering formulation of 3D Gaussian splatting are also covered to aid understanding of this technique.This survey aims to help beginners to quickly get started in this field and to provide experienced researchers with a comprehensive overview,aiming to stimulate future development of the 3D Gaussian splatting representation.

Neural 3D reconstruction from sparse views using geometric priors

Sparse view 3D reconstruction has attracted increasing attention with the development of neural implicit 3D representation.Existing methods usually only make use of 2D views,requiring a dense set of input views for accurate 3D reconstruction.In this paper,we show that accurate 3D reconstruction can be achieved by incorporating geometric priors into neural implicit 3D reconstruction.Our method adopts the signed distance function as the 3D representation,and learns a generalizable 3D surface reconstruction model from sparse views.Specifically,we build a more effective and sparse feature volume from the input views by using corresponding depth maps,which can be provided by depth sensors or directly predicted from the input views.We recover better geometric details by imposing both depth and surface normal constraints in addition to the color loss when training the neural implicit 3D representation.Experiments demonstrate that our method both outperforms state-of-the-art approaches,and achieves good generalizability.

MVContrast:Unsupervised Pretraining for Multi-view 3D Object Recognition

3D shape recognition has drawn much attention in recent years.The view-based approach performs best of all.However,the current multi-view methods are almost all fully supervised,and the pretraining models are almost all based on ImageNet.Although the pretraining results of ImageNet are quite impressive,there is still a significant discrepancy between multi-view datasets and ImageNet.Multi-view datasets naturally retain rich 3D information.In addition,large-scale datasets such as ImageNet require considerable cleaning and annotation work,so it is difficult to regenerate a second dataset.In contrast,unsupervised learning methods can learn general feature representations without any extra annotation.To this end,we propose a three-stage unsupervised joint pretraining model.Specifically,we decouple the final representations into three fine-grained representations.Data augmentation is utilized to obtain pixel-level representations within each view.And we boost the spatial invariant features from the view level.Finally,we exploit global information at the shape level through a novel extract-and-swap module.Experimental results demonstrate that the proposed method gains significantly in 3D object classification and retrieval tasks,and shows generalization to cross-dataset tasks.

Auto CAD三维实体建模的方法研究

针对Auto CAD不能由三维实体模型直接生成二维工程图的不足,为了提高绘图的效率和质量,文中提出了一种利用Auto CAD平面视口命令将三维实体模型转换为二维视图的方法,并对实际操作中容易出现的问题给予解决的建议,具有一定的工程应用价值。

Structural Interpretation and Petrophysical Analysis for Reservoir Sand of Lower Goru, Miano Area, Central Indus Basin, Pakistan

The main purpose of this research is to estimate the structural analysis and hydrocarbon potential of Miano Block by using seismic and well log techniques. Miano area hosts a number of gas fields with structural and stratigraphic traps. The area is located in Central Indus Basin which is a part of an extensional regime exhibiting normal faulting due to the split of the Indian Plate firstly from Africa and then from Madagascar and Seychelles. Miano area recognized as a proven petroleum province which has complex tectonic history of Cretaceous extensional and overprints of Tertiary strike-slip tectonics. The area has prospect with accumulation of hydrocarbons in structural and stratigraphic traps including pinchouts. NW-SE oriented Khairpur and Mari Highs are main structural features with impact on the fault system. The sands of Lower Goru of Lower Cretaceous age are acting as a reservoir in the area. The area has great potential of hydrocarbons for which more exploratory wells are required to be drilled with better insight of structural and stratigraphic traps.

Space-Temporal Variation in Underground Water Some Quality Parameters in Klodzko Water Intake Area Using Statistical and Geostatistical Methods （SW Part of Poland）

This paper presents selected results of research connected with the development of a （3D） geostatistical hydrogeochemical model of the Klodzko Drainage Basin, dedicated to the spatial and time variation in the selected quality parameters of underground water in the Klodzko water intake area （SW part of Poland） [1-6]. The research covers the period 1977-2012. Spatial analyses of the variation in different quality parameters, between others, Fe [gFe/m3], Mn [gMn/m3], ammonium ion [gNH4＋/m3] contents and oxidation capacity [gO2/m3], were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area [2-4]. Spatial and time variation in the parameters was analyzed on the basis of archival data （period 1977-1999） for 22 （pump and siphon） wells, later data obtained （November 2011） from tests of water taken from 14 existing wells and the latest data （January 2012） acquired from 3 new piezometers, which were made in other locations in the relevant area. Thematic databases, containing original data on coordinates X, Y （latitude, longitude） and Z （terrain elevation and time-years） and on regionalized variables, i.e. the underground water quality parameters in the Klodzko water intake area determined for different analytical configurations （22 wells, 14 wells, 14 wells ＋ 3 piezometers）, were created [2]. Both archival data （acquired in the years 1977-1999） and the latest data （collected in 2011-2012） were analyzed. These data were subjected to spatial analyses [2-6] using statistical and geostatistical methods [7-12]. The evaluation of basic statistics of the investigated quality parameters, including their histograms of distributions, scatter diagrams between these parameters and also correlation coefficients r, were presented in this article. The directional semivariogram function and the ordinary （block） kriging procedure were used to build the 3D geostatistical model. The geostatistical parameters of the theoretical models of directional semivariograms of the studied water quality parameters, calculated along the time interval and the well depth （taking into account the terrain elevation）, were used in the ordinary （block） kriging estimation. The obtained results of estimation, allowed to determine the levels of increased values Z＊ of studied underground water quality parameters [2, 4-6]. Generally, the behaviour of the underground water quality parameters has been found to vary in space and time. Thanks to the spatial analyses of the variation in the quality parameters in the Klodzko underground water intake area some regularities （trends） in the variation in water quality have been identified.

基于压缩感知技术的3D VIEW PD序列对膝关节成像的影响

目的探究压缩感知(CS)技术不同加速因子(AF)对膝关节3D VIEW PD的影响。方法使用3.0 T MR对23名健康志愿者(男10例,女13例)分别采用AF为0、4、6、8、10和12的3D VIEW PD序列进行膝关节MRI扫描,按照上述AF分为A、B、C、D、E、F组。由两名观测者分别对膝关节图像质量进行5分制主观评分,并在股骨远端、腓肠肌、半月板(外侧半月板前角和外侧半月板后角)和韧带(前交叉韧带和后交叉韧带)上绘制感兴趣区(ROI)。测量六组图像膝关节、骨及肌肉的信号值(SI)、噪声(SD)值,分别计算图像信噪比(SNR)、对比噪声比(CNR)。分别使用独立样本Kruskal-Wallis检验以及卡方检验对六组半月板前侧、半月板后侧、前交叉韧带、后交叉韧带、股骨远端SNR、CNR及三组图像质量评分结果进行组间统计学分析。结果两名观测者对六组图像的客观测量数据与图像主观评分的一致性良好(Kappa和ICC值均>0.75)。六组主观评分分别为4.96±0.21、4.87±0.34、4.83±0.39、4.61±0.50、3.83±0.58、3.61±0.58。E、F组与A组相比有显著差异。半月板前侧SNR在E组和F组与A组有显著性差异,CNR在D、E和F组有显著差异;半月板后侧SNR在F组与A组有显著性差异,CNR在D、E和F组有显著差异;股骨SNR在D、E和F组有显著差异,CNR在D、E组和F组有显著差异;前交叉韧带SNR无差异,CNR在D、E和F组有显著差异;后交叉韧带SNR在E组和F组时有差异,CNR在E组和F组有差异(P均<0.05)。传统3D VIEW PD的扫描时间为320 s,结合CS的AF=6的3D VIEW PD序列扫描时间缩短约28.8%(320 s vs.230 s)。结论选出最优AF=6,相较于传统3D VIEW PD序列,基于CS的3D VIEW PD序列能保证图像质量,并且显著缩短扫描时间(减少约28.8%),对于外伤难以耐受的患者的膝关节扫描时有较好的临床应用前景。

Propagation-based incremental triangulation for multiple views 3D reconstruction

To balance the accuracy and efficiency in multiple-view triangulation with sequential images, a high-efficiency propagationbased incremental triangulation(INT) method, carving three-dimensional(3 D) scene points by updating the incoming feature track one by one without iterations, is proposed. Based on the INT method, a more accurate iteration-limited INT method is also established with few iterations to bound the propagated errors, ensuring the accuracy of subsequent3 D reconstruction. Finally, experimental results demonstrate that the proposed methods can balance the efficiency and accuracy in different multiple-view INT situations.