Drishti Paint 3.2:a new open-source tool for both 2D and 3D segmentation

X-ray computed tomography(CT)has been an important technology in paleontology for several decades.It helps researchers to acquire detailed anatomical structures of fossils non-destructively.Despite its widespread application,developing an efficient and user-friendly method for segmenting CT data continues to be a formidable challenge in the field.Most CT data segmentation software operates on 2D interfaces,which limits flexibility for real-time adjustments in 3D segmentation.Here,we introduce Curves Mode in Drishti Paint 3.2,an open-source tool for CT data segmentation.Drishti Paint 3.2 allows users to manually or semi-automatically segment the CT data in both 2D and 3D environments,providing a novel solution for revisualizing CT data in paleontological studies.

Dynamic Modelling of a Hybrid Variable Reluctance Machine Using the 3D Finite Element Method

This paper presents the work carried out to evaluate the dynamic performance of the Hybrid Variable Reluctance Motor (HVRM). The fourth-order Runge-Kutta integration algorithm was employed to solve the equations of the dynamic model, in conjunction with the three-dimensional finite element method. The 3D numerical data was calculated using Comsol Multiphysics, which accounts for the nonlinearity of the ferromagnetic material and the 3D nature of the HVRM. The outcomes of this study are precise and accurately predict the dynamic behaviour of the HVRM in terms of rotor position response, rotational speed and torque. The distinctive contribution of this work lies in the 3D numerical modelling of the HVRM and the subsequent evaluation and analysis of its dynamic operation. Analytical and numerical 2D studies are less resource-intensive and time-consuming, and are more straightforward and rapid to analyse and interpret. However, they are constrained in their capacity to examine spatial, volumetric interactions and intricate dynamics such as flux studies where three 3D effects cannot be disregarded, winding end effects and the configuration and positioning of the interposed permanent magnet.

3D Model Occlusion Culling Optimization Method Based on WebGPU Computing Pipeline

Nowadays,Web browsers have become an important carrier of 3D model visualization because of their convenience and portability.During the process of large-scale 3D model visualization based on Web scenes with the problems of slow rendering speed and low FPS(Frames Per Second),occlusion culling,as an important method for rendering optimization,can remove most of the occluded objects and improve rendering efficiency.The traditional occlusion culling algorithm(TOCA)is calculated by traversing all objects in the scene,which involves a large amount of repeated calculation and time consumption.To advance the rendering process and enhance rendering efficiency,this paper proposes an occlusion culling with three different optimization methods based on the WebGPU Computing Pipeline.Firstly,for the problem of large amounts of repeated calculation processes in TOCA,these units are moved from the CPU to the GPU for parallel computing,thereby accelerating the calculation of the Potential Visible Sets(PVS);Then,for the huge overhead of creating pipeline caused by too many 3D models in a certain scene,the Breaking Occlusion Culling Algorithm(BOCA)is introduced,which removes some nodes according to building a Hierarchical Bounding Volume(BVH)scene tree to reduce the overhead of creating pipelines;After that,the structure of the scene tree is transmitted to the GPU in the order of depth-first traversal and finally,the PVS is obtained by parallel computing.In the experiments,3D geological models with five different scales from 1:5,000 to 1:500,000 are used for testing.The results show that the proposed methods can reduce the time overhead of repeated calculation caused by the computing pipeline creation and scene tree recursive traversal in the occlusion culling algorithm effectively,with 97%rendering efficiency improvement compared with BOCA,thereby accelerating the rendering process on Web browsers.

Survey on computational 3D visual optical art design

Visual arts refer to art experienced primarily through vision.3D visual optical art is one of them.Artists use their rich imagination and experience to combine light and objects to give viewers an unforgettable visual experience.How-ever,the design process involves much trial and error;therefore,it is often very time-consuming.This has prompted many researchers to focus on proposing various algorithms to simplify the complicated design processes and help artists quickly realize the arts in their minds.To help computer graphics researchers interested in creating 3D visual optical art,we first classify and review relevant studies,then extract a general framework for solving 3D visual optical art design problems,and finally propose possible directions for future research.

3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images

Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.

Securing 3D Point and Mesh Fog Data Using Novel Chaotic Cat Map

With the rapid evolution of Internet technology,fog computing has taken a major role in managing large amounts of data.The major concerns in this domain are security and privacy.Therefore,attaining a reliable level of confidentiality in the fog computing environment is a pivotal task.Among different types of data stored in the fog,the 3D point and mesh fog data are increasingly popular in recent days,due to the growth of 3D modelling and 3D printing technologies.Hence,in this research,we propose a novel scheme for preserving the privacy of 3D point and mesh fog data.Chaotic Cat mapbased data encryption is a recently trending research area due to its unique properties like pseudo-randomness,deterministic nature,sensitivity to initial conditions,ergodicity,etc.To boost encryption efficiency significantly,in this work,we propose a novel Chaotic Cat map.The sequence generated by this map is used to transform the coordinates of the fog data.The improved range of the proposed map is depicted using bifurcation analysis.The quality of the proposed Chaotic Cat map is also analyzed using metrics like Lyapunov exponent and approximate entropy.We also demonstrate the performance of the proposed encryption framework using attacks like brute-force attack and statistical attack.The experimental results clearly depict that the proposed framework produces the best results compared to the previous works in the literature.

Use of high-resolution X-ray computed tomography and 3D image analysis to quantify mineral dissemination and pore space in oxide copper ore particles

Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle, a cylindrical copper oxide ore sample (I center dot 4.6 mm x 5.6 mm) was scanned using high-resolution X-ray computed tomography (HRXCT), a nondestructive imaging technology, at a spatial resolution of 4.85 mu m. Combined with three-dimensional (3D) image analysis techniques, the main mineral phases and pore space were segmented and the volume fraction of each phase was calculated. In addition, the mass fraction of each mineral phase was estimated and the result was validated with that obtained using traditional techniques. Furthermore, the pore phase features, including the pore size distribution, pore surface area, pore fractal dimension, pore centerline, and the pore connectivity, were investigated quantitatively. The pore space analysis results indicate that the pore size distribution closely fits a log-normal distribution and that the pore space morphology is complicated, with a large surface area and low connectivity. This study demonstrates that the combination of HRXCT and 3D image analysis is an effective tool for acquiring 3D mineralogical and pore structural data.

Numerical analysis of the failure process of soil-rock mixtures through computed tomography and PFC3D models

Soil-rock mixture （SRM） is a unique type of geomaterial characterized by a heterogeneous composition and a complicated structure. It is intractable for the continuum-based soil and rock mechanics theories to accurately characterize and predict the SRM＇s mechanical properties. This study reports a novel numerical method incorporating microfocus computed tomography and PFC3D codes to probe the deformation and failure processes of SRM. The three-dimensional （3D） PFC models that represent the SRM＇s complex structures were built. By simulating the entire failure process in PFC3D, the SRM＇s strength, elastic modulus and crack growth were obtained. The influence of rock ratios on the SRM＇s strength, deformation and failure processes, as well as its internal mesoscale mechanism, were analyzed. By comparing simulation results with experimental data, it was verified that the 3D PFC models were in good agreement with SRM＇s real structure and the SRM＇s compression process, deformation and failure patterns; its intrinsic mesomechanism can be effectively analyzed based on such 3D PFC models.

Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network

Appearance-based dynamic Hand Gesture Recognition(HGR)remains a prominent area of research in Human-Computer Interaction(HCI).Numerous environmental and computational constraints limit its real-time deployment.In addition,the performance of a model decreases as the subject’s distance from the camera increases.This study proposes a 3D separable Convolutional Neural Network(CNN),considering the model’s computa-tional complexity and recognition accuracy.The 20BN-Jester dataset was used to train the model for six gesture classes.After achieving the best offline recognition accuracy of 94.39%,the model was deployed in real-time while considering the subject’s attention,the instant of performing a gesture,and the subject’s distance from the camera.Despite being discussed in numerous research articles,the distance factor remains unresolved in real-time deployment,which leads to degraded recognition results.In the proposed approach,the distance calculation substantially improves the classification performance by reducing the impact of the subject’s distance from the camera.Additionally,the capability of feature extraction,degree of relevance,and statistical significance of the proposed model against other state-of-the-art models were validated using t-distributed Stochastic Neighbor Embedding(t-SNE),Mathew’s Correlation Coefficient(MCC),and the McNemar test,respectively.We observed that the proposed model exhibits state-of-the-art outcomes and a comparatively high significance level.

Quantification of 3D macropore networks in forest soils in Touzhai valley(Yunnan,China)using X-ray computed tomography and image analysis

The three dimensional （3D） geometry of soil macropores largely controls preferential flow, which is a significant infiltrating mechanism for rainfall in forest soils and affects slope stability. However, detailed studies on the 3D geometry of macropore networks in forest soils are rare. The intense rainfall-triggered potentially unstable slopes were threatening the villages at the downstream of Touzhai valley （Yunnan, China）. We visualized and quantified the 3D macropore networks in undisturbed soil columns （Histosols） taken from a forest hillslope in Touzhai valley, and compared them with those in agricultural soils （corn and soybean in USA; barley, fodder beet and red fescue in Denmark） and grassland soils in USA. We took two large undisturbed soil columns （250 mm^25o mmxsoo mm）, and scanned the soil columns at in-situ soil water content conditions using X-ray computed tomography at a voxel resolution of 0.945 × 0.945 × 1.500o mm^3. After reconstruction and visualization, we quantified the characteristics of macropore networks. In the studied forest soils, the main types of maeropores were root channels, inter-aggregate voids, maeropores without knowing origin, root-soil interfaee and stone-soil interface. While maeropore networks tend to be more eomplex, larger, deeper and longer. The forest soils have high maeroporosity, total maeropore wall area density, node density, and large maeropore volume, hydraulie radius, mean maeropore length, angle, and low tortuosity. The findings suggest that maeropore networks in the forest soils have high inter- connectivity, vertical continuity, linearity and less vertically oriented.

Quasi-3D Numerical Simulation of Tidal Hydrodynamic Field

Based on the 2D horizontal plane numerical model, a quasi-3D numerical model is established for coastal regions of shallow water. The characteristics of this model are that the velocity profiles;can be obtained at the same time when the equations of the value of difference between the horizontal current velocity and its depth-averaged velocity in the vertical direction are solved and the results obtained are consistent with the results of the 2D, model. The circulating flow in the rectangular area induced by wind is simulated and applied to the tidal flow field of the radial sandbanks in the South Yellow Sea. The computational results from this quasi-3D model are in good agreement with analytical results and observed data. The solution of the finite difference equations has been found to be stable, and the model is simple, effective and practical.

Polarization sensitive photodetector based on quasi-1D ZrSe_(3)

The in-plane anisotropy of transition metal trichalcogenides(MX_(3))has a significant impact on the molding of materi-als and MX_(3) is a perfect choice for polarized photodetectors.In this study,the crystal structure,optical and optoelectronic aniso-tropy of one kind of quasi-one-dimensional(1D)semiconductors,ZrSe_(3),are systematically investigated through experiments and theoretical studies.The ZrSe_(3)-based photodetector shows impressive wide spectral response from ultraviolet(UV)to near in-frared(NIR)and exhibits great optoelectrical properties with photoresponsivity of 11.9 mA·W^(-1) and detectivity of~106 at 532 nm.Moreover,the dichroic ratio of ZrSe_(3)-based polarized photodetector is around 1.1 at 808 nm.This study suggests that ZrSe_(3) has potential in optoelectronic applications and polarization detectors.

Femoroacetabular impingement with chronic acetabular rim fracture- 3D computed tomography, 3D magnetic resonance imaging and arthroscopic correlation

Femoroacetabular impingement is uncommonly associated with a large rim fragment of bone along the superolateral acetabulum. We report an unusual case of femoroacetabular impingement(FAI) with chronic acetabular rim fracture. Radiographic, 3D computed tomography, 3D magnetic resonance imaging and arthroscopy correlation is presented with discussion of relative advantages and disadvantages of various modalities in the context of FAI.

X-ray Computed Tomography Characterization of 3D Tufted Twill Textile Composite for Aerostructures

Damage assessments in three dimensional (3D) textile composites subjected to mechanical loading can be performed by non-destructive and destructive techniques.This paper applies the two techniques to investigate the fracture behavior of 3D tufted textile composites.X-ray computed tomography as a non-destructive evaluation method is appropriate to detect damage locations and identify their progression in 3D textile composites.Destructive methods such as sectioning toward observing damage provide valuable information about damage patterns.The results of this research could be utilized to evaluate the initial cause of rupture in 3D tufted composites used in aerospace structures and analyze fracture modes and damage progression.

A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.

3D Reconstruction with Spiral Computed Tomography in Choroidal Osteoma

Choroidal osteoma (CO) is a rare, ossifying benign tumor originated in the choroid that typically occurs in otherwise healthy young women (1,2). It is characterized by a yellowish, well demarcated lesion in the juxtapapillary or macular area. The diagnosis is clinical and can be confirmed with the use of fluorescein or indocyanine angiography, optical coherence tomography, computed tomography or magnetic resonance imaging. Choroidal neovascularization or subretinal fluid, the main causes for vision loss, can be treated with laser therapy, photodynamic therapy or intravitreal antivascular endothelial growth factor therapy. We present a case of choroidal osteoma, showing the role of the high resolution 3D spiral computed tomography.

Phase II Clinical Study of Three-Dimensional Printed Coplanar Template Combined with CT-Guided Percutaneous Core Needle Biopsy of Pulmonary Nodules in Elderly Patients

Background: As the population age structure gradually ages, more and more elderly people were found to have pulmonary nodules during physical examinations. Most elderly people had underlying diseases such as heart, lung, brain and blood vessels and cannot tolerate surgery. Computed tomography (CT)-guided percutaneous core needle biopsy (CNB) was the first choice for pathological diagnosis and subsequent targeted drugs, immune drugs or ablation treatment. CT-guided percutaneous CNB requires clinicians with rich CNB experience to ensure high CNB accuracy, but it was easy to cause complications such as pneumothorax and hemorrhage. Three-dimensional (3D) printing coplanar template (PCT) combined with CT-guided percutaneous pulmonary CNB biopsy has been used in clinical practice, but there was no prospective, randomized controlled study. Methods: Elderly patients with lung nodules admitted to the Department of Oncology of our hospital from January 2019 to January 2023 were selected. A total of 225 elderly patients were screened, and 30 patients were included after screening. They were randomly divided into experimental group (Group A: 30 cases) and control group (Group B: 30 cases). Group A was given 3D-PCT combined with CT-guided percutaneous pulmonary CNB biopsy, Group B underwent CT-guided percutaneous pulmonary CNB. The primary outcome measure of this study was the accuracy of diagnostic CNB, and the secondary outcome measures were CNB time, number of CNB needles, number of pathological tissues and complications. Results: The diagnostic accuracy of group A and group B was 96.67% and 76.67%, respectively (P = 0.026). There were statistical differences between group A and group B in average CNB time (P = 0.001), number of CNB (1 vs more than 1, P = 0.029), and pathological tissue obtained by CNB (3 vs 1, P = 0.040). There was no statistical difference in the incidence of pneumothorax and hemorrhage between the two groups (P > 0.05). Conclusions: 3D-PCT combined with CT-guided percutaneous CNB can improve the puncture accuracy of elderly patients, shorten the puncture time, reduce the number of punctures, and increase the amount of puncture pathological tissue, without increasing pneumothorax and hemorrhage complications. We look forward to verifying this in a phase III randomized controlled clinical study. .

RANGE ACQUISITION IN BINOCULAR 3-D COMPUTER VISION USING EDGE-BASED HIERARCHICAL MATCHING

This paper deals with a binocular 3-D computer vision system based on the hierarchicalmatching of edge features, Frei and Chen operator is used to extract the edge. The averagegradients of an image obtained by two isotropic operators are non-equal quantized andthresholded in an angle, Edge features are extracted after passing a preemphasis transferfunction which can equalize, the noise affection. Binary edge images are decomposed into apyramid structure which is stored and searched using llliffe’s location method. Corre-sponding points are used to determine the range data using triangulation based on an improvedTrivedi’s formula. In calibration the authors set the optical axes of the two cameras parallelto simplify the calculation, A 3 rd order Householder transform is used to solve the compati-ble coupled equations.

DESIGN AND IMPLEMENTATION OF A 3-DIMENSIONAL COMPUTER AIDED GARMENT DESIGN SYSTEM

A 3-Dimensional computer aided garment design (CAGD) system has been developed andimplemented on a high-performance workstation. We studied various approaches to the func-tional modelling of garment designs for the system. According to the characteristic data of a hu-man body, the models of human body and the garment are displayed on the screen, then we canmodify the garment with various styles and different sizes. The system can transform the 3-Dgarment to the 2-D pieces. The system has improved design efficiency. Various potential alterna-tives and improvement of the system have also been studied and explored.

3-D MODELLING OF COMPUTER AIDED GARMENT DESIGN

This paper describes a method of the computer aided garment design,and discusses 3-D humanbody,wire frame modelling,approaches of expressing and a shading model of the 3-D garment.