3D Algorithm Research Articles

Application of optical scanning systems and 3D modeling algorithms as a method to control the depth of teeth preparation for fixed orthopedic structures

Background. In orthopedic dentistry at the present stage of its development, a chemical technique for preparing teeth for fixed structures of dentures has been developed; however, the state of the pulp in response to preparation is not taken into account. As a result, medical tactics for preserving or extirpating the pulp of abutment teeth, depending on the clinical case, are unreasonable. Given the generally accepted rules for preparing teeth for fixed orthopedic structures, there is a significant percentage of complications. Controlling the depth of tooth preparation makes it possible to carry out this manipulation as rationally as possible, and as a result to ensure the effectiveness of procedure, based on the state of vitality of the prepared teeth. The aim of the study is to determine and control the depth of the studied teeth preparation using digital volumetric scanning technology and algorithms of a digital graphic 3D editor in the CAD/CAM system. Materials and methods. The article presents the results of using digital volumetric scanning of the CAD/CAM system and an integrated algorithm for digital 3D modeling to determine and control the depth of teeth preparation for fixed orthopedic structures. Results. Based on the results of digital volumetric scanning, the working thickness of the tooth preparation in the area of the tooth neck was determined with the formation of various types of chamfer in different study groups. In order to determine the depth of the preparation of hard dental tissues, an artificial crown was modeled in the CAD system — digital volumetric scanner NeWay (Open Technologies) and data on its thickness in the area of the ledge were obtained. Conclusions. Method of digital volumetric scanning to determine and control the depth of preparation of hard dental tissues makes it possible to prevent the development of irreversible morpho-functional changes in the tissues of teeth caused by odontoreparation.

A CT based 3D Algorithm for Diagnosis of DDH and Quantification of Surgical Correction

A CT based 3D Algorithm for Diagnosis of DDH and Quantification of Surgical Correction

Research on Active Disturbance Rejection Algorithm for Loading Control of 3-DOF Parallel Robot

A three-dimensional (3D) loading device based on a pneumatic 3-universal-prismatic-universal (UPU) parallel manipulator (three chains with UPU joint each) is designed to apply time-varying multi-dimensional loads to a target. First, according to the principle of vector superposition and Newton–Raphson method, the inverse and forward kinematics of the loading device are analyzed. Second, based on the screw theory, the static mapping between the dynamic platform and actuations is derived. Third, a second-order mathematical model is established for pneumatic 3-UPU parallel mechanism based on proportional flow valve and a metal seal pneumatic cylinder. A referential inaccurate model is provided for the control algorithm during modeling. Fourth, based on active disturbance rejection control (ADRC) technique, a 3D loading control algorithm is proposed and dynamic loading control is realized. Experimental results show that the ADRC algorithm has good robustness against disturbances, the steady-state control accuracy is less than 2 N, and the mean square error in dynamic tracking (sinusoidal tracking at 0.2 Hz) is less than 10.5 N.

Feature information extraction method for narrow gap U-type groove based on laser vision

The precise measurement of weld groove position and geometric dimensions serves as the foundation for predicting and planning welding strategies and process parameters. The steep sidewalls of narrow gap U-type grooves pose challenges for sensing and detection during the welding process. This paper presents a feature information extraction method for narrow gap U-type grooves based on laser vision technology. Firstly, the image acquisition system is calibrated using the incident plane of the laser beam. Subsequently, a digital image processing technique is employed to enhance the collected images, combining a 3D spatial domain enhancement algorithm with a laser stripe image refinement method based on Euclidean distance transformation. Finally, the transverse and vertical positions of the groove, as well as its geometric features such as width, depth, assembly gap, and misalignment, are computed and measured using feature point positioning. The proposed algorithm is experimentally verified for its accuracy, robustness, and real-time performance. The results indicate that the method effectively suppresses unevenness in laser stripe brightness and mitigates random noise in the captured images. The average measurement errors for transverse position, vertical position, width, depth, assembly gap, and misalignment of the groove are 0.0857 mm, 0.0987 mm, 0.1664 mm, 0.2216 mm, 0.0935 mm, and 0.0997 mm, respectively. Furthermore, the average image processing time per frame is 58 ms, meeting the requirements of pre-weld detection in arc welding.

Validation of HiG-Flow Software for Simulating Two-Phase Flows with a 3D Geometric Volume of Fluid Algorithm

This study reports the development of a numerical method to simulate two-phase flows of Newtonian fluids that are incompressible, immiscible, and isothermal. The interface in the simulation is located and reconstructed using the geometric volume of fluid (VOF) method. The implementation of the piecewise-linear interface calculation (PLIC) scheme of the VOF method is performed to solve the three-dimensional (3D) interface transport during the dynamics of two-phase flows. In this method, the interface is approximated by a line segment in each interfacial cell. The balance of forces at the interface is accounted for using the continuum interfacial force (CSF) model. To solve the Navier–Stokes equations, meshless finite difference schemes from the HiG-Flow computational fluid dynamics software are employed. The 3D PLIC-VOF HiG-Flow algorithm is used to simulate several benchmark two-phase flows for the purpose of validating the numerical implementation. First, the performance of the PLIC implementation is evaluated by conducting two standard advection numerical tests: the 3D shearing flow test and the 3D deforming field test. Good agreement is obtained for the 3D interface shape using both the 3D PLIC-VOF HiG-Flow algorithm and those found in the scientific literature, specifically, the piecewise-constant flux surface calculation, the volume of fluid method implemented in OpenFOAM, and the high-order finite-element software FEEL. In addition, the absolute error of the volume tracking advection calculation obtained by our 3D PLIC-VOF HiG-Flow algorithm is found to be smaller than the one found in the scientific literature for both the 3D shearing and 3D deforming flow tests. The volume fraction conservation absolute errors obtained using our algorithm are 4.48×10−5 and 9.41×10−6 for both shearing and deforming flow tests, respectively, being two orders lower than the results presented in the scientific literature at the same level of mesh refinement. Lastly, the 3D bubble rising problem is simulated for different fluid densities (ρ1/ρ2=10 and ρ1/ρ2=1000) and viscosity ratios (μ1/μ2=10 and μ1/μ2=100). Again, good agreement is obtained for the 3D interface shape using both the newly implemented algorithm and OpenFOAM, DROPS, and NaSt3D software. The 3D PLIC-VOF HiG-Flow algorithm predicted a stable ellipsoidal droplet shape for ρ1/ρ2=10 and μ1/μ2=10, and a stable cap shape for ρ1/ρ2=1000 and μ1/μ2=100. The bubble’s rise velocity and evolution of the bubble’s center of mass are also computed with the 3D PLIC-VOF HiG-Flow algorithm and found to be in agreement with those software. The rise velocity of the droplet for both the ellipsoidal and cap flow regime’s is found, in the initial stages of the simulation, to gradually increase from its initial value of zero to a maximum magnitude; then, the steady-state velocity of the droplet decreases, being more accentuated for the cap regime.

An Accelerated Algorithm for 3D Inversion of Gravity Data Based on Improved Conjugate Gradient Method

The 3D inversion algorithm for gravity data based on a smooth model constraint has been proven to yield a reasonable density distribution. However, as the amount of observed data and model parameters increases, the algorithm experiences issues with high memory consumption and prolonged computation time. Therefore, the corresponding problem in interpreting gravity inversion lies in developing a fast inversion algorithm. The conventional smooth model constraint inversion algorithm, based on regularization theory, requires the introduction of a model weighting function with a large matrix, and involves storage and operation of a large matrix with intermediate variables during inversion iteration, contributing significantly to the prolonged computation time. In this paper, a diagonal weight matrix is represented by vectorization, and the intermediate variable of the large matrix type in the iteration is replaced with the combination of a small matrix and a vector. Additionally, the algorithm flow of the conjugate gradient method is further optimized to minimize the number of vectors that need to be stored during iteration. As a result of these optimizations, the memory consumption of the algorithm during the operation process is successfully reduced. Finally, the experiments demonstrate the successful development of a fast 3D inversion algorithm for gravity data. Specifically, for a 80 × 80 × 20 mesh number inversion, our accelerated algorithm achieves an average speed of ~0.5 s per iteration, and the iterative process speeds up by a factor of 1000, providing an effective strategy for the fast inversion of large-scale data.

An automated method for topology consistent processing of parallel geological cross-sections based on topology reasoning

The 3D modeling method based on parallel geological cross-sections is suitable for modeling large-scale bedrock geological bodies. However, there are usually more branching, pinch-out strata, deformation structures (such as faults and folds), and the correspondence problem of geological boundaries between adjacent cross-sections. These problems have become the most crucial obstacle in the current application of 3D geological modeling based on parallel geological cross-sections. To this end, this paper proposes a topological reasoning automatic processing method for the consistency of parallel geological cross-sections to obtain topologically consistent adjacent cross-sections efficiently. The method involves (1) Stratigraphic inference based on the distance and topological relationships, transforming strata with m:n relationships into three relatively simple cases of 1:1, 1:n, and 1:0; (2) Splitting branching strata based on the Voronoi diagram, transforming strata with 1:n relationships into 1:1 relationships; (3) Dealing pinch-out strata based on the method of filling virtual strata, transforming strata with 1:0 relationships into 1:1 relationships (4) Topologically consistent processing of stratigraphic boundaries based on automatic recognition of no-corresponding arcs and addition of virtual stratum. Based on experiments in the Longtoushan Hill area in Jiangsu Province, China, and the southeast side of Chandler Mountain, Alabama, USA, this method can effectively replace the many manual processes such as determining the location of pinch-out adding auxiliary cross-sections and performing branching strata correspondence in the current application of 3D geological modeling based on arc segments. The geological cross-sections processed based on this method have an exemplary data structure and consistent topological relationships. The 3D geological modeling algorithm based on parallel cross-sections has the advantages of low algorithm complexity, high automation, and stable modeling quality.

2D and 3D object detection algorithms from images: A Survey

2D and 3D object detection algorithms from images: A Survey

Cooperative 3D tunnel measurement based on 2D–3D registration of omnidirectional laser light

AbstractIn this study, we proposed a high‐density three‐dimensional (3D) tunnel measurement method, which estimates the pose changes of cameras based on a point set registration algorithm regarding 2D and 3D point clouds. To detect small deformations and defects, high‐density 3D measurements are necessary for tunnel construction sites. The line‐structured light method uses an omnidirectional laser to measure a high‐density cross‐section point cloud from camera images. To estimate the pose changes of cameras in tunnels, which have few textures and distinctive shapes, cooperative robots are useful because they estimate the pose by aggregating relative poses from the other robots. However, previous studies mounted several sensors for both the 3D measurement and pose estimation, increasing the size of the measurement system. Furthermore, the lack of 3D features makes it difficult to match point clouds obtained from different robots. The proposed measurement system consists of a cross‐section measurement unit and a pose estimation unit; one camera was mounted for each unit. To estimate the relative poses of the two cameras, we designed a 2D–3D registration algorithm for the omnidirectional laser light, and implemented hand‐truck and unmanned aerial vehicle systems. In the measurement of a tunnel with a width of 8.8 m and a height of 6.4 m, the error of the point cloud measured by the proposed method was 162.8 and 575.3 mm along 27 m, respectively. In a hallway measurement, the proposed method generated less errors in straight line shapes with few distinctive shapes compared with that of the 3D point set registration algorithm with Light Detection and Ranging.

Three-dimensional quantification of apple phenotypic traits based on deep learning instance segmentation

Estimating three-dimensional (3D) fruit-level phenotypic traits of apple trees can potentially improve apple orchard breeders' management strategy. However, the phenotypic traits of apple fruits (including the quantity, 3D distribution, and volume of apples) constitute important parameters that influence yield but are difficult to quantify manually. Therefore, it is necessary to effectively and efficiently quantify apple phenotyping to monitor apple yield and support a better management system. This study developed a novel method for extracting individual 3D apple traits and 3D mapping for three apple training systems. The 3D point cloud of apples was reconstructed from multi-view images collected via a multi-camera system-based unmanned-aerial vehicle. Individual apples in the 3D point cloud were extracted via a 3D instance segmentation algorithm that included generalized sparse convolutional neural networks, a weighted discriminative loss function, and a varying density-based 3D clustering method. The developed apple trait extraction algorithm can help compute the position and volume of an individual apple. The R2 values with the average weighted-mean-absolute-percentage error (WMAPE) of apple counting and apple volume estimation were 0.84–0.99 (VMAPE = 3.41–12.75%) and 0.84–0.90 (WMAPE = 4.74–7.03%), respectively. The 3D spatial and volumetric distribution of apples were obtained and analyzed. This study developed an effective method combining 3D photography and 3D instance segmentation that can accurately estimate individual apple phenotypic traits from different types of apple training systems in orchards and can also be utilized for the analysis of other fruit traits.

Three-Dimensional Pore Structure Characterization of Bituminous Coal and Its Relationship with Adsorption Capacity.

Bituminous coal reservoirs exhibit pronounced heterogeneity, which significantly impedes the production capacity of coalbed methane. Therefore, obtaining a thorough comprehension of the pore characteristics of bituminous coal reservoirs is essential for understanding the dynamic interaction between gas and coal, as well as ensuring the safety and efficiency of coal mine production. In this study, we conducted a comprehensive analysis of the pore structure and surface roughness of six bituminous coal samples (1.19% < Ro,max < 2.55%) using various atomic force microscopy (AFM) techniques. Firstly, we compared the microscopic morphology obtained through low-pressure nitrogen gas adsorption (LP-N2-GA) and AFM. It was observed that LP-N2-GA provides a comprehensive depiction of various pore structures, whereas AFM only allows the observation of V-shaped and wedge-shaped pores. Subsequently, the pore structure analysis of the coal samples was performed using Threshold and Chen's algorithms at ×200 and ×4000 magnifications. Our findings indicate that Chen's algorithm enables the observation of a greater number of pores compared to the Threshold algorithm. Moreover, the porosity obtained through the 3D algorithm is more accurate and closely aligns with the results from LP-N2-GA analysis. Regarding the effect of magnification, it was found that ×4000 magnification yielded a higher number of pores compared to ×200 magnification. The roughness values (Rq and Ra) obtained at ×200 magnification were 5-14 times greater than those at ×4000 magnification. Interestingly, despite the differences in magnification, the difference in porosity between ×200 and ×4000 was not significant. Furthermore, when comparing the results with the HP-CH4-GA experiment, it was observed that an increase in Ra and Rq values positively influenced gas adsorption, while an increase in Rsk and Rku values had an unfavorable effect on gas adsorption. This suggests that surface roughness plays a crucial role in gas adsorption behavior. Overall, the findings highlight the significant influence of different methods on the evaluation of pore structure. The 3D algorithm and ×4000 magnification provide a more accurate description of the pore structure. Additionally, the variation in 3D surface roughness was found to be related to coal rank and had a notable effect on gas adsorption.

3D shape recovery algorithm from image orientations of textured surfaces.

Previous psychophysical studies have demonstrated that the image orientation of textured surfaces guides human 3D shape perception. However, the accuracy of computational 3D shape reconstruction solely from image orientation requires further study. This paper proposes a 3D shape recovery algorithm from the image orientation of a single textured surface image. The evaluation of the proposed algorithm uses computer-generated textured complex 3D surfaces. The depth correlations between the recovered and true surface shapes achieved or exceeded 0.8, which is similar to the accuracy of human shape perception, as shown in a previous psychophysical study, indicating that the image orientations contain adequate information for 3D shape recovery from textured surface images.

A flexible optoacoustic blood ‘stethoscope’ for noninvasive multiparametric cardiovascular monitoring

Quantitative and multiparametric blood analysis is of great clinical importance in cardiovascular disease diagnosis. Although there are various methods to extract blood information, they often require invasive procedures, lack continuity, involve bulky instruments, or have complicated testing procedures. Flexible sensors can realize on-skin assessment of several vital signals, but generally exhibit limited function to monitor blood characteristics. Here, we report a flexible optoacoustic blood ‘stethoscope’ for noninvasive, multiparametric, and continuous cardiovascular monitoring, without requiring complicated procedures. The optoacoustic blood ‘stethoscope’ features the light delivery elements to illuminate blood and the piezoelectric acoustic elements to capture light-induced acoustic waves. We show that the optoacoustic blood ‘stethoscope’ can adhere to the skin for continuous and non-invasive in-situ monitoring of multiple cardiovascular biomarkers, including hypoxia, intravascular exogenous agent concentration decay, and hemodynamics, which can be further visualized with a tailored 3D algorithm. Demonstrations on both in-vivo animal trials and human subjects highlight the optoacoustic blood ‘stethoscope’‘s potential for cardiovascular disease diagnosis and prediction.

BED-BPP: Benchmarking dataset for robotic bin packing problems

Many algorithms that were developed for solving three-dimensional bin packing problems use generic data for either experiments or evaluation. However, none of these datasets became accepted for benchmarking 3D bin packing algorithms throughout the community. To close this gap, this paper presents the benchmarking dataset for robotic bin packing problems (BED-BPP), which is based on realistic data. We show the variety of the dataset by elaborating an n-gram analysis. Besides, we propose an evaluation function, which contains a stability check that uses rigid body simulation. We demonstrated the application of our dataset on four different approaches, which we integrated in our software environment.

Applicability of 2D algorithms for 3D characterization in digital rocks physics: an example of a machine learning-based super resolution image generation

Digital rock physics is based on imaging, segmentation and numerical computations of rock samples. Due to challenges regarding the handling of a large 3-dimensional (3D) sample, 2D algorithms have always been attractive. However, in 2D algorithms, the efficiency of the pore structures in the third direction of the generated 3D sample is always questionable. We used four individually captured µCT-images of a given Berea sandstone with different resolutions (12.922, 9.499, 5.775, and 3.436 µm) to evaluate the super-resolution 3D images generated by multistep Super Resolution Double-U-Net (SRDUN), a 2D algorithm. Results show that unrealistic features form in the third direction due to section-wise reconstruction of 2D images. To overcome this issue, we suggest to generate three 3D samples using SRDUN in different directions and then to use one of two strategies: compute the average sample (reconstruction by averaging) or segment one-directional samples and combine them together (binary combination). We numerically compute rock physical properties (porosity, connected porosity, P- and S-wave velocity, permeability and formation factor) to evaluate these models. Results reveal that compared to one-directional samples, harmonic averaging leads to a sample with more similar properties to the original sample. On the other hand, rock physics trends can be calculated using a binary combination strategy by generating low, medium and high porosity samples. These trends are compatible with the properties obtained from one-directional and averaged samples as long as the scale difference between the input and output images of SRDUN is small enough (less than about 3 in our case). By increasing the scale difference, more dispersed results are obtained.

3D DC inversion, visualization, and processing of dense time-lapse data in fine domains applied to remediation monitoring

Using electrical direct-current (DC) data to monitor the subsurface is an efficient solution for observing changes in the shallow subsurface. Recent advances in instrumentation enable the acquisition of large data sets over 3D domains in a reasonable time. We have developed an inversion approach capable of handling very large amounts of data on a finely discretized domain, which enables the delivery of time-lapse results of dense data acquisitions in a feasible time and with high resolution. To spatially represent 3D DC data, a visualization method is introduced that formally generalizes the focusing point of a common pseudosection in three dimensions. The method physically describes subsurface properties for simple geologic scenarios. In addition, the focusing points are used to design our 3D measuring protocol. We develop a DC data processing scheme using the full time-domain induced polarization (IP) waveform data by applying two novel physics-based criteria that enforce charge buildup and steady state. These criteria are tested on DCIP field data and find that 98% of the filtered DC data have less than 1% relative error. The 3D visualization method and inversion algorithm are evaluated on synthetic scenarios of 3D DC dense borehole data. Then, we indicate time-lapse results of DC field data acquired at an uncontaminated site where a remediation agent was injected at depth. The data are acquired with a new DCIP instrument capable of measuring dense data sets at fast acquisition times. Accounting for DCIP data acquisition, signal processing, and 3D inversion of 60,000 DC measurements, our results locate in 14 h the 3D spread of the remediation agent in a [Formula: see text] volume.

A Novel Approach for Bathymetry Estimation through Bayesian Gravity Inversion

The bathymetry is the most superficial layer of the Earth’s crust on which it is possible to perform direct measurements. However, it is also well known that water covers more than 70% of the Earth’s surface, so an enormous expenditure of acquisition campaigns should be performed to produce a high-resolution map of this layer. Currently exploiting mainly commercial navigation routes, the sea floor coverage with shipborne sounding is only at 11%, and the remaining part is currently modeled by classical interpolation techniques or satellite-based gravity inversion methods. In the present work, a new method to refine bathymetry modeling based on the exploitation of global gravity field models is presented. In the proposed solution, once modeled and removed from the observed gravity field, the gravitational signals related to the deepest structures, a 3D Bayesian inversion algorithm is used to improve the actual knowledge of bathymetry. The proposed inversion method also enables limiting the solution to shipborne sounding measurements in such a way as to improve the seafloor grid where no local, high-quality information is available. Two test cases are discussed in the Mediterranean Sea region. Promising results are presented, opening the possibility of applying an analogous method to refine the bathymetry modeling at larger scales up to the global one.

Three-dimensional imaging of martian glaciated terrain using Mars Reconnaissance Orbiter Shallow Radar (SHARAD) observations

We present a three-dimensional radargram of a 13° x 11° region of Deuteronilus Mensae, produced from 457 Mars Reconnaissance Orbiter Shallow Radar (SHARAD) observations. We assess the viability of the 3D imaging algorithms developed to work with SHARAD observations in mid-latitude regions of interest. The quality of subsurface imaging in topographically complex regions is highly improved due to the proper positioning and mitigation of off-nadir reflections in the resulting image. The initial analysis of debris-covered glaciers using 3D radargrams has yielded results that are consistent with previous 2D-based mapping efforts. However, the use of 3D radargrams has enabled the analysis of 3× more area resulting in more accurate estimates of total ice volume, indicating over 9% more ice than previously estimated. Such discrepancies have important implications for Mars climate history studies and in situ resource utilization. The success of this imaging study paves the way for future 3D radargrams in the martian mid-latitudes and stands to increase our confidence in the distribution of many subsurface features of interest.

Multimodal Image Registration Using a Viscous Fluid Model with the Bhattacharyya Distance.

Image registration is an elementary task in medical image processing and analysis, which can be divided into monomodal and multimodal. Direct 3D multimodal registration in volumetric medical images can provide more insight into the interpretation of subsequent image processing applications than 2D methods. This paper is dedicated to the development of a 3D multimodal image registration algorithm based on a viscous fluid model associated with the Bhattacharyya distance. In our approach, a modified Navier-Stoke's equation is exploited as the foundation of the multimodal image registration framework. The hopscotch method is numerically implemented to solve the velocity field, whose values at the explicit locations are first computed and the values at the implicit positions are solved by transposition. The differential of the Bhattacharyya distance is incorporated into the body force function, which is the main driving force for deformation, to enable multimodal registration. A variety of simulated and real brain MR images were utilized to assess the proposed 3D multimodal image registration system. Preliminary experimental results indicated that our algorithm produced high registration accuracy in various registration scenarios and outperformed other competing methods in many multimodal image registration tasks.Clinical Relevance- This facilitates the disease diagnosis and treatment planning that requires accurate 3D multimodal image registration without massive image data and extensive training regardless of the imaging modality.

Optimization of multi-directional functionally graded plates in thermal environment based on 3D isogeometric analysis and adaptive-hybrid evolutionary firefly algorithm

In this study, a numerical model based on three-dimensional isogeometric analysis and adaptive hybrid evolutionary firefly algorithm is developed to concurrently optimize the shape and material distribution of multi-directional functionally graded plates. The optimization problems focus on maximizing the fundamental frequency of the plates subjected to thermal effects, while the volume fraction of ceramic constituent material and volume of the plates are considered as side constraints. Isogeometric multi-mesh design approach is employed to generate design and analysis domain. The free vibration analysis of multi-directional functionally graded plates with variable thickness is conducted within the framework of three-dimensional elasticity theory and isogeometric analysis. The generalized numerical framework developed in this study could accurately capture the thermal effects on the behavior of nonhomogeneous plates with variable thickness. Various numerical examples are conducted to illustrate the optimal shapes and material distributions within square, rectangular, and circular plates. Influences of temperature field, boundary conditions, and geometries of the plates on the optimal results are also addressed.