Three-dimensional Data Acquisition Research Articles

Current Status and Analysis of the Clinical Application of Digital Technology in Oral Medicine

With the increasing maturity and popularization of digital technology in oral medicine, its application has now expanded to various clinical subspecialties of oral medicine. Digitalization has become one of the important development directions of oral medicine. What is the current development status of digital technology in oral medicine? In what ways is digital technology applied across various clinical specialties of oral medicine? Dentists are particularly concerned about these issues in their clinical work and research. In this paper, all the digital technologies applied in oral medicine are organized and categorized from a technical perspective. In this paper, we focused on presenting three-dimensional data acquisition technology, dental computer-aided design technology, dental computer-aided processing technology, and oral surgery implementation technology. Their technical principles, technical characteristics, applications in oral medicine, a secondary discipline of medicine, and the development status of domestically-developed technology are described and reviewed in detail. The other technologies such as oral digital materials, oral virtual simulation teaching, and oral multi-source data management are briefly discussed. We intend to provide references for dentists to apply digital technology in clinical practice and research.

Accurate and semantic 3D reconstruction of maize leaves

The rapid advances in equipment and technology for crop three-dimensional (3D) data acquisition have enabled the high-throughput and high-quality acquisition of crop 3D data. However, the challenge now lies in comprehending unstructured crop 3D data and extracting phenotypes and knowledge. Extracting semantic feature points from plant leaves and achieving high-precision 3D reconstruction is a prevalent and formidable issue in this field. In this study, we present an accurate method for semantic 3D reconstruction of maize leaves. The algorithm utilizes 3D point cloud data of maize leaves as the initial input. Subsequently, the semantic 3D reconstruction of maize leaves is achieved by means of point cloud preprocessing, initial triangular meshing, hole filling, remeshing, mesh parameterization, two-dimensional (2D) edge detection, 2D semantic point interpolation, 3D semantic point selection, mesh generation, and optimization of feature-point position. A total of 56 leaves from five different maize cultivars were reconstructed utilizing this method. The results indicate that the average distance error index dCDMP between the reconstructed mesh vertices and the input point cloud is less than 0.3 cm2 for all five cultivars, and the mean of the maximum distance error index dHDMP for each cultivar is within the range of 0.5–0.8 cm, indicating it is high-accuracy. The visualization of leaves shows good consistency between the reconstructed mesh and corresponding point cloud. Additionally, the reconstructed 3D mesh of the leaves exhibits enhanced triangular facet consistency. Each vertex can be precisely identified as a leaf vein point, leaf edge point, leaf tip point, or leaf surface point, and includes semantic data such as the position on the leaf blade, which can be directly employed for phenotype estimations. High-precision reconstruction of 3D models of crop organs that include semantic information and cultivar resolution yields significant benefits. This technology can improve the resolution and accuracy of crop morphological and structural research, and it is also crucial for crop phenomics, functional-structural plant modelling, and fusion research between plant phenotyping and crop models.

EVALUATION OF A LOW-COST PHOTOGRAMMETRIC SYSTEM FOR THE RETRIEVAL OF 3D TREE ARCHITECTURE

Abstract. Reconstruction of major branches of a tree is an important first step for the monitoring of tree sway and assessment of structural stability. Photogrammetric systems can provide a low-cost alternative for the acquisition of three-dimensional data, while also enabling long-term monitoring of a tree of interest. This study introduces a low-cost photogrammetric system based on two Raspberry Pi cameras, which is used to reconstruct the tree architecture for the purpose of stability monitoring. Images of five trees are taken at a range of distances and the resulting point clouds are evaluated in terms of point density and distribution with the reference to TLS. While the photogrammetric point clouds are sparse, it was found that they are capable of reconstructing the tree trunk and lower-order branches, which are most relevant for sway monitoring and tree stability assessment. The most optimal distance for the reconstruction of the relevant branches was found to be 9–10 m, with a baseline of 120 cm.

A geometric assessment method for estimating dimensional change of retrieved dual mobility liners for total hip arthroplasty.

Despite their emerging use, the current understanding of the in-vivo functional mechanisms of Dual Mobility (DM) Total Hip Replacements (THRs) is poor, and current characterisation methodologies are not suitable for the unique function and design of these types of devices. Therefore, the aim of this study was to develop a geometric characterisation methodology to estimate dimensional change across the articulating surfaces of retrieved DM polyethylene liners so that their invivo function may be better understood. The method involves the acquisition of three-dimensional coordinate data from the internal and external surfaces of DM liners. The data is processed using a bespoke MATLAB script which approximates the unworn reference geometry of each surface, calculates geometric variance at each point and produces surface deviation heatmaps so that areas of wear and/or deformation may be visualised across the implant. One as-manufactured and five retrieved DM liners were assessed, which demonstrated the efficacy, repeatability and sensitivity of the developed method. This study describes an automated and non-destructive approach for assessing retrieved DM liners of any size and from any manufacturer, which may be used in future research to improve our understanding of their in-vivo function and failure mechanisms.

Aided Imaging Phase Measuring Deflectometry Based on Concave Focusing Mirror

With the rapid development of aerospace, high-speed train, and automotive industries, the demand for the measurement of high-precision specular components is increasing. The acquisition of high-precision three-dimensional (3D) data is conducive to improving the performance of and extending the service life of these components. However, the existing 3D measurement methods of specular surfaces are affected by the inherent limitation of the depth of field (DOF) of camera lenses. Based on the principle of paraxial reflection imaging of a concave mirror, this paper introduces a concave mirror into a phase measuring deflectometry (PMD) system and proposes an aided imaging PMD (AIPMD) based on a concave focusing mirror. The proposed system realizes the clear imaging of the encoded patterns and the surface under test in the DOF of the camera lens, simultaneously. Meanwhile, the iterative coefficient specular reconstruction algorithm is studied based on this system. The feasibility and accuracy of the proposed method are verified by simulations and experiments.

Confocal LiDAR for remote high-resolution imaging of auto-fluorescence in aquatic media

Spatially resolved in situ monitoring of plankton can provide insights on the impacts of climate change on aquatic ecosystems due to their vital role in the biological carbon pump. However, high-resolution underwater imaging is technically complex and restricted to small close-range volumes with current techniques. Here, we report a novel inelastic scanning confocal light detection and ranging (LiDAR) system for remote underwater volumetric imaging of fluorescent objects. A continuous wave excitation beam is combined with a pinhole in a conjugated detection plane to reject out-of-focus scattering and accomplish near-diffraction limited probe volumes. The combination of bi-directional scanning with remote focusing enables the acquisition of three-dimensional data. We experimentally determine the point spread and axial weighting functions, and demonstrate selective volumetric imaging of obstructed layers through spatial filtering. Finally, we spatially resolve in vivo autofluorescence from sub-millimeter Acocyclops royi copepods to demonstrate the applicability of our novel instrument in non-intrusive morphological and spectroscopic studies of aquatic fauna. The proposed system constitutes a unique tool e.g. for profiling chlorophyll distributions and for quantitative studies of zooplankton with reduced interference from intervening scatterers in the water column that degrade the the performance of conventional imaging systems currently in place.

Research and design of a deformation monitoring system for the platform and canopy of a railway station

In this paper, the deformation of the platform and canopy of a high-speed railway station is studied, and an online monitoring system for platform canopy deformation is designed to solve the problem of online monitoring of platform canopy deformation. Due to the conventional one-dimensional measurement has been difficult to meet the needs of high-speed railway industrial production and daily life. Nowadays, laser radar and binocular cameras for three-dimensional data measurement have gradually emerged. At present, there is almost no three-dimensional data acquisition equipment with high measurement accuracy, low price, and a high degree of automation in the market. Given the lack of this equipment in the market, this paper presents a three-dimensional data acquisition system based on a laser rangefinder. By collecting, processing, and analyzing the data of the platform and canopy, the purpose of prediction can be achieved, and then the abnormal response, damage, and degradation of the structure can be found in time. The study shows that the monitoring system is helpful to detect deformation and give early warning, and effectively prevent the occurrence of hazards.

Three-Dimensional Digital Image Correlation Based on Speckle Pattern Projection for Non-Invasive Vibrational Analysis.

Non-contact vibration measurements are relevant for non-invasively characterizing the mechanical behavior of structures. This paper presents a novel methodology for full-field vibrational analysis at high frequencies using the three-dimensional digital image correlation technique combined with the projection of a speckle pattern. The method includes stereo calibration and image processing routines for accurate three-dimensional data acquisition. Quantitative analysis allows the extraction of several deformation parameters, such as the cross-correlation coefficients, shape and intensity, as well as the out-of-plane displacement fields and mode shapes. The potential of the methodology is demonstrated on an Unmanned Aerial Vehicle wing made of composite material, followed by experimental validation with reference accelerometers. The results obtained with the projected three-dimensional digital image correlation show a percentage of error below 5% compared with the measures of accelerometers, achieving, therefore, high sensitivity to detect the dynamic modes in structures made of composite material.

A miniaturized phenotyping platform for individual plants using multi-view stereo 3D reconstruction.

Plant phenotyping is essential in plant breeding and management. High-throughput data acquisition and automatic phenotypes extraction are common concerns in plant phenotyping. Despite the development of phenotyping platforms and the realization of high-throughput three-dimensional (3D) data acquisition in tall plants, such as maize, handling small-size plants with complex structural features remains a challenge. This study developed a miniaturized shoot phenotyping platform MVS-Pheno V2 focusing on low plant shoots. The platform is an improvement of MVS-Pheno V1 and was developed based on multi-view stereo 3D reconstruction. It has the following four components: Hardware, wireless communication and control, data acquisition system, and data processing system. The hardware sets the rotation on top of the platform, separating plants to be static while rotating. A novel local network was established to realize wireless communication and control; thus, preventing cable twining. The data processing system was developed to calibrate point clouds and extract phenotypes, including plant height, leaf area, projected area, shoot volume, and compactness. This study used three cultivars of wheat shoots at four growth stages to test the performance of the platform. The mean absolute percentage error of point cloud calibration was 0.585%. The squared correlation coefficient R2 was 0.9991, 0.9949, and 0.9693 for plant height, leaf length, and leaf width, respectively. The root mean squared error (RMSE) was 0.6996, 0.4531, and 0.1174 cm for plant height, leaf length, and leaf width. The MVS-Pheno V2 platform provides an alternative solution for high-throughput phenotyping of low individual plants and is especially suitable for shoot architecture-related plant breeding and management studies.

Identification Model of Writhing Posture of Classical Dance Based on Motion Capture Technology and Few-Shot Learning.

Chinese classical dance is cut into the inner verve from a grasp of external form in dance instruction, and the aesthetic fashion and artistic norms of classical dance are established with historical depth. The “professional specificity” of characters and the “language description” of plots are eliminated in Chinese classical dance creation, highlighting the contemporary spirit of classical dance creation. Chinese classical dance was born during the early years of the People's Republic of China. The term “classical dance” did not refer to all Chinese classical dances at the time; rather, it referred to a dance form that embodied China's national spirit and had a classical cultural heritage based on Chinese traditional dance. The average frequency of step-over was 0.9, which was higher than the average rate of basic turnover of 0.75 and step-by-step turnover of 0.5, according to the results of the SPSS19.0 analysis. As a result, except for a few points with loud noise, it can be concluded that stepping over is an effective feature. The recognition model of the somersault posture of classical dance is studied in this paper, a database for real-time acquisition of three-dimensional data of human motion is established, and the Google model of human body characteristics is obtained based on feature plane matching of human body posture, all using motion capture technology and few-shot learning. The above data has good reference and application value for improving teachers' teaching level and arousing students' learning enthusiasm in the dance teaching process when applied to posture teaching and analysis. The captured data can convert human motion in real three-dimensional space into data in virtual three-dimensional space. Motion capture technology converts human motion information into a technology that can be recognized by computers.

Research on three-dimensional spectrum mapping driven by propagation model

Spectrum map is the foundation of spectrum resource management, security governance and spectrum warfare. Aiming at the problem that the traditional spectrum mapping is limited to two-dimensional space, a three-dimensional spectrum data acquisition and mapping system architecture for the integration of space, sky and earth is presented, and a spectrum map reconstruction scheme driven by propagation model is proposed, which can achieve high-precision three-dimensional spectrum map rendering under the condition of sparse sampling. The spectrum map reconstructed by this method in the case of single radiation source and multiple radiation sources is in good agreement with the theoretical results based on ray tracing method. In addition, the measured results of typical scenes further verify the feasibility of this method.

Pose Tracking of Spacecraft Based on Point Cloud DCA Features

As a key on-orbit service technology, relative measurement of non-cooperative spatial targets can give accurate relative pose for the unmanned rendezvous and docking of non-cooperative targets. With the rapid development of three-dimensional data acquisition equipment such as flash lidar in the field of non-cooperative targets’ pose measurement in recent years, research on the pose tracking technology based on the three-dimensional (3D) point cloud of non-cooperative targets has become more and more urgent. In this paper, we proposed an approach for autonomous recognition and pose tracking of non-cooperative targets based on point cloud features. For this method, the density, curvature and normal angle of a non-cooperative target 3D point cloud are first calculated as the local feature description (DCA) of the point cloud, and then the feature description is used to match and remove errors through RANSAC. Finally the Iterative Closest Point (ICP) algorithm is adopted to obtain the precise pose of the non-cooperative target. Experimental results have shown that this approach can effectively find the features of non-cooperative tumbling targets, get rid of the dependence on the target model and database, and realize the pose tracking of non-cooperative targets.

757 Cardio-TC role in patients selection for transcatheter edge to edge tricuspid repair

Abstract Aims Anatomic knowledge of the tricuspid valve (TV) is the first step in the management of patients with tricuspid regurgitation (TR) who are candidates for transcatheter tricuspid valve intervention (TTVI). Echocardiography is undoubtedly the first approach in assessing the aetiology and severity of TR and the size and function of the right chambers. Computed tomography (CT) provides a detailed morphological visualization of the cardiac structures owing to acquisition of 3D data with high spatial resolution. These findings may undoubtedly help in decision-making progress for novel transcatheter therapies. The purpose of the present study was to assess the geometrical changes of the TV complex using CT images, in patients suffering from functional TR and lead-induced TR. Methods The study population consisted of 21 consecutive patients with symptomatic severe TR referred to Policlinico Universitario Campus Biomedico between November 2020 and October 2021. Patients were prospectively included in the study only if they presented severe TR, diagnosed by echocardiography and underwent cardiac CT study dedicated to the right-chambers. The reconstructions were transferred to an external workstation for off-line image analysis. The following measurements were reported: tricuspid annulus area, perimeter, septal–lateral and antero-posterior diameters. Commissures were identified as antero-septal (AS), postero-septal (PS) and anteroposterior (AP). Were measured the inferior vena cava ostium to tricuspid valve centroid distance, anatomic regurgitant orifice area (AROA) and its position respect to the centroid, and the right chambers. Results All 21 patients underwent CT scan using Siemens SOMATOM Definition AS 128 Slice CT Machine. The measurements were calculated off-line using the 3mensio workstation. In our study population, the annulus resulted enlarged in the annulus area, perimeter, septal-lateral and anterior-posterior dimensions. Measurements did not differ significantly, except for the septal-lateral diameter that was smaller in systole (52.80 ± 7.28 mm vs. 47.83 ± 6.83 mm (P=0.027). Also, distances between the commissures were similar except for the AP-AS distance that was shorter in systole (45.26 ± 3.48 mm vs. 42.13 ± 3.73, P=0.007). The AROA resulted to be central in 7 patients, the IVC ostium to TV centroid distance was 23±3 mm. Right chambers and IVC resulted very enlarged in all patients. Conclusions CT provides a complete morphologic imaging of the heart structures, thanks to a high spatial resolution with excellent capacity to define the endocardial border and allows acquisition of three-dimensional data with high spatial resolution of the TV and provides valuable information about the geometric variations of the tricuspid complex in patients with TR. Image quality for analysis should be optimized with specific CT acquisition protocols that focus on the right ventricles.

Whole Three-Dimensional Dosimetry of Carbon Ion Beams with an MRI-Based Nanocomposite Fricke Gel Dosimeter Using Rapid T1 Mapping Method.

MRI-based gel dosimeters are attractive systems for the evaluation of complex dose distributions in radiotherapy. In particular, the nanocomposite Fricke gel dosimeter is one among a few dosimeters capable of accurately evaluating the dose distribution of heavy ion beams. In contrast, reduction of the scanning time is a challenging issue for the acquisition of three-dimensional volume data. In this study, we investigated a three-dimensional dose distribution measurement method for heavy ion beams using variable flip angle (VFA), which is expected to significantly reduce the MRI scanning time. Our findings clarified that the whole three-dimensional dose distribution could be evaluated within the conventional imaging time (20 min) and quality of one cross-section.

LED source interferometer for microscopic fringe projection profilometry using a Gates’ interferometer configuration

The fringe projection technique is considered one of the most reliable solutions for structured light technology, developed for non-contact three-dimensional (3D) data acquisition. When working with this technique, applying it on a microscopic scale, one often encounters some problems such as the limited depth of field of the projected fringe pattern, typical of the imaging lenses, or the formation of speckle-noise when laser interferometric fringes are projected, which are problems that can cause significant errors on test surfaces whose height exceeds the depth of field, and on which, the other hand, speckle noise affects the resolution of the technique. This paper presents a Gates’ interferometer configuration with a LED source to project a fringe pattern without speckle noise and a very long field depth. We explain how a non-located sinusoidal fringe pattern can be obtained using two-beamsplitter cubes and a LED light source. Moreover, we compare measurements made using the LED and laser concerning a commercial contact profilometer.

Automated defect inspection of concrete structures

This paper presents a framework for automated defect inspection of the concrete structures, made up of data collection, defect detection, scene reconstruction, defect assessment and data integration stages. A mobile data collection system, comprising a 360° camera and a digital Light Detection and Ranging (LiDAR), is developed to render high flexibility of data acquisition of image and three-dimensional spatial data, while users traverse complex indoor environments. Deep learning algorithms are implemented to efficiently detect defects from the collected images, and a simultaneous localization and mapping algorithm is adopted for site reconstruction with the acquired LiDAR data. Based on the images of detected defects, assessment is conducted to evaluate the defect conditions, complemented with the defect dimensions estimated from the aligned image and LiDAR data. The position of defects could also be identified and mapped to respective structural elements. All the inspection results are finally integrated into existing Building Information Modelling files for better facility management. The proposed workflow was validated using a case study for determining concrete cracks and spalls in a real-world facility, successfully demonstrating the joint application of advanced technologies in facilitating inspection programs of civil infrastructure.

"3-D Dental Measurement Using A Non-Contact Optical Technique"

This research is aimed at creating a system of automatic acquisition of three-dimensional data with one or more teeth...

3D face imaging with the spatial-temporal correlation method using a rotary speckle projector.

In this paper, a compact, cost-effective, and fast rotary speckle projector (RSP) is designed and manufactured for high-precision three-dimensional (3D) face data acquisition. Compared with the common speckle projectors, RSP uses a simple speckle pattern design method and has a good performance in high-speed projection and compact structure, which allows a flexible balance between measurement accuracy and time cost in a real acquisition task. Using a carefully designed rotation angle of the speckle mask, temporally and spatially non-correlative speckle patterns in the measurement volume can be generated. The rotation angle of the speckle mask is carefully checked and optimally selected via detailed theoretical analysis, simulation, and experiments to ensure 3D reconstruction accuracy across the reconstruction area. Subsequently, a binocular 3D face imaging system composed of the RSP and two cameras is constructed. With captured stereo speckle image pairs, we adopted our previously well-established spatial-temporal correlation method to determine the disparity. The accuracy of the 3D face imaging system was verified by using a real face mask, which is standardized by a certified, high-precision industrial 3D scanner. The real face data collection under various expressions has demonstrated that the proposed system also has a good performance for 3D face imaging in dynamic scenes.

Research on Classification Method of 3D Point Cloud Model Based on KE-PointVNet

With the popularization and use of three-dimensional data acquisition equipment, the acquisition of three-dimensional data is more convenient. Three-dimensional data contains rich shape and scale information. How to effectively and accurately classify, segment and identify three-dimensional data is a research hotspot in the field of computer vision. Aiming at the particularity of 3D point cloud data and the neglect of local correlation between points, this paper proposes a new end-to-end depth network framework, namely KE-PointVNet. KE-PointVNet can directly deal with point cloud and construct deep convolutional network. KE-PointVNet extracts local geometric features of each point based on the EdgeConv module. By using the KNN proximity algorithm to construct local neighborhood of the point cloud, it can avoid its non-local diffusion, and finally obtain the high-level semantics of the point cloud through the local aggregation vector VLAD layer. The experimental results show that this method has a higher classification accuracy than most of the existing point cloud classification methods.

Three-Dimensional, Real-Time, and Intelligent Data Acquisition of Large Deformation in Deep Tunnels

Potential disasters of large deformation pose serious threats to deep underground projects such as tunnels and mines. Engineering with large deformation is typically characterized by high stress, complex engineering geology, strong disturbance, and squeezing deformation, posing a great challenge to the design of an effective and accurate monitoring system. To address this problem, it is necessary to grasp the three-dimensional features of deformation and establish integrated monitoring of a support system. Monitoring equipment should be selected to obtain joint, stress, deformation, cracking process, and other information, and this information can be fed back to the warning and control module. The scheme of the monitoring system presented here was successfully applied to a deep metal mine. This intelligent monitoring system ensures safety during the construction and operation of the tunnel under complex surrounding rock conditions, allows the use of field monitoring data to guide construction and design, and provides a reference for future construction and project monitoring.