Voxel Model Research Articles

Voxel modeling and association of ubiquitous spatiotemporal information in natural language texts

ABSTRACT The ubiquitous spatiotemporal information extracted from Internet texts limits its application in spatiotemporal association and analysis due to its unstructured nature and uncertainty. This study uses ST-Voxel modeling to solve the problem of structured modeling and the association of ubiquitous spatiotemporal information in natural language texts. It provides a new solution for associating ubiquitous spatiotemporal information on the Internet and discovering public opinion. The main contributions of this paper include: (1) It proposes a convolved method for ST-Voxel, which solves the voxel modeling problem of unstructured and uncertain spatiotemporal objects and spatiotemporal relation in natural language texts. Experiments show that this method can effectively model 5 types of spatiotemporal objects and 16 types of uncertain spatiotemporal relation founded in texts; (2) It realizes the unknown event discovery based on voxelized spatiotemporal information association. Experiments show that this method can effectively solve the aggregation of ubiquitous spatiotemporal information in multi-natural language texts, which is conducive to discovering spatiotemporal events. The selection of convolution parameters in voxel modeling is also discussed. A parameter selection method for balancing the discovery capability and discovery accuracy of spatiotemporal events is given.

Improving the Probability of Stroke Detection inside the Human Head Using Wideband Polarimetric Synthetic Aperture Radar Imaging

This paper presents an imaging system based on ultrawideband microwave radars for the detection of bleeding regions and strokes inside the human head. The proposed system is portable and focuses on revealing bleeding areas with unpredictable shapes using polarimetric data acquisition. A custom-designed dual-polarized bowtie patch antenna capable of pumping the UWB pulses inside the patient’s head is designed and presented as the biomedical sensor for the system. The antenna dimensions are 25 × 25 m m 2 . It mitigates the mismatch between the air and skin needles of any coupling liquid, resulting in safe SAR levels below 0.5 W/kg and wideband operating bandwidth that covers 1.2-4.5 GHz with unidirectional radiations. To collect the raw polarimetric data, an elliptical array of the proposed antenna is formed around the patient’s head model that includes 16 elements in direct contact with the phantom. The performance of the proposed method is validated through an imaging scenario with two nonuniform bleeding areas inside the patient head model. The whole structure is simulated with a Gaussian pulse as the excitation using CST Microwave Studio tools. To produce 2D images of the voxel model, the time-domain elliptical synthetic aperture radar (ESAR) imaging algorithm is applied. Accurately detecting the presence and shape of anomalies in reconstructed images using the proposed method demonstrates the efficiency of the proposed system and determines its advantages over single-polarization systems.

Radiofrequency antenna concepts for human cardiac MR at 14.0 T

ObjectiveTo examine the feasibility of human cardiac MR (CMR) at 14.0 T using high-density radiofrequency (RF) dipole transceiver arrays in conjunction with static and dynamic parallel transmission (pTx).Materials and methodsRF arrays comprised of self-grounded bow-tie (SGBT) antennas, bow-tie (BT) antennas, or fractionated dipole (FD) antennas were used in this simulation study. Static and dynamic pTx were applied to enhance transmission field (B1+) uniformity and efficiency in the heart of the human voxel model. B1+ distribution and maximum specific absorption rate averaged over 10 g tissue (SAR10g) were examined at 7.0 T and 14.0 T.ResultsAt 14.0 T static pTx revealed a minimum B1+ROI efficiency of 0.91 μT/√kW (SGBT), 0.73 μT/√kW (BT), and 0.56 μT/√kW (FD) and maximum SAR10g of 4.24 W/kg, 1.45 W/kg, and 2.04 W/kg. Dynamic pTx with 8 kT points indicate a balance between B1+ROI homogeneity (coefficient of variation < 14%) and efficiency (minimum B1+ROI > 1.11 µT/√kW) at 14.0 T with a maximum SAR10g < 5.25 W/kg.DiscussionMRI of the human heart at 14.0 T is feasible from an electrodynamic and theoretical standpoint, provided that multi-channel high-density antennas are arranged accordingly. These findings provide a technical foundation for further explorations into CMR at 14.0 T.

Computer Aided Process Planning for Rough Machining Based on Machine Learning with Certainty Evaluation of Inferred Results

Process planning is well known as the key toward achieving highly efficient machining. However, it is difficult to standardize machining skills for process planning, which depend heavily on skilled operators. Hence, in a previous study, a computer aided process planning (CAPP) system using machine learning is developed to determine the operation parameters for finish machining of dies and molds. On the other hand, in rough machining, it is assumed that some machining operations are conducted sequentially using a respective tool according to the workpiece shape, which induces a much higher complexity in process planning. Therefore, in this study, machine learning is adopted to determine operation parameters for rough machining. The developed CAPP system converts the removal volume into a voxel model and infers a machining operation for each voxel. The inferred machining operation is visualized using different colors and identified corresponding to the voxel. Finally, the removal volume is classified using three different machining operations. However, machine learning is said to have a critical problem in that it is difficult to understand the reasons for the inferred results. Hence, it is necessary for the CAPP system to demonstrate the certainty level of the determined operation parameters. Thus, this study proposes a method for calculating the degree of certainty. If an artificial neural network is trained sufficiently, similar inferred results would always be obtained. Consequently, by using the Monte Carlo dropout to delete weights at random, the certainty level is defined as the variance of the inferred results. To verify the usefulness of the CAPP system, a case study is conducted by assuming rough machining of dies and molds. The results confirm that the machining operations are inferred with high accuracy, and the proposed method is effective for evaluating the certainty of the inferred results.

Towards an integrated radiofrequency safety concept for implant carriers in MRI based on sensor-equipped implants and parallel transmission.

To protect implant carriers in MRI from excessive radiofrequency (RF) heating it has previously been suggested to assess that hazard via sensors on the implant. Other work recommended parallel transmission (pTx) to actively mitigate implant-related heating. Here, both ideas are integrated into one comprehensive safety concept where native pTx safety (without implant) is ensured by state-of-the-art field simulations and the implant-specific hazard is quantified in situ using physical sensors. The concept is demonstrated by electromagnetic simulations performed on a human voxel model with a simplified spinal-cord implant in an eight-channel pTx body coil at . To integrate implant and native safety, the sensor signal must be calibrated in terms of an established safety metric (e.g., specific absorption rate [SAR]). Virtual experiments show that -field and implant-current sensors are well suited for this purpose, while temperature sensors require some caution, and probes are inadequate. Based on an implant sensor matrix , constructed in situ from sensor readings, and precomputed native SAR limits, a vector space of safe RF excitations is determined where both global (native) and local (implant-related) safety requirements are satisfied. Within this safe-excitation subspace, the solution with the best image quality in terms of magnitude and homogeneity is then found by a straightforward optimization algorithm. In the investigated example, the optimized pTx shim provides a 3-fold higher magnitude compared with circularly polarized excitation for a maximum implant-related temperature increase . To date, sensor-equipped implants interfaced to a pTx scanner exist as demonstrator items in research labs, but commercial devices are not yet within sight. This paper aims to demonstrate the significant benefits of such an approach and how this could impact implant-related RF safety in MRI. Today, the responsibility for safe implant scanning lies with the implant manufacturer and the MRI operator; within the sensor concept, the MRI manufacturer would assume much of the operator's current responsibility.

Three-Dimensional Computational Model Simulating the Initial Callus Growth during Fracture Healing in Long Bones: Application to Different Fracture Types.

Bone fractures are among the most common and potentially serious injuries to the skeleton, femoral shaft fractures being especially severe. Thanks to recent advances in the area of in silico analysis, several approximations of the bone healing process have been achieved. In this context, the objective of this work was to simulate the initial phase of callus formation in long bones, without a pre-meshed domain in the 3D space. A finite element approach was computationally implemented to obtain the values of the cell concentrations along the whole domain and evaluate the areas where the biological quantities reached the thresholds necessary to trigger callus growth. A voxel model was used to obtain the 3D domain of the bone fragments and callus. A mesh growth algorithm controlled the addition of new elements to the domain at each step of the iterative procedure until complete callus formation. The implemented approach is able to reproduce the generation of the primary callus, which corresponds to the initial phase of fracture healing, independently of the fracture type and complexity, even in the case of several bone fragments. The proposed approach can be applied to the most complex bone fractures such as oblique, severely comminuted or spiral-type fractures, whose simulation remains hardly possible by means of the different existing approaches available to date.

Effect of subject-specific head morphometry on specific absorption rate estimates in parallel-transmit MRI at 7 T.

To assess the accuracy of morphing an established reference electromagnetic head model to a subject-specific morphometry for the estimation of specific absorption rate (SAR) in 7T parallel-transmit (pTx) MRI. Synthetic T1 -weighted MR images were created from three high-resolution open-source electromagnetic head voxel models. The accuracy of morphing a "reference" (multimodal image-based detailed anatomical [MIDA]) electromagnetic model into a different subject's native space (Duke and Ella) was compared. Both linear and nonlinear registration methods were evaluated. Maximum 10-g averaged SAR was estimated for circularly polarized mode and for 5000 random RF shim sets in an eight-channel transmit head coil, and comparison made between the morphed MIDA electromagnetic models and the native Duke and Ella electromagnetic models, respectively. The averaged error in maximum 10-g averaged SAR estimation across pTx MRI shim sets between the MIDA and the Duke target model was reduced from 17.5% with only rigid-body registration, to 11.8% when affine linear registration was used, and further reduced to 10.7% when nonlinear registration was used. The corresponding figures for the Ella model were 16.7%, 11.2%, and 10.1%. We found that morphometry accounts for up to half of the subject-specific differences in pTx SAR. Both linear and nonlinear morphing of an electromagnetic model into a target subject improved SAR agreement by better matching head size, morphometry, and position. However, differences remained, likely arising from details in tissue composition estimation. Thus, the uncertainty of the head morphometry and tissue composition may need to be considered separately to achieve personalized SAR estimation.

A Survey of the Landscape Visibility Analysis Tools and Technical Improvements.

Visual perception of the urban landscape in a city is complex and dynamic, and it is largely influenced by human vision and the dynamic spatial layout of the attractions. In return, landscape visibility not only affects how people interact with the environment but also promotes regional values and urban resilience. The development of visibility has evolved, and the digital landscape visibility analysis method allows urban researchers to redefine visible space and better quantify human perceptions and observations of the landscape space. In this paper, we first reviewed and compared the theoretical results and measurement tools for spatial visual perception and compared the value of the analytical methods and tools for landscape visualization in multiple dimensions on the principal of urban planning (e.g., complex environment, computational scalability, and interactive intervention between computation and built environment). We found that most of the research was examined in a static environment using simple viewpoints, which can hardly explain the actual complexity and dynamic superposition of the landscape perceptual effect in an urban environment. Thus, those methods cannot effectively solve actual urban planning issues. Aiming at this demand, we proposed a workflow optimization and developed a responsive cross-scale and multilandscape object 3D visibility analysis method, forming our analysis model for testing on the study case. By combining the multilandscape batch scanning method with a refined voxel model, it can be adapted for large-scale complex dynamic urban visual problems. As a result, we obtained accurate spatial visibility calculations that can be conducted across scales from the macro to micro, with large external mountain landscapes and small internal open spaces. Our verified approach not only has a good performance in the analysis of complex visibility problems (e.g., we defined the two most influential spatial variables to maintain good street-based landscape visibility) but also the high efficiency of spatial interventions (e.g., where the four recommended interventions were the most valuable), realizing the improvement of intelligent landscape evaluations and interventions for urban spatial quality and resilience.

Color printing based on 3MF: Color diffusion from the surface to the interior of voxel model

AbstractFull‐color 3D printing technology has become more and more popular for industrial manufacturing applications. The voxelization of color 3D models and the expression of appearance colors become more and more important. To illustrate the complex appearance and internal characteristics of 3D models, we present a voxelization algorithm of the color 3D models for color 3D printing in this paper. Specifically, we use the 3D model of 3D Manufacturing Format (3MF) with color appearance features for surface voxelization first. Then, we propose an improved scan line filling algorithm to realize the voxelization of the interior of the model and obtain the color voxel model. Finally, to improve the high quality of color printing, we propose a surface color inward diffusion algorithm, which can make the surface color of the voxel model diffuse inward and further express the surface color of the voxel model. The experimental results show our proposed method can obtain an effective color voxel model and accurately express the color of the voxel model surface, which can enhance the color effect of the color model and realize the control of voxels.

Quality analysis of voxel models obtained with remote sensing

Use of the resource potential of the Arctic is impossible without reliable information about the spatial and temporal characteristics of the developed territories. The topographic and bathymetric information are needed to solve engineering and logistic tasks. Furthermore, surveying, geodetic surveying and geological surveys in these territories are limited by climatic conditions and their infrastructural remoteness. That means, that it’s needed to replace classical methods of performing geodetic works and surveys with the presence of workers on the object with modern automated methods of remote sensing of territories. That methods include the technologies of multipath echo-location, aerial or terrestrial laser scanning, photogrammetry and space sensing of the Earth. Despite the differences between these technologies, they are united by the result, the geospatial data, often called a “point cloud”. Such point clouds are not regular in their structure and form 3D-model of the object due to the redundant data, which makes processing, systematizing and storing this kind of the information more difficult. The paper considers the method of generalization of geospatial data, that allows to reduce these disadvantages by approximating local sections of the model with planes that fit into a fragment of a point cloud using the least squares method. The model described in the paper allow to statistically assess the quality of the initial data, to simplify next mathematical processing for solving specific engineering problems, including geomechanical, environmental and glaciological monitoring.

A Pose-Normalization Method for Casting Voxel Models Using Second-Order Central Moment Matrix

Within the framework of casting process design, the efficient retrieval of three-dimensional (3D) computer-aided design (CAD) models could result in significant time and cost savings. However, this technique still suffers from inefficiency and inaccuracy because of the wide variety of casting models’ poses. In this study, a method for normalizing the poses of casting models is proposed. This method constructs the transformation matrix through the eigendecomposition of the second-order central moment matrix calculated from the voxel casting model. Then the transformation matrix is applied to the casting model to get a normalized pose. An assessment approach for pose normalization is also suggested in the study, which measures the distance between poses normalized based on multiple poses of the same model. The study demonstrates that the pose-normalization approach reliably transforms distinct poses of the same model into a unified pose. The mean distance between normalized poses is 0.016 and the minimum distance is 0.010. The method’s effects improve when the voxel size reduces.

Wire-EDM geometrical simulation based on superposition of single craters

Setting EDM technology parameters is a time consuming and expensive process. The development of a process model facilitates the understanding of the input parameters on the process results, which can speed up the selection of the optimal technology for a cut. This work aims to model the wire-EDM machining process with a three-dimensional geometrical voxel model through the sequential placement of single craters. To model workpiece sizes closer to reality, 2.25 109 voxel elements are used to construct the virtual workpiece. The simulation showed that under the same pulse energy conditions, main cut simulations have a smaller average roughness compared to trim cuts, a claim that is supported by experiments presented in this work. This disparity is related to the direction of the craters imposed by the geometrical conditions, i.e. the position of the wire relative to the workpiece. Furthermore, the simulation showed proportional roughness values compared to the experimental ones, though always underestimating the roughness value. This difference emerges because the model, as it does not incorporate the build up around the craters that might appear on the surface.

Optimizing CAD Models with Latent Space Manipulation

When it comes to the optimization of CAD models in the automation domain, neural networks currently play only a minor role. Optimizing abstract features such as automation capability is challenging, since they can be very difficult to simulate, are too complex for rule-based systems, and also have little to no data available for machine-learning methods. On the other hand, image manipulation methods that can manipulate abstract features in images such as StyleCLIP have seen much success. They rely on the latent space of pretrained generative adversarial networks, and could therefore also make use of the vast amount of unlabeled CAD data. In this paper, we show that such an approach is also suitable for optimizing abstract automation-related features of CAD parts. We achieved this by extending StyleCLIP to work with CAD models in the form of voxel models, which includes using a 3D StyleGAN and a custom classifier. Finally, we demonstrate the ability of our system for the optimiziation of automation-related features by optimizing the grabability of various CAD models.

Comprehensive Analysis of Wireless Capsule Endoscopy Radio Channel Characteristics Using Anatomically Realistic Gastrointestinal Simulation Model

This paper presents a comprehensive study of radio channels related to capsule endoscopy communications in ultra wideband wireless body area networks (UWB-WBAN) utilizing multiple antenna systems. The research includes 363 channel realizations, obtained through simulations using an anatomically realistic voxel model and a capsule model. A capsule position is modelled in such a way that it moves throughout the entire intestinal tract. The study examines the frequency and time domain characteristics of the channels in various capsule locations, including the most challenging positions deep inside the tissues or far away from most of the antennas. Additionally, the propagation characteristics inside the abdominal tissue are studied by calculating the most obvious propagation paths based on power flow illustrations and reflecting the results with the channel impulse response analysis. The impact of capsule rotation is also studied. It is shown how small changes in capsule location can greatly impact on the channel characteristics if the thickness of the tissues between the capsule and the on-body antenna changes significantly. The paper concludes with statistical analysis of the channel data, including path loss and root mean square (RMS) delay spread. The results provide valuable insight into how the signal propagates inside different parts of the gastrointestinal tract. They show that channel attenuation remains moderate along most of the gastrointestinal tract, and that even the deepest locations in the small intestine area can be resolved with the use of directional on-body antennas and receivers with higher sensitivity.

Comparison between MCNP and planning system in brachytherapy of cervical cancer

Absorbed doses in uterus during brachytherapy were calculated with MCNP in relevant points and compared with planning system for one patients. MCNP was applied with two different humanoid phantoms in input, ORNL and voxel models, which represent human body in mathematical way. Good agreement between both phantoms, as well as, between MCNP and planning system were found.In addition the doses in critical organs (bladder and colon in this kind of therapy), were calculated and compared with maximal doses in these organs obtained from planning system for 15 other patients. MCNP doses agree well with planning system in points of uterus for those 15 patients, where radioactive source is used to apply. However, there are systematical discrepancies between doses in colon and bladder obtained by MCNP and planning system.

Human Posture Classification Using Interpretable 3-D Fuzzy Body Voxel Features and Hierarchical Fuzzy Classifiers

This article proposes a human posture classification system to classify the four postures of standing, bending, sitting, and lying using three-dimensional (3-D) fuzzy body voxel features obtained from two cameras and hierarchical fuzzy classifiers (FCs). The system consists of four parts: human body segmentation, 3-D body voxel model construction, feature extraction, and classification. A region-dependent Gaussian mixture model with shadow removal is proposed for human body segmentation. The silhouette volume intersection method with computation speedup is then used to construct the 3-D body model using the segmented images from two cameras. After that, fuzzy 3-D body voxel features for posture classification are extracted from a minimum enclosed cube of the 3-D model. For classification, this article proposes an FC with soft margin minimization (FC-SMM) and its hierarchical structure to improve the classification performance. The consequent and antecedent parameters are optimized through a linear batch support vector machine and margin selective gradient descent algorithm, respectively. The FC-SMM also shows the advantage of model interpretability through visualization of the fuzzy rules. Experimental results of the comparison of different feature extraction methods and classifiers in different videos show the superiority of the proposed classification method.

Stationary Stokes solver for single-phase flow in porous media: A blastingly fast solution based on Algebraic Multigrid Method using GPU

The paper is focused on high efficiency Stokes solver that is applied to the incompressible flow in porous media. Computational domains are represented by binarized 3D computed tomography voxel models. The solution procedure is constructed around a fast algebraic multigrid solver that utilizes the power of graphics processing units (GPUs). In order to minimize memory footprint and accelerate the solver, a simple MAC-type staggered finite difference discretization is used and a coupled Stokes saddle-point type system is solved directly on a GPU. The MAC discretization is discussed, taking particular care of internal solid boundaries around pores. The method includes topological domain analysis on a GPU, which removes isolated volumes with no flow in the domain (based on the connected component labeling), depending on the boundary conditions. We consider various types of boundary conditions and efficient parallel strategies for the GPUs, including fast matrix assembly and residual regularization. Our method is extensively benchmarked both against analytical solutions and applied problems from digital rock physics in terms of computational wall time, precision, approximation order, and convergence. We demonstrate that it takes up to 5–23 s on a modern GPU card to obtain a solution with 1⋅10−6 error residuals for 3D geometries with 300–4503 voxels and a porosity range of 5–37%.

Quadrature transceive wireless coil: Design concept and application for bilateral breast MRI at 1.5 T.

Development of a novel quadrature inductively driven transceive wireless coil for breast MRI at 1.5 T. A quadrature wireless coil (HHMM-coil) design has been developed as a combination of two linearly polarized coils: a pair of 'metasolenoid' coils (MM-coil) and a pair of Helmholtz-type coils (HH-coil). The MM-coil consisted of an array of split-loop resonators. The HH-coil design included two electrically connected flat spirals. All the wireless coils were coupled to a whole-body birdcage coil. The HHMM-coil was studied and compared to the linear coils in terms of transmit and SAR efficiencies via numerical simulations. A prototype of HHMM-coil was built and tested on a 1.5 T scanner in a phantom and healthy volunteer. We also proposed an extended design of the HHMM-coil and compared its performance to a dedicated breast array. Numerical simulations of the HHMM-coil with a female voxel model have shown more than a 2.5-fold increase in transmit efficiency and a 1.7-fold enhancement of SAR efficiency compared to the linearly polarized coils. Phantom and in vivo imaging showed good agreement with the numerical simulations. Moreover, the HHMM-coil provided good image quality, visualizing all areas of interest similar to a multichannel breast array with a 32% reduction in signal-to-noise ratio. The proposed quadrature HHMM-coil allows the -field to be significantly better focused in the region-of-interest compared to the linearly polarized coils. Thus, the HHMM-coil provides high-quality breast imaging on a 1.5 T scanner using a whole-body birdcage coil for transmit and receive.

Solid Modelling for Manufacturing: From Voelcker’s Boundary Evaluation to Discrete Paradigms

Herb Voelcker and his research team laid the foundations of Solid Modelling, on which Computer-Aided Design is based. He founded the ambitious Production Automation Project, that included Constructive Solid Geometry (CSG) as the basic 3D geometric representation. CSG trees were compact and robust, saving a memory space that was scarce in those times. But the main computational problem was Boundary Evaluation: the process of converting CSG trees to Boundary Representations (BReps) with explicit faces, edges and vertices for manufacturing and visualization purposes. This paper presents some glimpses of the history and evolution of some ideas that started with Herb Voelcker. We briefly describe the path from “localization and boundary evaluation” to “localization and printing”, with many intermediate steps driven by hardware, software and new mathematical tools: voxel and volume representations, triangle meshes, and many others, observing also that in some applications, voxel models no longer require Boundary Evaluation. In this last case, we consider the current research challenges and discuss several avenues for further research. • History and evolution from boundary evaluation to boundary printing. • From continuous surface reconstruction to discrete paradigms. • Boundary evaluation on discrete models. • Boundaries in manufacturing.

Design of 3D and 4D printed continuous fibre composites via an evolutionary algorithm and voxel-based Finite Elements: Application to natural fibre hygromorphs

This paper describes a novel voxel-based technique to accurately model 3D printed continuous yarns of fibre composites at printed filament scale. To cater for the constraints of continuous filament printing, the design strategy here makes use of a set of variables that fully define the printing path as input in the model. A voxel-based algorithm is developed to obtain the local orientations of the filaments and local quantities of yarns and matrix from a pixelated flat layout of the printed composite. This voxel-based representation is then translated into a Finite Element model to obtain the required structural properties. This approach simplifies and potentially shortens the design of the part, compared to other analytical techniques. The design space of the part is defined by the variables of the gcode used to print the composite. The voxel model is coupled with an evolutionary algorithm to explore the part of the design space related to the use of continuous yarns. The hygro expansion of the material was measured to determine the coefficients of moisture expansion serving as input in the model. Promising results are obtained from a test case related to a continuous flax fibres-reinforced polylactic acid (PLA) printed structure, mimicking the shape of a leaf. The proposed modelling strategy has the potential to characterise geometric, material, mechanical and actuation properties of general 3D printed structures with negligible out-of-plane (i.e., through thickness) printing. • FEA voxel-based strategy can be used to model continuous fibre 3D printed composite. • Leaf shaped hygromorph printed with continuous flax fibre polylactic acid composite. • 4D printed continuous fibre hygromorphs can be designed via evolutionary algorithm.