3D Engine Research Articles

WebMRI: Brain extraction and linear registration in the web browser

AbstractBackground and AimSince the initial release of the World Wide Web, the capabilities of web browsers have grown from presenting formatted documents to running complex programs, such as 3D game engines. The medical imaging community started to adopt technologies that came with the fifth major version of the HyperText Markup Language (HTML5). It led to the creation of various web-based radiological applications such as cornerstone.js or BrainBrowser. BrainBrowser supports both 3D and 2D rendering of neuroimaging data. However, it cannot run important image processing algorithms, such as brain extraction and linear registration, which are essential in most neuroimaging workflows. The most commonly used library that supports these algorithms is the FMRIB Software Library (FSL). We aim to build a web-based cross-platform neuroimaging platform that combines data visualization with image processing.MethodsWe built our system as an extension of BrainBrowser. We developed WebMRI in JavaScript and designed the user interface using HTML, CSS, and Bootstrap. We used Emscripten to port the brain extraction and linear registration tools of FSL to the web.ResultsWe built WebMRI, a fully web-based extensible neuroimaging platform that combines the visualization capabilities of BrainBrowser with the brain extraction and linear registration tools of FSL by porting them from C++ to WebAssembly. We extended BrainBrowser with a plugin system that makes it easy to bring other processing algorithms into the platform. We released the WebMRI source code on Github: https://github.com/wpmed92/WebMRI.ConclusionsWe developed and released WebMRI, a web-based cross-platform open-source neuroimaging platform.

Cryopreservation of 3D Bioprinted Scaffolds with Temperature-Controlled-Cryoprinting.

Temperature-Controlled-Cryoprinting (TCC) is a new 3D bioprinting technology that allows for the fabrication and cryopreservation of complex and large cell-laden scaffolds. During TCC, bioink is deposited on a freezing plate that descends further into a cooling bath, keeping the temperature at the nozzle constant. To demonstrate the effectiveness of TCC, we used it to fabricate and cryopreserve cell-laden 3D alginate-based scaffolds with high cell viability and no size limitations. Our results show that Vero cells in a 3D TCC bioprinted scaffold can survive cryopreservation with a viability of 71%, and cell viability does not decrease as higher layers are printed. In contrast, previous methods had either low cell viability or decreasing efficacy for tall or thick scaffolds. We used an optimal temperature profile for freezing during 3D printing using the two-step interrupted cryopreservation method and evaluated drops in cell viability during the various stages of TCC. Our findings suggest that TCC has significant potential for advancing 3D cell culture and tissue engineering.

Real Driving Cycle Simulation of a Hybrid Bus by Means of a Co-Simulation Tool for the Prediction of Performance and Emissions

This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity.

Designing an Android-Based Educational Game for Fruit Recognition in Seruni Pertiwi Preschool

The objective of this research is to design and develop an Android-based educational game for fruit recognition in Seruni Pertiwi Preschool. The educational game application consists of a main menu, fruit menu, and tree menu. The fruit menu includes various fruit options such as bananas, papayas, apples, grapes, oranges, pineapples, watermelons, durians, rambutans, and strawberries. The research methodology employed in this thesis includes data and information collection, system design, software requirement analysis, interface design, coding, testing, and implementation. The Unity 3D engine is utilized for designing the educational game application. Based on the conducted testing, the following conclusions can be drawn: the developed educational game is free from errors based on the black-box testing results. The research findings indicate that the average validation score from user feedback, ranging from user 1 to user 10, is 4.6, which indicates a high level of agreement with the system assessment, falling under the category of "strongly agree".

Morphology and Morphometry of Aortic Valve in Humans and Porcines – A Comparative Study

Background: The aortic valve is a semilunar valve with three leaflets that are in the left ventricle’s outflow tract and only permits unidirectional blood flow away from the ventricle. The valve leaflet can tolerate extremely high mechanical and hemodynamic forces resulting from the great complexity and complicated cellular and molecular functions. Aims: The aim of the study is to provide an add-on to the understanding of the morphological and morphometrical aspects of human and porcine aortic heart valves on comparative grounds so that they can be used as a guide in the construction of three-dimensional (3D)-printed mechanical valve. Materials and Methods: Twenty swine and twenty human hearts were compared and examined in this investigation. The porcine and human hearts weighing in between 300 g and 450 g were considered, and any variation from the normal and any mechanical damage rendered during procurement were all excluded from the study. Results: The length of the attached margin of the right coronary cusp, left coronary cusp, and noncoronary cusp of human and porcine were 45.15 mm, 36.47 mm, and 41.53 mm and 36.55 mm, 43.14 mm, and 36.10 mm, respectively. The length of the free margin and the height of the cusps from nadir to the sinotubular junction and the effective height of the cusp from nadir to the free margin of the cusps of human and porcine have been compared. Conclusion: The human and swine aortic valves share morphological and morphometrical characteristics, which can be used to create 3D valves and tissue engineering procedures with greater biocompatibility and biofunctionality.

Clinical Trials with Mesenchymal Stem Cell Therapies for Osteoarthritis: Challenges in the Regeneration of Articular Cartilage.

Osteoarthritis (OA) is a whole-joint disease primarily characterized by the deterioration of hyaline cartilage. Current treatments include microfracture and chondrocyte implantation as early surgical strategies that can be combined with scaffolds to repair osteochondral lesions; however, intra-articular (IA) injections or implantations of mesenchymal stem cells (MSCs) are new approaches that have presented encouraging therapeutic results in animal models and humans. We critically reviewed clinical trials with MSC therapies for OA, focusing on their effectiveness, quality, and outcomes in the regeneration of articular cartilage. Several sources of autologous or allogeneic MSCs were used in the clinical trials. Minor adverse events were generally reported, indicating that IA applications of MSCs are potentially safe. The evaluation of articular cartilage regeneration in human clinical trials is challenging, particularly in the inflammatory environment of osteoarthritic joints. Our findings indicate that IA injections of MSCs are efficacious in the treatment of OA and the regeneration of cartilage, but that they may be insufficient for the full repair of articular cartilage defects. The possible interference of clinical and quality variables in the outcomes suggests that robust clinical trials are still necessary for generating reliable evidence with which to support these treatments. We suggest that the administration of just-sufficient doses of viable cells in appropriate regimens is critical to achieve effective and durable effects. In terms of future perspectives, genetic modification, complex products with extracellular vesicles derived from MSCs, cell encapsulation in hydrogels, and 3D bioprinted tissue engineering are promising approaches with which to improve MSC therapies for OA.

A novel optical coherence tomography-based in vitro method of anti-aging skin analysis using 3D skin wrinkle mimics.

Wrinkles represent a characteristic symptom of skin aging. In recent years, various studies have focused on their prevention and/or cure. However, clinical tests are still the only method available to directly detect and evaluate the anti-wrinkle efficacy of various substances. Moreover, no in vitro strategy for such anti-aging skin analysis has been reported. Therefore, in this study, we aimed to develop a novel technology to overcome these limitations. Full-thickness (FT) skin wrinkle mimics with various widths and depths were fabricated using a collagen stamping method. These were analyzed and compared using 2D and 3D Swept Source-Optical Coherence Tomography (SS-OCT) imaging technologies. SS-OCT demonstrated superficial and cross-sectional images of the wrinkle mimics, and the size of the wrinkles was validated using image analysis. Retinoic acid treatment significantly decreased both the depth and width of wrinkles formed in the FT skin wrinkle mimics. Using 3D tissue engineering and SS-OCT imaging technologies, we developed a novel in vitro technique that can directly detect skin wrinkles. This significantly efficient method could lead to an alternative strategy for animal experiments and preclinical anti-aging research on the skin.

3D bioprinting strategy for engineering vascularized tissue models.

Leveraging three-dimensional (3D) bioprinting in the fields of tissue engineering and regenerative medicine has rapidly accelerated progress toward the development of living tissue constructs and biomedical devices. Ongoing vigorous research has pursued the development of 3D in vitro tissue models to replicate the key aspects of human physiology by incorporating relevant cell populations and adequate environmental cues. Given their advantages of being able to intimately mimic the heterogeneity and complexity of their native counterparts, 3D in vitro models hold promise as alternatives to conventional cell cultures or animal models for translational application to model human physiology/pathology and drug screening. Research has highlighted the importance of in vitro models, and a sophisticated biomanufacturing strategy is vitally required. In particular, vascularization is critical for the prolonged survival and functional maturation of the engineered tissues, which has remained one of the major challenges in the establishment of physiologically relevant 3D in vitro models. To this end, 3D bioprinting can efficiently generate solid and reproducible vascularized tissue models with high architectural and compositional similarity to the native tissues, leading to improve the structural maturation and tissue-specific functionality. Multiple bioprinting strategies have been developed to vascularize in vitro tissues by spatially controlled patterning of vascular precursors or generating readily perfusable vascular structures. This review presents an overview of the advanced 3D bioprinting strategies for vascularized tissue model development. We present the key elements for rebuilding functional vasculature in 3D-bioprinted tissue models and discuss the recent achievements in the engineering of 3D vascularized in vitro models using 3D bioprinting. Finally, we delineate the current challenges and future outlooks of 3D bioprinting-based vascularized tissue models.

Naturally Derived Maleic Chitosan/Thiolated Sodium Hyaluronate Hydrogels as Potential 3D Printing Tissue Engineering Materials

Abstract3D printing is an attractive method to accurately construct artificial organs or alternative materials with complicated structures and functional performance. Naturally derived hydrogels have emerged as promising materials for the preparation of biomimetic 3D organization or scaffolds by 3D printing due to their good biocompatibility, high water content, and fascinating 3D network. However, the poor printing properties and weak structural stability of naturally derived hydrogels limit their applications. In this study, photopolymerizable hydrogels are designed based on maleic chitosan (MCS) and thiolated sodium hyaluronate (SHHA). The Michael addition between MCS and SHHA improves the viscosity of the mixed solution. Moreover, it benefits the 3D printing process, followed by photopolymerization (acrylate‐thiol step‐chain polymerization and acrylate–acrylate chain polymerization) to form a stable covalent network rapidly. The rheological property, swelling behaviors, microstructure, and in vitro degradation are tuned by adjusting the molar ratio of the thiol group and acrylate group. In addition, MCS/SHHA hydrogel scaffolds with good accuracy and enhanced structural stability are prepared using extrusion‐based 3D printing and photopolymerization technology. The hydrogels display excellent cytocompatibility and can support adherence of L929 cells, which can be used as prospective materials for tissue engineering applications.

Projector-based augmented stacking framework for irregularly shaped objects

Augmented reality in additive fabrication is predominantly applied to the manufacturing of structures from regularly shaped materials. Our work however embraces natural heterogeneity, by focusing on the assembly of irregularly shaped elements such as mineral scraps. We introduce a computer-aided framework with a 3D stacking engine and an augmented reality interface capable of guiding users through the balanced positioning of discrete and highly nonuniform objects according to an on-the-fly computed model and without prior trimming of the building unit. The pipeline is tested by the construction of two dry-stone structures (i.e., lacking any adhesives), and its accuracy is validated with a comparative study between the point cloud of the as-built digitized artifacts and the generated execution model, which shows an average 2.9 ± 1.8 cm error between the stones of the two models. We finally show how the proposed framework could be improved both in terms of software and hardware. In the interests of reproducibility, all the methods are shared as open source with the community.Graphical abstract

PD-0906 Preventing potential treatment collisions on a TrueBeam system using a 3D video game engine

PD-0906 Preventing potential treatment collisions on a TrueBeam system using a 3D video game engine

독도 투어

Dokdo Tour is an augmented reality tour system developed using the Dokdo diorama. When the camera is pointed at the Dokdo diorama, virtual objects such as birds and ships are augmented, and the sounds of waves and seagulls are combined to create a sense of presence. Users can move their bodies to explore different parts of Dokdo, and interact with specific elements of the island, such as rocks and structures, to deepen their understanding of the island while hearing explanations of the elements they want to see. DokdoTour was developed using CoSpaces as the main development environment and MageCube for augmented reality implementation. In the future, if the DokdoTour is developed with 3D game engines such as Unity3D and Unreal by professional developers, it is expected to become a service with sufficient commercial value for education and non-face-to-face tourism. The system is also highly scalable, as it can be applied not only to Dokdo but also to various industries that can be made into dioramas. Although it was developed with CoSpaces, an educational platform, the DokdoTour is expected to be a prototype and a good reference for implementing an augmented reality system using dioramas in the future, including the process of directly generating voices for elements using artificial intelligence voice generation services and the process of implementing reality blending for realistic augmentation by scanning dioramas in three dimensions.

A Front Advancing Adaptive Triangular Mesh Dynamic Generation Algorithm and Its Application in 3D Geological Modeling

The traditional advancing front technique algorithm encounters many problems due to the complex geometric characteristics of the front edge shape. These problems include poor quality, a slow algorithm, low robustness, and the inability of the mesh unit to converge. To address these problems, an optimized adaptive triangular mesh dynamic generation algorithm called R-TIN is proposed and applied to 3D engineering geological modeling in this study. Firstly, all the shapes involved in advancing the front edge inward were classified into four types, and then the optimal triangular unit was constructed by using the candidate mesh point heuristic algorithm. Then, the robustness of this algorithm could be maintained by the graded concession of the included angle threshold in the adjacent front-line segments. Finally, based on 160 engineering geological boreholes in the study area, the 3D engineering geological model was constructed and the accuracy and visualization effect of the overall geological model have been greatly improved, which can better present the spatial distribution of strata and lithological characteristics. At the same time, this algorithm can be used in geoscience information services to support the regional or national exploration of resources and energy, sustainable development and utilization, environmental protection and the prevention of geological disasters.

Strategy for ship energy efficiency based on optimization model and data-driven approach

This paper proposes an innovative approach to evaluate and enhance the ship's energy efficiency using a machine learning (ML) technique. A methodology is proposed combining an engine optimization model and a data-driven approach to monitor and predict the performance of the ship along the route. The starting point is a dataset of noon report data covering significant operational information corresponding to the main engine. Then, an engine model is developed, calibrated and validated in a 1D engine simulation software to compute the engine performance for different speeds and loads. After the simulation process is performed, operational parameters are derived from the developed engine model such as volumetric efficiency, scavenging ratio, brake mean effective pressure, and brake power according to the noon report of the ship. Lastly, a data-driven adaptive neuro-fuzzy inference system (ANFIS) model is developed to estimate brake power as a main parameter affecting fuel consumption. Various ANFIS configurations are created and evaluated by error metrics to determine the best structure of the ML model. The proposed strategy provides an effective approach to maritime companies for monitoring, controlling, and improving ships' energy efficiency status based on the noon report data that is already collected onboard.

Biosensors integrated 3D organoid/organ-on-a-chip system: A real-time biomechanical, biophysical, and biochemical monitoring and characterization

As a full-fidelity simulation of human cells, tissues, organs, and even systems at the microscopic scale, Organ-on-a-Chip (OOC) has significant ethical advantages and development potential compared to animal experiments. The need for the design of new drug high-throughput screening platforms and the mechanistic study of human tissues/organs under pathological conditions, the evolving advances in 3D cell biology and engineering, etc., have promoted the updating of technologies in this field, such as the iteration of chip materials and 3D printing, which in turn facilitate the connection of complex multi-organs-on-chips for simulation and the further development of technology-composite new drug high-throughput screening platforms. As the most critical part of organ-on-a-chip design and practical application, verifying the success of organ model modeling, i.e., evaluating various biochemical and physical parameters in OOC devices, is crucial. Therefore, this paper provides a logical and comprehensive review and discussion of the advances in organ-on-a-chip detection and evaluation technologies from a broad perspective, covering the directions of tissue engineering scaffolds, microenvironment, single/multi-organ function, and stimulus-based evaluation, and provides a more comprehensive review of the progress in the significant organ-on-a-chip research areas in the physiological state.

Novel Airflow-Field-Driven Melt Spinning 3D Printing of Tubular Scaffolds Based on Polycaprolactone Blends

The fabrication of various 3D tissue engineering tubular scaffolds with fibrous structures, to assist the human body in rapidly repairing a variety of ailments, is receiving more and more attention. Due to the inefficiency of the majority of fibrous preparation techniques, the question of how to rapidly produce the requisite three-dimensional tubular microfiber scaffold structures has become an urgent problem. In this study, an efficient polymer fiber preparation method was developed, using a high-speed airflow drive. Melt blending of polycaprolactone (PCL), polylactic acid (PLA), and tributyl citrate (TBC), was used for the printing material, to achieve the efficient preparation of tubular microfiber scaffolds with different structures. The scaffold diameter was as small as 2 mm, the wall thickness was up to 100 μm, and the fiber injection efficiency reached 15.48 g/h. By utilizing simulations to optimize the printing parameters and by adjusting the printing settings, it was possible to achieve a controlled fiber diameter in the range of 3 μm to 15 μm. In addition, plasma treatment was applied to the microfibers' surface, to increase their wettability, and the efficiency of the hydrophilic modification was demonstrated. Furthermore, the mechanical property test demonstrated that the fibers have a tensile strength of 1.36 ± 0.16 MPa and a tensile strain of 30.8 ± 3.5%. The radial compressive strain of the tubular scaffold could reach 60% of the original scaffold's diameter. Finally, the in vitro degradation of the fibers at various pH values was tested. The results showed that, under alkaline conditions, the surface of the fibers would be severely crushed and the rate of deterioration would increase.

In-Cylinder Heat Transfer Model Proposal Compatible with 1D Simulations in Uniflow Scavenged Engines

Advanced two-stroke engines are considered as powertrains for range extenders in hybrid electric vehicles due to size, simplicity, cost, and power density advantages. In-cylinder heat transfer is a phenomenon that affects the temperature of burnt gases and fresh air in an internal combustion engine. Compared to four-stroke units, this influence is more critical in two-stroke engines during the scavenging process since the gases velocity field inside the cylinder evolves rapidly in space and time. This study proposes a new convective heat transfer coefficient model beyond those based on Reynolds number calculation with the mean piston velocity. The model uses semi-empirical equations with non-dimensional numbers since it has to be integrated within the frame of a physical engine model, where thermo- and fluid dynamic properties of the gases inside the engine are solved using 0D or 1D approaches. In this particular application, the temperature deviation led to a poor prediction of trapped mass in the cylinder. The proposed convective heat transfer coefficient is calculated using a pseudo-velocity of the gases inside the cylinder based on the mass flow rates in the intake and exhaust ports during scavenging. The experimental results validate the 1D engine physical model, which is then used as initial conditions for CFD simulations. These CFD results are used to deduce the necessary conclusions for enhanced temperature predictability during scavenging, where deviations of less than 2% can be observed and an impact of up to 12% on the in-cylinder trapped mass can be seen.

New Coupled Canopy–Light Model (CCLM) to Improve Visual Polymorphism Simulation of Fir Morphology

Environmental factors substantially influence the growth of trees. The current studies on tree growth simulation have mainly focused on the effect of environmental factors on diameter at breast height and tree height. However, the influence of environmental factors, especially light, on canopy morphology has not been considered, hindering the accurate understanding of the range of characteristics of tree morphology that occur due to environmental changes. To solve this problem, this study investigated the influence of light on the changes in canopy morphology and constructed a coupled canopy–light model (CCLM) to visually simulate the polymorphism of fir morphology. Using the Huangfengqiao Forestry Farm in You County, Hunan Province, China, as the study area, we selected a typical sample plot. Field surveys of the fir trees in the sample plot were conducted for three consecutive years to obtain longitudinal data of fir tree canopy shape. We constructed the canopy curves using a cubic uniform B-spline to construct 3D models of the fir trees in different years. The topographic and spatial location distribution data of the fir trees were used to construct a 3D scene of the sample plot in the UE4 3D engine, and the light distribution for each part of the canopy was calculated in a 3D scene by using the annual average photosynthetically active radiation (PAR) as the light parameter, which we combined with the ray-tracing algorithm. This study constructed the CCLM from the fir diameter using the breast-height growth model (BDGM) and the height–diameter curve model (HDCM), the fir trees’ canopy shape description from two years, and the light distribution data. We compared the canopy data obtained from canopy simulations using the CCLM with those obtained using a growth model based on spatial structure (GMBOSS) and those obtained from field surveys to identify any difference in the effectiveness of the canopy simulations using the CCLM and GMBOSS. Based on the BDGM and HDCM, we constructed the CCLM of firs with a determination coefficient (R2) of 0.829, combining data on canopy shape descriptions obtained from two years of field surveys and the light distribution data of each part of the canopy obtained through the ray-tracing algorithm. The Euclidean distance between the canopy description data obtained using the CCLM and the canopy description data obtained from the field survey was 15.561; that between the GMBOSS and the field survey was 23.944. A virtual forest stand environment was constructed from the survey data, combining ray-tracing algorithms to construct the CCLM model of fir in a virtual forest stand environment for growth visualization and simulation. Compared with the canopy description data obtained using the GMBOSS, the canopy description data obtained using the CCLM better fit the canopy description data obtained from the field survey, and the Euclidean distance decreased from 23.944 to 15.561.

Hybrid synthetic data generation pipeline that outperforms real data

Fine-tuning a pretrained model with real data for a machine learning task requires many hours of manual work, especially for computer vision tasks, where collection and annotation of data can be very time-consuming. We present a framework and methodology for synthetic data collection that is not only efficient in terms of time taken to collect and annotate data, making use of free- and open-source software tools and 3D assets but also beats the state-of-the-art against real data, which is the ultimate test for any similar-to-real approach. We test our approach on a set of image classes from ObjectNet, which is a challenging image classification benchmark test dataset that is designed to be similar in many respects to ImageNet but with a wider variety of viewpoints, rotations, and backgrounds, which can make it more difficult for transfer learning problems. The novelty of our approach stems from the way we create complex backgrounds for 3D models using 2D images laid out as decals in a 3D game engine, where synthetic images are captured programmatically with a large number of systematic variations. We demonstrate that our approach is highly effective, resulting in a deep learning model with a top-1 accuracy of 72% on the ObjectNet data, which is a new state-of-the-art result. In addition, we present an efficient strategy for learning rate tuning that is an order of magnitude faster than regular grid search.

Development of Virtual Reality Walking Collision Detection Test on Head-mounted display.

Detecting and avoiding collisions during walking is critical for safe mobility. To determine the effectiveness of clinical interventions, a realistic objective outcome measure is needed. A real-world obstacle course with moving hazards has numerous limitations (e.g., safety concerns of physical collision, inability to control events, maintaining event consistency, and event randomization). Virtual reality (VR) platforms may overcome such limitations. We developed a VR walking collision detection test using a standalone head-mounted display (HMD, Meta Quest 2) with the Unity 3D engine to enable subjects' physical walking within a VR environment (i.e., a busy shopping mall). The performance measures focus on the detection and avoidance of potential collisions, where a pedestrian may (or may not) walks toward a collision with the subject, while various non-colliding pedestrians are presented simultaneously. The physical space required for the system was minimized. During the development, we addressed expected and unexpected hurdles, such as mismatch of visual perception of VR space, limited field of view (FOV) afforded by the HMD, design of pedestrian paths, design of the subject task, handling of subject's response (detection or avoidance behavior), use of mixed reality (MR) for walking path calibration. We report the initial implementation of the HMD VR walking collision detection and avoidance scenarios that showed promising potential as clinical outcome measures.