Search Results (170)

Landscape visualization plays a crucial role in various scientific and artistic fields, including geography, environmental sciences, and digital arts. Recent advancements in computer graphics have enabled more sophisticated approaches to landscape representation. The integration of artificial intelligence (AI) image generation has further improved accessibility for researchers, allowing efficient creation of landscape visualizations. This study presents a comprehensive workflow for the rapid and cost-effective generation of photorealistic still images. The methodology combines AI applications, computational techniques, and photographic methods to reconstruct the historical landscapes of the Great Hungarian Plain, one of Europe’s most significantly altered regions. The most accurate and visually compelling results are achieved by using historical maps and drone imagery as compositional and stylistic references, alongside a suite of AI tools tailored to specific tasks. These high-quality landscape visualizations offer significant potential for scientific research and public communication, providing both aesthetic and informative value. The article, which primarily presents a methodological description, does not contain numerical results. To test the method, we applied a procedure: we ran the algorithm on a current topographic map of a sample area and compared the resulting image with the view model provided by Google Earth. Full article

Augmented reality (AR) has become a research focus in computer vision and graphics, with growing applications driven by advances in artificial intelligence and the emergence of the metaverse. Panoramic cameras offer new opportunities for AR due to their wide field of view but also pose significant challenges for camera pose estimation because of severe distortion and complex scene textures. To address these issues, this paper proposes a lightweight, unsupervised deep learning model for panoramic camera pose estimation. The model consists of a depth estimation sub-network and a pose estimation sub-network, both optimized for efficiency using network compression, multi-scale rectangular convolutions, and dilated convolutions. A learnable occlusion mask is incorporated into the pose network to mitigate errors caused by complex relative motion. Furthermore, a panoramic view reconstruction model is constructed to obtain effective supervisory signals from the predicted depth, pose information, and corresponding panoramic images and is trained using a designed spherical photometric consistency loss. The experimental results demonstrate that the proposed method achieves competitive accuracy while maintaining high computational efficiency, making it well-suited for real-time AR applications with panoramic input. Full article

Preoperative facial markings are critical to surgical precision and aesthetic outcomes in plastic surgery, yet remain operator-dependent and variably documented. Generative artificial intelligence (AI), particularly large multimodal models, offers potential for the automated illustration of surgical plans. This study compares the performances of ChatGPT-4o and Gemini Advanced in generating standardised preoperative markings for aesthetic facial procedures. Methods: Six text prompts describing common facial aesthetic surgeries were developed using established marking protocols. Each prompt was submitted once to ChatGPT-4o and Gemini Advanced, yielding twelve illustrations. Three board-certified plastic surgeons independently evaluated the images using a five-domain Likert scale assessing incision clarity, anatomical accuracy, template conformity, clinical usefulness, and overall graphic quality. A composite score out of 25 was calculated. Data were analysed using paired t-tests, and interrater reliability was assessed with intraclass correlation coefficients. Results: ChatGPT-4o significantly outperformed Gemini Advanced in composite scores (mean 18.0 ± 1.4 vs. 13.9 ± 1.6, p = 0.001, Cohen’s d = 1.69). Superior performance was noted across all domains, particularly in clarity (mean difference 0.83, p = 0.002) and graphic quality (mean difference 0.90, p = 0.001). Interrater reliability was good (ICC = 0.82). Discussion: ChatGPT-4o demonstrated higher fidelity in translating surgical prompts into anatomically appropriate, clinically useful illustrations. However, neither system achieved the precision required for clinical implementation without revision. These models may serve as adjuncts in education and preliminary planning. Future work should explore model fine-tuning, surgeon-guided generation, and performance in reconstructive procedures. Full article

Generative neural networks have expanded from text and image generation to creating realistic 3D graphics, which are critical for immersive virtual environments. Physically Based Rendering (PBR)—crucial for realistic 3D graphics—depends on PBR maps, environment (env) maps for lighting, and camera viewpoints. Current research mainly generates PBR maps separately, often using fixed env maps and camera poses. This limitation reduces visual consistency and immersion in 3D spaces. Addressing this, we propose EnvMat, a diffusion-based model that simultaneously generates PBR and env maps. EnvMat uses two Variational Autoencoders (VAEs) for map reconstruction and a Latent Diffusion UNet. Experimental results show that EnvMat surpasses the existing methods in preserving visual accuracy, as validated through metrics like L-PIPS, MS-SSIM, and CIEDE2000. Full article

Near the 11–12 locks of the Canal de Castilla, there once stood a paper mill built in the 18th century and dismantled in 1983. Despite the scarce physical remains, the absence of original plans, and the limited availability of data, this research aims to reconstruct its initial layout, characteristics, and operation. To achieve this, an analytical–synthetic method has been followed: in the analysis phase, multiple sources and materials are thoroughly examined from various perspectives, while in the synthesis phase, drawing is employed as a means of reflection, since any hypothesis about this factory must be validated through sufficiently precise graphical representations. The most relevant result is the complete drafting of the factory’s plans, including its machinery, as well as the clarification of its production system. The main conclusion suggests that, although based on the mechanisms and equipment of traditional paper mills, this manufacturing facility sought to be innovative and exemplary in its time. Its dispersed typology was designed to improve and dignify working conditions for employees, while its internal organization optimized the paper production process and increased manufacturing capacity. Full article

Three-Dimensional Gaussian Splatting (3DGS), an important advancement in the field of computer graphics and 3D vision, has emerged to greatly accelerate the rendering process in novel views’ synthesis. Due to its ability to directly realize the real-time estimation of 3D shapes without neural networks, 3DGS has received a lot of attention in the fields of robotics, urban mapping, autonomous navigation, and virtual reality/augmented reality. In view of the growing popularity of 3DGS, we conduct a systematic review of the relevant literature. We begin by surveying existing work on 3D reconstruction and rendering, outlining the historical development and recent advances from both foundational and innovation-driven perspectives. Next, we summarize the most commonly used datasets and evaluation metrics in 3D reconstruction and rendering. Finally, we summarize the current challenges and suggest potential directions for future research. Through this survey, we aim to provide researchers with a treasure trove of resources in understanding and using techniques related to 3D reconstruction and rendering, in order to promote technological development and application deepening in the field of 3D vision. Full article

Objectives: To predict the survival rates of Osimertinib as first- and second-line therapy using time-to-event models based on literature data. Methods: Kaplan–Meier curves from randomized clinical trials were extracted after a systematic search of PubMed and Cochrane Library from their inception to 10 May 2023. Randomized clinical trials of Osimertinib reporting both first- and second-line overall survival (OS) and progression-free survival (PFS) in NSCLC patients with specific mutations, compared to earlier epidermal growth factor receptor (EGFR) inhibitors and chemotherapy. Kaplan–Meier curves of OS and PFS were extracted from published articles. A two-column raw dataset (time, survival probability) was extracted, and time-to-event outcomes (time, event) were derived using a graphic reconstructive algorithm. Data analysis was conducted from 1 June 2023 to 31 January 2024. Primary outcomes included OS and PFS for time-to-event modeling of Osimertinib as first- and second-line therapy. Results: The Weibull model, incorporating race as a covariate, best fit the first-line OS data. The log-logistic model best fit first-line PFS and second-line OS/PFS data. Based on these models, the predicted median OS for first-line and second-line treatment were 36.35 months (95% CI, 33.53–39.30 months) and 27.46 months (95% CI, 25.30–29.99 months), respectively. The predicted median PFS were 18.11 months (95% CI, 16.37–19.90 months) and 10.35 months (95% CI, 9.31–11.44 months), respectively. The predicted 3- and 5-year survival rates with first-line Osimertinib were 51% and 23%, respectively. Subgroup analysis revealed longer estimated 3- and 5-year survival rates for non-Asian patients compared to Asian patients (60% vs. 49% and 29% vs. 21%, respectively). Conclusions: The predicted survival rates from the time-to-event modeling align with the original clinical trial results, and an ethnic difference in Osimertinib efficacy was observed. Full article

Motion correction in magnetic resonance imaging (MRI) has become increasingly complex due to the high computational demands of iterative reconstruction algorithms and the heterogeneity of emerging computing platforms. However, the clinical applicability of these methods requires fast processing to ensure rapid and accurate diagnostics. Graphics processing units (GPUs) have demonstrated substantial performance gains in various reconstruction tasks. In this work, we present a GPU implementation of the reconstruction kernel for the generalized reconstruction by inversion of coupled systems (GRICS), an iterative joint optimization approach that enables 3D high-resolution image reconstruction with motion correction. Three implementations were compared: (i) a C++ CPU version, (ii) a Matlab–GPU version (with minimal code modifications allowing data storage in GPU memory), and (iii) a native GPU version using CUDA. Six distinct datasets, including various motion types, were tested. The results showed that the Matlab–GPU approach achieved speedups ranging from 1.2× to 2.0× compared to the CPU implementation, whereas the native CUDA version attained speedups of 9.7× to 13.9×. Across all datasets, the normalized root mean square error (NRMSE) remained on the order of ${10}^{-6}$ to ${10}^{-4}$, indicating that the CUDA-accelerated method preserved image quality. Furthermore, a roofline analysis was conducted to quantify the kernel’s performance on one of the evaluated datasets. The kernel achieved 250 GFLOP/s, representing a 15.6× improvement over the performance of the Matlab–GPU version. These results confirm that GPU-based implementations of GRICS can drastically reduce reconstruction times while maintaining diagnostic fidelity, paving the way for more efficient clinical motion-compensated MRI workflows. Full article

This paper explores the application of a specialized end-to-end framework, crafted to study historical soundscapes, with a specific focus on 18th-century Naples. The framework combines historical research, natural language processing, architectural acoustics, and virtual acoustic modelling to achieve historically accurate and physically based soundscape reconstructions. Central to this study is the development of a Historically Informed Soundscape (HIS) map, which concentrates on the urban spaces of Largo di Palazzo and Via Toledo in Naples. Using virtual and audio-augmented reality, the HIS map provides 3D spatialized audio, offering an immersive experience of the acoustic environment of 18th-century Naples. This interdisciplinary approach not only contributes to the field of sound studies but also represents a significant methodological innovation in the analysis and interpretation of historical urban soundscapes. By incorporating historical maps as interactive graphical user interfaces, the project fosters a dynamic, multisensory engagement with the past, offering a valuable tool for scholars, educators, and the public to explore and understand historical sensory environments. Full article

Wind turbines’ volume and power generation capacity have increased worldwide. Consequently, their inspection, maintenance, and repair are garnering increasing attention. Structural defects are common in turbine blades, but their detection is difficult due to the relatively large size of the blades. Therefore, engineers often use nondestructive testing. This study employed an unmanned aerial vehicle (UAV) to simultaneously capture visible-light and infrared thermal images of wind power blades. Subsequently, instant neural graphic primitives and neural radiance fields were used to reconstruct the visible-light image in three dimensions (3D) and generate a 3D mesh model. Experiments determined that after converting parts of the orthographic-view images to elevation- and depression-angle images, the success rate of camera attitude calculation increased from 85.6% to 97.4%. For defect measurement, the system first filters out the perspective images that account for 6–12% of the thermal image foreground area, thereby excluding most perspective images that are difficult to analyze. Based on the thermal image data of wind power generation blades, the blade was considered to be in a normal state when the full range, average value, and standard deviation of the relative temperature grayscale value in the foreground area were within their normal ranges. Otherwise, it was classified as abnormal. A heat accumulation percentage map was established from the perspective image of the abnormal state, and defect detection was based on the occurrence of local minima. When a defect was observed in the thermal image, the previously reconstructed 3D image was switched to the corresponding viewing angle to confirm the actual location of the defect on the blade. Thus, the proposed 3D image reconstruction process and thermal image quality analysis method are effective for the long-term monitoring of wind turbine blade quality. Full article

This paper presents an engineering design-based investigation of a historical invention: a single-cylinder horizontal high-pressure steam engine with a Corliss valve gear designed by Arnold Throp. The research, grounded in engineering drawing, has enabled an understanding of the operation of this invention based on a 3D CAD model derived solely from original plans published in the Model Engineer magazine in 1982 and reproduced by Julius de Waal in 2018. Contributing to the field of industrial archeology, our novel research utilizes CAD, engineering drawing, and mechanical engineering principles to revitalize historical inventions. Our methodology allows for a detailed analysis of the design and function of these significant technological advancements, ensuring their legacy is preserved. However, challenges were encountered during the geometric modeling process due to missing dimensions for certain components and errors in others. To address these issues, dimensional, geometric, and kinematic constraints (degrees of freedom) had to be applied to ensure that the 3D CAD model was coherent and functional, and an interference analysis also had to be conducted. Ultimately, symmetry was discovered in the governor’s structure and the arrangement of the four valves within the cylinder block, particularly in the mechanism that operates the inlet valves. This symmetry is essential to ensure that forces and movements are distributed evenly during the steam exchange within the cylinder, allowing for more balanced work, reduced vibrations, and the optimization of the overall efficiency of the invention. Full article

The contact surface area (CSA) quantifies the interface between a tumor and an organ and is a key predictor of perioperative outcomes in kidney cancer. However, existing CSA computation methods rely on shape assumptions and manual annotation. We propose a novel approach using 3D reconstructions from computed tomography (CT) scans to provide an accurate CSA estimate. Our method includes a segmentation protocol and an algorithm that processes reconstructed meshes. We also provide an open-source implementation with a graphical user interface. Tested on synthetic data, the algorithm showed minimal error and was evaluated on data from 82 patients. We computed the CSA using both our approach and Hsieh’s method, which relies on subjective CT scan measurements, in a double-blind study with two radiologists of different experience levels. We assessed the correlation between our approach and the expert radiologist’s measurements, as well as the deviation of both our method and the less experienced radiologist from the expert’s values. While the mean and variance of the differences between the less experienced radiologist and the expert were lower, our method exhibited a slight deviation from the expert’s, demonstrating its reliability and consistency. These findings are further supported by the results obtained from synthetic data testing. Full article

Musculoskeletal ultrasound (US) imaging faces challenges such as operator experience, limited spatial flexibility, and high personnel costs. This study introduces an Automated Robotic Ultrasound Scanning (ARUS) system that integrates key technological advancements to automate the ultrasound scanning procedure with the robot, including anatomical target localization, automatic trajectory generation, deep-learning-based segmentation, and 3D reconstruction of musculoskeletal structures. The ARUS system consists of a robotic arm, ultrasound imaging, and stereo vision for precise anatomical area detection. A Graphical User Interface (GUI) facilitates a flexible selection of scanning trajectories, improving user interaction and enabling customized US scans. To handle complex and dynamic curvatures on the skin, together with anatomical area detection, the system employs a hybrid position–force control strategy based on the generated trajectory, ensuring stability and accuracy. Additionally, the utilized RA-UNet model offers multi-label segmentation on the bone and muscle tissues simultaneously, which incorporates residual blocks and attention mechanisms to enhance segmentation accuracy and robustness. A custom musculoskeletal phantom was used for validation. Compared to the reference 3D reconstruction result derived from the MRI scan, ARUS achieved a 3D reconstruction root mean square error (RMSE) of 1.22 mm, with a mean error of 0.94 mm and a standard deviation of 0.77 mm. The ARUS system extends 3D musculoskeletal imaging capacity by enabling both bones and muscles to be segmented and reconstructed into 3D shapes in real time and simultaneously. These features suggest significant potential as a cost-effective and reliable option for musculoskeletal examination and diagnosis in real-time applications. Full article

This article focuses on modern methods of documentation and visualization for a historic object. Digital photogrammetry and terrestrial laser scanning (TLS), which are essential tools for documenting cultural heritage in view of their rapid development in recent years, were used, compared, and analyzed. Furthermore, the use of available 3D computer graphics technologies for visualization is described and an optimal procedure for converting the object into VR and AR is proposed and implemented. The technologies presented in this article were tested within the context of a project on the reconstruction of the shrine of the Prophet Nahum in the city of Alqosh in northern Iraq, taking the shrine as a case study. Funded by ARCH Int. and provided by GemaArt Int., the restoration project started in 2018 and was completed in 2021. The ongoing documentation was prepared by the CTU and it used the materials for research purposes. Accurate documentation using photogrammetry, drones, and TLS was key to the restoration. Leica BLK360, Faro Focus S150, and GeoSlam laser scanners were used, as well as photogrammetric methods. In particular, the documentation process involved the creation of 3D textured models from the photogrammetry, which were compared to the TLS data to ensure accuracy. These models were necessary to track changes during the reconstruction phases and to calculate the volumes of rubble removed and materials added. Our data analysis revealed significant differences between the construction logs and the analysis of the accurate 3D models; the results showed an underestimation of the displaced material statements by 13.4% for removed material and 4.6% for added material. The use of heat maps and volumetric analyses helped to identify areas of significant change that guided the reconstruction and documented significant changes to the building for the investor. These findings are important for use in the construction industry with respect to historic sites as well as for further research focused on visualization using VR (virtual reality) and AR (augmented reality). The conversion of existing 3D models into VR and AR is rapidly evolving and significant progress was made during this project. The Unreal Engine (UE) game engine was used. Despite the significantly improved performance of the new UE 5 version, the data for conversion to VR and AR needs to be decimated to reduce the amount—in our case, this was by up to 90%. The quality appearance of the objects is then ensured by textures. An important outcome of this part of the research was the debugged workflow developed to optimize the 3D models for VR, which was essential for creating a virtual museum that shows the restoration process. Full article

Fractal geometry theory has been widely used in engineering image processing. In this work, the basic principles and features of fractal geometry are first introduced and its importance in image processing is explained. The features of the symmetry and asymmetry of images are represented in fractal geometry and symmetry scaling is utilized to deal with image processing problems in engineering applications. Subsequently, specific applications of fractal geometry in engineering image processing are discussed in detail in terms of image compression, edge detection, texture analysis, and image reconstruction and restoration. The exploration of these applications reveals the advantages and usefulness of fractal geometry theory in image processing, and it is found that the image has certain symmetry and self-similarity, which is conducive to the establishment of mathematical models for the statistics of graphic contours and shapes. Finally, the unique value of fractal geometry in engineering image processing is further emphasized by comparing the innovations of fractal geometry with traditional image processing methods, which prompts the in-depth consideration of its potential value in this field. This paper provides new insights and directions for the research of engineering image processing, which is of positive significance for future research. Full article