Effective 3D patient data visualization for brain MRI is required in surgical planning and in-situ guidance during brain tumor resection. Traditional 2D displays do not possess depth perception and are poor in underst...
详细信息
ISBN:
(数字)9798350351422
ISBN:
(纸本)9798350351439
Effective 3D patient data visualization for brain MRI is required in surgical planning and in-situ guidance during brain tumor resection. Traditional 2D displays do not possess depth perception and are poor in understanding complex anatomical structures being displayed in 3D. In this work, an interactive visualization system based on augmented reality is presented, which provides an intuitive and truly immersive way to visualize and interact with 3D brain MRI data as preoperative planning and in-situ guidance by a surgeon during tumor resection procedures of the brain. In this work, we propose a system where AR Devices can render patient-specific 3D brain models, reconstructed from MRI data, in a spatially registered way to the surgical field. These 3D virtual models can be interacted by the surgeon, through the natural use of controls, to study the spatial relationship of critical structures such as tumors, ventricles, and functional brain regions. Advanced volume rendering and multi-modal data fusions are used in creating photorealistic 3D visualizations with high anatomical detail.
作者:
Durra, MahganjAl-Naymat, Ghazi
College of Engineering and Information Technology Ajman University United Arab Emirates
In the current data-driven era, businesses continuously generate vast quantities of data, underscoring the critical importance of deriving actionable insights from this data deluge to inform decision-making. Despite t...
详细信息
Over the past 40 years, immersive visualization laboratories have existed in various forms across academia, industry, and government. Common to many of these laboratories has been the presence of surround-screen-based...
详细信息
ISBN:
(数字)9798331514846
ISBN:
(纸本)9798331525637
Over the past 40 years, immersive visualization laboratories have existed in various forms across academia, industry, and government. Common to many of these laboratories has been the presence of surround-screen-based immersive display systems, such as CAVEs, powerwalls, tiled display systems, and related variations. With the rise of consumer off-the-shelf (COTS) virtual reality (VR) head-mounted displays (HMDs) over the past ten years, questions have arisen regarding the costs versus benefits of continuing to build, operate, and maintain surround-screen-based immersive display systems. This document highlights the benefits of continuing to promote these systems, both through a survey of existent systems post-2020 and by specifically showcasing low-cost approaches undertaken during a recent upgrade of a six-sided CAVE system. It will discuss applications unique to surround-screen-based immer-sive display systems, the advantages of these systems over COTS HMDs, and future needs and directions for these technologies to remain beneficial to users of XR technology.
Due to the increasing number of cyberattacks and respective predictions for the upcoming years with even larger numbers of occurrences, companies are becoming aware not only that the digitization of their businesses i...
详细信息
ISBN:
(纸本)9780738124766
Due to the increasing number of cyberattacks and respective predictions for the upcoming years with even larger numbers of occurrences, companies are becoming aware not only that the digitization of their businesses is essential, but also that the adoption of efficient cybersecurity strategies is crucial. Therefore, approaches for a better understanding and analysis of cybersecurity are essential. Thus, SecGrid, a Machine Learning (ML) empowered platform for analyzing, classification, and visualization of cyberattacks is introduced. SecGrid implements an extensible set of miners to analyze information from network traces to provide insightful visualizations of malicious traffic given and to classify automatically different types of cyberattacks by using supervised ML. Experiments conducted show high overall usability, scalability in terms of the capacity of the platform to extract information from large files, and high performance and accuracy during the classification of cyberattacks.
This paper investigates the factors influencing the development of China's New Energy Vehicle (NEV) industry using an ARIMA model and power function nonlinear regression. A comprehensive dataset spanning 2013-2022...
详细信息
ISBN:
(数字)9798350389579
ISBN:
(纸本)9798350389586
This paper investigates the factors influencing the development of China's New Energy Vehicle (NEV) industry using an ARIMA model and power function nonlinear regression. A comprehensive dataset spanning 2013-2022 was collected and preprocessed, including technical, economic, convenience, and policy factors. The study employs entropy weight method for comprehensive evaluation and constructs a multiple linear regression model to analyze the impact of key factors. Correlation analysis and PCA visualization confirm the significant relationship between these factors and NEV development. The ARIMA and power function nonlinear regression models predict a robust growth in China's NEV industry over the next decade, with both models showing high accuracy in forecasting.
Various real-world factors, such as time, weather, distance, environment, the COVID-19 pandemic, or even protests, can all impact human decision-making. However, restrictions and unexpected occurrences may also influe...
详细信息
The paper originally presents a wireless AC power monitoring module by integrating voltage and current sensors with a WeMos D1 mini WiFi module and shows the visualization of voltage, current, electric power and energ...
详细信息
Training a robot through demonstration requires robust algorithms capable of processing provided trajectories to generate high-quality task executions. However, the success of this process is highly dependent on the q...
详细信息
ISBN:
(数字)9798350378931
ISBN:
(纸本)9798350378948
Training a robot through demonstration requires robust algorithms capable of processing provided trajectories to generate high-quality task executions. However, the success of this process is highly dependent on the quality of the trajectories. Poor-quality trajectories hinder the ability of algorithms to learn and generalize effectively, while high-quality trajectories can improve learning outcomes, reducing the need for overly complex algorithms. In this work, we propose an initial method for comparing sets of semantically annotated trajectories used for robot demonstration. To evaluate the proposed methodologies, we recorded trajectories of 60 participants in a study setup in Virtual Reality where each participant tested one of three different control-visualization compositions. We use classical approaches such as Dynamic Time Warping and Discrete Frechet-Distance to measure the similarity between segments of recorded trajectories and show that different input devices and visualization combinations affect the resulting trajectory metrics.
The Villanova CAVE was established under the auspices of the school's Center of Excellence in Enterprise Technology in 2014. Over the following nine years the facility and the Center have experienced several succe...
详细信息
The Villanova CAVE was established under the auspices of the school's Center of Excellence in Enterprise Technology in 2014. Over the following nine years the facility and the Center have experienced several successes and challenges in supporting research and teaching with VR on campus. This paper reviews the Center's work with the CAVE as a large-scale facility and its strategies for promoting VR and visualization. It concludes with some challenges for both HMD-based facilities and large scale facilities.
Alpine skiing is a popular winter sport, and several systems have been proposed to enhance training and improve efficiency. However, many existing systems rely on simulation-based environments, which suffer from drawb...
Alpine skiing is a popular winter sport, and several systems have been proposed to enhance training and improve efficiency. However, many existing systems rely on simulation-based environments, which suffer from drawbacks such as a gap between real skiing and the lack of body ownership. To address these limitations, we present ARpenSki, a novel augmented reality (AR) ski training system that employs a see-through head mounted display (HMD) to deliver augmented visual training cues that may be applied on real slopes. The proposed AR system provides a transparent view of the lower half of the field of vision, where we implemented three different AR-based direct and indirect postural visualization methods. We conducted an user study to investigate the influence of different visual cues in the AR environment. Our results indicate that a simple AR visualization of the user’s spine (Figure 1.2) yields the most favorable training performance, surpassing conventional visualizations by 7% improvement in the user’s posture. Building upon these promising findings, we further tested our system on real slopes and showed the potential of a real AR skiing application.
暂无评论