EG2025

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https://diglib.eg.org/handle/10.2312/3607134

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Browsing EG2025 by Subject "Applied computing → Interactive learning environments"

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    Non-linear, Team-based VR Training for Cardiac Arrest Care with enhanced CRM Toolkit
    (The Eurographics Association, 2025) Kentros, Mike; Kamarianakis, Manos; Cole, Michael; Popov, Vitaliy; Protopsaltis, Antonis; Papagiannakis, George; Ceylan, Duygu; Li, Tzu-Mao
    This paper introduces iREACT, a novel VR simulation addressing key limitations in traditional cardiac arrest (CA) training. Conventional methods struggle to replicate the dynamic nature of real CA events, hindering Crew Resource Management (CRM) skill development. iREACT provides a non-linear, collaborative environment where teams respond to changing patient states, mirroring real CA complexities. By capturing multi-modal data (user actions, cognitive load, visual gaze) and offering real-time and post-session feedback, iREACT enhances CRM assessment beyond traditional methods. A formative evaluation with medical experts underscores its usability and educational value, with potential applications in other high-stakes training scenarios to improve teamwork, communication, and decision-making.
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    VisibleUS: From Cryosectional Images to Real-Time Ultrasound Simulation
    (The Eurographics Association, 2025) Casanova-Salas, Pablo; Gimeno, Jesus; Blasco-Serra, Arantxa; González-Soler, Eva María; Escamilla-Muñoz, Laura; Valverde-Navarro, Alfonso Amador; Fernández, Marcos; Portalés, Cristina; Günther, Tobias; Montazeri, Zahra
    The VisibleUS project aims to generate synthetic ultrasound images from cryosection images, focusing on the musculoskeletal system. Cryosection images provide a highly accurate representation of real tissue structures without artifacts. Using this rich anatomical data, we developed a ray-tracing-based simulation algorithm that models ultrasound wave propagation, scattering, and attenuation. This results in highly realistic ultrasound images that accurately depict fine anatomical details, such as muscle fibers and connective tissues. The simulation tool has various applications, including generating datasets for training neural networks and developing interactive training tools for ultrasound specialists. Its ability to produce realistic ultrasound images in real time enhances medical education and research, improving both the understanding and interpretation of ultrasound imaging.