AR/VR/XR and AI-Driven Immersive Visualization in Medical Imaging and Healthcare (MedXR- 2026)

Goal of the workshop

MedXR-2026 aims to bring together researchers, doctors, developers, and industry specialists to further the incorporation of Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), and Artificial Intelligence (AI) in medical imaging and clinical practices. This workshop seeks to promote interdisciplinary collaboration, emphasize emerging technologies, and investigate how immersive systems might improve diagnosis, surgical planning, medical training, and patient care.

Workshop theme

Conventional visualization techniques for CT, MRI, PET, ultrasound, and histopathological data depend on static 2D displays, which constrain depth perception and interactivity. The integration of VR/AR/XR with AI, generative models, digital twins, and 3D reconstruction is revolutionizing doctors’ exploration, interpretation, and application of medical data. MedXR-2026 will concentrate on:

• AI-enhanced immersive visualization
• Real-time 3D interaction with medical imagery
• Digital twins and individualized patient simulations
• VR/AR tools for diagnoses, training, and intervention
• Integration of clinical operations with extended reality technologies

Scope of the workshop

Researchers and practitioners globally, from academia and industry, engaged in computer science, healthcare, and VR development, are invited to discuss cutting-edge solutions, emerging issues, recent advancements, applications, experience reports, methodologies, techniques, and tools for the development and application of VR in enhancing the visualization, interpretation, and utilization of medical images in clinical practice. Topics of interest include, but are not limited to, the following:

• Engaging Visualization and Interaction
  -Visualization of CT, MRI, PET, ultrasound, and pathology using VR, AR, and XR technologies
  -Digital twins, 3D anatomical rendering, virtual surgical navigation
  -Mixed Reality in the surgical environment
  -Exploration of interactive volumetric data
  
  
• AI and Multi-modal Integration
  -AI-augmented segmentation and 3D reconstruction for extended reality
  -Generative models (GANs, diffusion) for synthetic immersive data generation
  -Integration of imaging, biosignals, and clinical text into VR/AR platforms
  -LLM-driven assistants for interactive diagnosis and reporting
  
  
• Training, Simulation, and Clinical Practice
  -VR-based surgical skills training and residency education
  -Haptic-augmented immersive simulation
  -XR for anatomical instruction and medical student education
  -Rehabilitation, cognitive therapy, and telehealth patient engagement
  
  
• Systems, Implementation & Infrastructure
  -Edge and cloud computing for realtime rendering and streaming
  -Techniques for GPU acceleration and compression
  -Telemedicine and remote cooperation in XR environments
  -Integration of workflows and interoperability
  
  
• Ethics, Security, and Evaluation
  -Privacy-preserving immersive platforms
  -Clinical validation and regulatory factors
  -Human-computer interaction and usability evaluation
  -Ethical considerations of XR-based diagnosis and therapy