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    MD-Cave is an immersive analytics system enhancing radiologist visual diagnoses with 3D visualizations and interactions. This system supports deep-seated anatomical structure visualization for various diagnostic scenarios.

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    Area of Science:

    • Medical Imaging
    • Computer-Aided Diagnosis
    • Human-Computer Interaction

    Background:

    • Radiologists require advanced tools for interpreting complex 3D volumetric data.
    • Current visualization methods may not fully leverage the potential of 3D imaging.
    • Immersive technologies offer new paradigms for visual data analysis.

    Purpose of the Study:

    • To introduce the MD-Cave, an immersive analytics system for enhanced radiological diagnosis.
    • To evaluate the system's utility and 3D interaction capabilities in real-world radiological examinations.
    • To demonstrate the system's general framework for visualizing deep-seated anatomical structures.

    Main Methods:

    • Development of MD-Cave integrating high-resolution stereoscopic surround triple-monitor visualization.
    • Implementation of 3D interactions using head and hand tracking.
    • Creation of a general framework supporting 3D visualization without explicit segmentation.

    Main Results:

    • MD-Cave provides enhanced stereoscopic visualizations and intuitive 3D interactions.
    • The system is practical for radiologists, considering desk space and long-duration use.
    • Case studies demonstrated utility in diagnosing pancreatic cancer, shoulder-CT, and COVID-19 Chest CT.

    Conclusions:

    • MD-Cave offers a versatile solution for improving visual diagnoses in radiology.
    • The immersive system effectively supports the investigation of 3D volumetric data.
    • Close collaboration with radiologists ensured clinical relevance and user-centered design.