HoloInset: 3D Biomedical Image Data Exploration through Augmented Hologram Insets

Junyoung Choi, Haejin Jeong, Won-Ki Jeong

Abstract: The extended reality (XR) provides realistic depth perception and huge visualization spaces, which can serve as a powerful workspace for 3D data exploration and analysis. However, a direct adaptation of XR to conventional 3D data exploration tasks is less feasible due to several hardware limitations, such as low screen resolution, dizziness, narrow field of view, etc. In this paper, we propose a novel mixed reality visualization scheme, HoloInset, which combines a conventional visual analytics system and a virtual environment to effectively explore 3D biomedi-cal image data. We also demonstrate the usability of the proposed visualization through a real-world analysis case.