Hello! I’m Wenhao Gu, a PhD student at Johns Hopkins University, part of the ARCADE lab in the Laboratory for Computational Sensing and Robotics (LCSR). My work combines technology and healthcare, focusing on improving surgeries with mixed reality. Under the guidance of my advisor, Mathias Unberath, I aim to create mixed reality workflows that make surgical procedures more precise and effective with computer vision and human-centered design.
Gu, W., Knopf, J., Cast, J., Higgins, L. D., Knopf, D., & Unberath, M. (2023). Nail it! vision-based drift correction for accurate mixed reality surgical guidance. International Journal of Computer Assisted Radiology and Surgery, 18(7), 1235-1243.
Gu, W., Martin-Gomez, A., Cho, S. M., Osgood, G., Bracke, B., Josewski, C., … & Unberath, M. (2022). The impact of visualization paradigms on the detectability of spatial misalignment in mixed reality surgical guidance. International Journal of Computer Assisted Radiology and Surgery, 17(5), 921-927.
Gu, W., Shah, K., Knopf, J., Josewski, C., & Unberath, M. (2022). A calibration-free workflow for image-based mixed reality navigation of total shoulder arthroplasty. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 10(3), 243-251.
Gu, W., Shah, K., Knopf, J., Navab, N., & Unberath, M. (2021). Feasibility of image-based augmented reality guidance of total shoulder arthroplasty using microsoft HoloLens 1. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 9(3), 261-270.
Gu, W., Gao, C., Grupp, R., Fotouhi, J., & Unberath, M. (2020). Extended capture range of rigid 2d/3d registration by estimating riemannian pose gradients. In Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings 11 (pp. 281-291). Springer International Publishing.