IMHOTEP - Virtual Reality Framework for Surgical Applications
Micha Pfeiffer, Hannes Kenngott, Anas Preukschas, Matthias Huber, Lisa, Bettscheider, Beat M\"uller-Stich, Stefanie Speidel

TL;DR
IMHOTEP is an open-source VR framework that enhances surgical planning and education by providing an immersive, modular environment for visualizing and manipulating complex 3D patient data, demonstrating high clinical acceptance.
Contribution
The paper introduces IMHOTEP, a modular, open-source VR framework that integrates multi-modal patient data for surgical applications, improving comprehension and training.
Findings
Majority found complex surgeries easier with IMHOTEP
Framework is well-suited for educational purposes
Demonstrated adaptability in various clinical scenarios
Abstract
Purpose: The data which is available to surgeons before, during and after surgery is steadily increasing in quantity as well as diversity. When planning a patient's treatment, this large amount of information can be difficult to interpret. To aid in processing the information, new methods need to be found to present multi-modal patient data, ideally combining textual, imagery, temporal and 3D data in a holistic and context-aware system. Methods: We present an open-source framework which allows handling of patient data in a virtual reality (VR) environment. By using VR technology, the workspace available to the surgeon is maximized and 3D patient data is rendered in stereo, which increases depth perception. The framework organizes the data into workspaces and contains tools which allow users to control, manipulate and enhance the data. Due to the framework's modular design, it can easily…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
