Layer-By-Layer 3D Virtual Cadaver Models Using Photogrammetry and Lidar for Skull Base Education

Objective: Cadaveric dissection is considered the gold standard for learning skull base anatomy, yet access is often restricted by limited availability, high costs, and the one-time use of specimens. This study aimed to develop reproducible, high-resolution 3D cadaver models using photogrammetry and LiDAR technology, and to assess their potential role in surgical education. Methods: Cadaveric heads were sequentially dissected in a layer-by-layer manner. At each stage, high-resolution images were obtained with photogrammetry and LiDAR cameras. The collected datasets were processed using commercially available software to generate virtual 3D models with layered structures. These models allowed interactive visualization, selective removal of anatomical layers, and repeated inspection of key regions relevant to skull base surgery. Results: The resulting 3D models demonstrated high spatial fidelity in reproducing critical skull base anatomical structures, including deep neurovascular complexes. Users reported that the models enhanced their spatial understanding, facilitated pre-laboratory preparation, and provided opportunities for repetitive practice that are not possible with traditional cadaveric dissection. The system also offered an accessible and portable resource for institutions with limited cadaver availability. Conclusion: Layered 3D virtual cadaver models constructed using photogrammetry and LiDAR represent a valuable adjunct to skull base anatomical education. By enabling repeated, interactive, and detailed exploration, they reduce dependence on physical cadaveric material and may expand global access to high-quality surgical training resources. Integration with virtual or augmented reality platforms may further enhance their role in future neurosurgical education. Publication History Article published online: 27 February 2026 © 2026. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany