VolumetricOR: A new Approach to Simulate Surgical Interventions in Virtual Reality for Traning and Education

With VolumetricOR surgical staff can learn and train surgical interventions in a photorealistic virtual operating room. Situated in the virtual reality environment users can experience surgical workflows based on the spatial reconstruction of images recorded directly in the operating theater. While existing simulation formats restrict users in terms of scale, perspective and field of view, in VolumetricOR trainees can experience a scene three-dimensionally, from any perspective and in real scale as if they are physically present.

VolumetricOR improves the linking of theoretical expertise and practical application of knowledge and shifts the learning experience from observation to participation. It can be applied for digital training and education as well as for quality assessment, legal documentation and recruitment. Trainees can acquire procedural knowledge before going to the operating room and professional staff could improve the efficiency and quality of the learning and training process by communicating techniques and workflows when the possibilities of training on-site are limited. By enabling hospitals to produce their own volumetric content, we would like to empower them to build digital classrooms to communicate surgical skills and workflows in the OR.

The project is funded by the German Research Foundation and Charité Universitätsmedizin Berlin.

Publications:
Queisner M, Pogorzhelskiy M, Remde C, Pratschke J,  Sauer IM. VolumetricOR: A new Approach to Simulate Surgical Interventions in Virtual Reality for Training and Education. Surgical Innovation. 2022;  doi: 10.1177/15533506211054240.

Info
Funded by the German Research Foundation
Partner: Cluster of Excellence Image Knowledge Gestaltung, Humboldt University of Berlin

Image
Image
Image

Our Team

Stacks Image 2000

Head of Experimental Surgery

Stacks Image 2105

Junior Research Group Leader

Stacks Image 2121

Michael Pogorzhelskiy

Researcher

Stacks Image 2113

Researcher

Stacks Image 2037

Peter Tang

Research Assistant

This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purpose illustrated in the Disclaimer. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to the use of cookies.