SurReal: enhancing Surgical simulation Realism using style transfer
This work addresses the need for more realistic surgical training tools for medical trainees, but it is incremental as it builds on existing style transfer methods.
The paper tackled the problem of low visual fidelity in surgical simulations by applying style transfer from real surgical video labels to synthetic content, demonstrating feasibility on cataract surgery simulations.
Surgical simulation is an increasingly important element of surgical education. Using simulation can be a means to address some of the significant challenges in developing surgical skills with limited time and resources. The photo-realistic fidelity of simulations is a key feature that can improve the experience and transfer ratio of trainees. In this paper, we demonstrate how we can enhance the visual fidelity of existing surgical simulation by performing style transfer of multi-class labels from real surgical video onto synthetic content. We demonstrate our approach on simulations of cataract surgery using real data labels from an existing public dataset. Our results highlight the feasibility of the approach and also the powerful possibility to extend this technique to incorporate additional temporal constraints and to different applications.