Evaluating the Potential Benefit of Autostereoscopy in Laparoscopic Sacrocolpopexy through VR Simulation During laparoscopic sacrocolpopexy, pelvic organ prolapse is repaired by suturing one side of a synthetic mesh around the vaginal vault while stapling the other end to the sacrum, restoring the anatomical position of the vagina. A perineal assistant positions and tensions the vault with a vaginal manipulator instrument to properly expose the vaginal tissue to the laparoscopic surgeon. A technical difficulty during this surgery is the loss of depth perception due to visualization of the patientu0027s internals on a 2D screen. Especially during precise surgical tasks, a more natural way to understand the distance between the laparoscopic instruments and the surgical region of interest could be advantageous. This work describes an exploratory study to investigate the potential of introducing 3D visualization into this surgical intervention. More in particular, experimentation is conducted with autostereoscopic display technology. A mixed reality setup was constructed featuring a virtual reality model of the vagina, 2D and 3D visualization, a physical interface representing the tissue of the body wall and a tracking system to track instrument motion. An experiment was conducted whereby the participants had to navigate the instrument to a number of predefined locations under 2D or 3D visualization. Compared to 2D, a considerable reduction in average task time (42.9 %), travelled path lenght (31.8 %) and errors (52.2 %) was observed when performing the experiment in 3D. Where this work demonstrated a potential benefit of autostereoscopic visualization with respect to 2D visualization, in future work we wish to investigate if there also exists a benefit when comparing this technology with conventional stereoscopic visualization and whether stereoscopy can be used for (semi) automated guidance during robotic laparoscopy.

Multicamera 3D Reconstruction of Dynamic Surgical Cavities: NonRigid Registration and Point Classification Deformable objects and surfaces are ubiquitous in the daily lives of humans xe2x80x93 from the garments in fashion to soft tissues within the body. Because of this routine interaction with soft materials, humans are adept and trained in manipulation of deformable objects while avoiding irreversible damage. The dexterity and care involved is largely facilitated through a combination of the human haptic sense of touch and visual observations of object deformation 1. While this scenario presents itself as a trivially intuitive task, it becomes significantly more difficult and complex with the deprivation of both 3D depth perception and haptic senses. This deprived state is not dissimilar to the scenarios encountered in many robotassisted minimally invasive surgeries. As a result, unintentional tissue damage can occur due to lack of force feedback and fine 3D visibility 2. One approach to remediate these issues combines realtime dynamic 3D reconstruction and visionbased force estimation for haptic feedback. Toward that end, this work continues research in a series of studies focusing on multicamera 3D reconstruction of dynamic surgical cavities. Previous work introduced a novel approach of camera grouping and pair sequencing 3. This paper builds upon that work by introducing a method for nonrigid, sparse point cloud registration and subsequent point classification. In particular, to enable deformation and force analyses, surfaces are locally classified into three categories: static, shifting and deforming. The topics addressed in this paper present open challenges and ongoing research directions for researchers to this day 4, and provide a step towards realtime 3D reconstruction and force feedback in robotassisted surgery.