Laparoscopic Surgery Training Software
Multivariate Visualization for Surgical Training and Skill is an add-on to surgical simulation systems that displays new quantitative surgical performance data as it is collected from surgical instruments. This software was specifically designed to improve training for laparoscopic surgery, which is more difficult to train for because of the layer of indirection between the surgeon and the surgical tools. The software system visually displays the quantitative data--for example, the areas where too much pressure was applied are shaded in a different color--allowing surgeons to analyze and evaluate their operational skills. By providing immediate visual feedback, surgeons can improve their understanding of the collected quantitative data and their own surgical skills. This advancement reduces the lengthy process of surgical skills training in minimally invasive surgery and robotic surgery.
|MN-IP Try and Buy|
|This technology is available via a standard negotiated license agreement. Contact Andrew Morrow for specific details.|
Surgical Skills Improve with Multivariate Visualization
Multivariate Visualization for Surgical Training and Skill uses data visualization algorithms and applies these to the data derived from surgical simulations. The visualization interface is based on three main principles: linked views to allow for a richer exploration of the data, a “drill down” behavior to allow data subsets of interest to be examined in more detail, and integrated contextual information to prevent an individual from losing their place in the data. Integrating quantitative data results into a visual interface, yields objective data-driven evaluations of surgical skills.
FEATURES OF MULTIVARIATE VISUALIZATION FOR SURGICAL TRAINING:
- Improves surgical training--beneficial for laparoscopic surgery that is difficult to train for.
- Visual Interface--integrates quantitative results into visual display.
- Immediate feedback--surgeons can understand and evaluate the data more efficiently.