Visual instrument guidance in minimally invasive robot surgery

Surgical tool tracking is an important key functionality for many high-level tasks such as the visual guidance of surgical instruments or automated camera control. Readings from robot encoders and the kinematic chain are usually error prone in this kind of complex setup, but still allow for a coarse pose estimation of the instruments in image space. This information can be utilized to (re-)initialize image-based tracking in case of tracking loss and supervise the tracking process. Accounting for the difficult environmental conditions in surgery, the choice of an appropriate tracking modality is important. We have chosen the Contracting Curve Density algorithm (CCD) that maximizes the separation of local color statistics along the contour of a model in contrast to the background. As an application example, the visual guidance of laparoscopic instruments under trocar kinematic is presented.