Accurate Evaluation of Rotational Angle and Translation Movement of Our Organ-Following Algorithm Based on Depth-Depth Matching

We present an algorithm, based on simulated annealing, that causes a virtual liver to mimic an actual liver. We evaluate its precision using the concordance rate of range images of both virtual and actual livers. This concordance rate is evaluated by superimposing a range image, in which a liver polyhedron standard triangulated language form is put through graphical z-buffering using the computer graphics of a PC and a depth image of the actual liver taken with Kinect v2. However, when the actual liver moves in a translational and rotational manner, we are unable to evaluate how accurately the concordance rate corresponds to the actual movement. In this study, we first manufacture a mechanical system that moves a replica of an actual liver in a translational and rotational manner for measurement. This system has two translational degrees of freedom (i.e., X, Y) and three rotational degrees of freedom (i.e., yaw, roll, pitch). This enables the system to move the replica of an actual liver in an extremely accurate manner. Next, we precisely move the actual liver and investigate how much the simulated annealing-based algorithm moves the virtual liver, and we evaluate its accuracy. Whereas previous experiments were conducted under fluorescent lamps and sunlight, our experiment is conducted in an operating room lit by two shadow-less lamps. The Kinect v2 captures depth images utilizing a shade filter to prevent interference from the infrared light of the shadow-less lamps. The past concordance rate and precision of the amount of translational and rotational movement are also evaluated.