A comparison of modified evolutionary computation algorithms with applications to three-dimensional endoscopic camera motion tracking
Endoscope 3D motion tracking plays an irreplaceable role for computer-assisted endoscopy systems development. Without such tracking, it is impossible to synchronize pre- and intraoperative images in a reference coordinate frame. Currently available methods are comprised of video-based and electromagnetic tracking. These methods limit to either video image artifacts or inaccurate sensor measurements and dynamic errors. This paper proposes two modified evolutionary computation algorithms: (a) adaptive particle swarm optimization (APSO) and (b) observation-boosted differential evolution (OBDE), to augment current endoscopic camera motion tracking. The experimental results demonstrate that our modified algorithms, which combine endoscopic video images with sensor measurements to estimate endoscope movements, can improve tracking accuracy from 4.8 mm to 2.9 mm. OBDE outperforms APSO for endoscope tracking.