Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots
This addresses the need for reliable navigation in minimally invasive medical procedures, though it appears incremental as it builds on existing sensor fusion and non-rigid deformation techniques.
The paper tackles the problem of 3D reconstruction and localization for endoscopic capsule robots in the gastrointestinal tract, proposing a sensor fusion method that achieves root mean square surface reconstruction errors of 1.58 to 2.17 cm in ex-vivo tests.
Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is demonstrated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors 1.58 to 2.17 cm.