Real-time bronchoscope three-dimensional motion estimation using multiple sensor-driven alignment of CT images and electromagnetic measurements.

Bronchoscope three-dimensional motion estimation plays a key role in developing bronchoscopic navigation systems. Currently external tracking devices, particularly electromagnetic trackers with electromagnetic sensors, are increasingly introduced to navigate surgical tools in pre-clinical images. An unavoidable problem, which is to align the electromagnetic tracker to pre-clinical images, must be solved before navigation. This paper proposes a multiple sensor-driven registration method to establish this alignment without using any anatomical fiducials. Although current fiducially free registration methods work well, they limit to the initialization of optimization and manipulating the bronchoscope along the bronchial centerlines, which could be failed easily during clinical interventions. To address these limitations, we utilize measurements of multiple electromagnetic sensors to calculate bronchoscope geometric center positions that are usually closer to the bronchial centerlines than the sensor itself measured positions. We validated our method on a bronchial phantom. The experimental results demonstrate that our idea of using multiple sensors to determine bronchoscope geometric center positions for fiducial-free registration was very effective. Compared to currently available methods in bronchoscope three-dimensional motion estimation, our method reduced fiducial alignment error from at least 6.79 to 4.68-5.26 mm and significantly improved motion estimation or tracking accuracy from at least 5.42 to 3.78-4.53 mm. Crown