An Observer-Based Fusion Method Using Multicore Optical Shape Sensors and Ultrasound Images for Magnetically-Actuated Catheters

Minimally invasive surgery involves using flexible medical instruments such as endoscopes and catheters. Magnetically actuated catheters can provide improved steering precision over conventional catheters. However, besides the actuation method, an accurate tip position is required for precise control of the medical instruments. In this study, the tip position obtained from transverse 2D ultrasound images and multicore optical shape sensors are combined using a robust sensor fusion algorithm. The tip position is tracked in the ultrasound images using a template-based tracker and a convolutional neural network based tracker, respectively. Experimental results for a rhombus path are presented, where data obtained from both tracking sources are fused using Luenberger and Kalman state estimators. The mean and standard deviation of the Euclidean error for the Luenberger observer is $0.2\pm 0.11$ [mm] whereas for the Kalman filter it is $0.18\pm 0.13$ [mm], respectively.