Data fusion for catheter tracking using Kalman filtering: applications in robot-assisted catheter insertion

Abstract

X-ray image guided angioplasty is a minimally invasive procedure that involves the insertion of a catheter into a blood vessel to remove blockages to blood flow. There are several issues associated with conventional angioplasty which cause risks for the patient (damage to blood vessels, dislodging plaques, etc.) and difficulties for the clinician (X-ray exposure, fatigue, etc.). Autonomous or semi-autonomous robot-assisted catheter insertion is a solution that can reduce these problems substantially. To perform autonomous catheter insertion, closed-loop position control of the distal tip of the catheter is required during insertion. Therefore accurate real-time position feedback is needed for this purpose. We have developed a real-time image processing algorithm for catheter tip position tracking which has an acceptable performance but is sensitive to X-ray image artifacts caused by bones and dense tissues. A magnetic tracking system (MTS) is another modality that has also been used for catheter tip position tracking, but it is sensitive to external electromagnetic interferences and ferromagnetic material. Combining the measurement data provided by both imaging and magnetic sensors can compensate for the deficiencies of each and can also improve the robustness of catheter tip position tracking. We have developed a Kalman filter based sensor fusion scheme to overcome deficiencies of both of these methods and create a reliable real-time tracking of a catheter tip. Experiments have been performed by inserting a guide catheter into a model of the vasculature. The method has been tested in presence of occlusion in the images and also electromagnetic interference.