LAUSR

Catheter tracking is essential during minimally invasive endovascular procedures, and Electromagnetic (EM) tracking is a widely used technology for this purpose. When preoperative patient images are available, they can be used to guide EM-tracked interventions. However, a registration step between preoperative images and intraoperative EM tracking space is usually required. Most existing solutions for this registration process require manual interactions, which can add additional steps to the workflow. In this letter, a novel automatic feature-based registration method is proposed, based on electric sensing of vascular geometry by the catheter, also known as Bioelectric sensing. The technique employs the Bioelectric sensing capabilities of the catheter to identify vascular features, such as bifurcations, aneurysms, or stenosis. The known EM position of these features is then utilized to register the EM tracking space and the preoperative images. The registration is refined using iterative closest point (ICP) registration algorithms. Unlike existing solutions, the proposed method does not require external markers, interventional imaging, or additional surgeon actions, and hence does not impact the interventional workflow.