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Abstract-This work presents a novel scheme for tracking of motion and deformation of interventional tools such as guidewires and catheters in fluoroscopic X-ray sequences. Being able to track and thus to estimate the correct positions of these tools is crucial in order to offer guidance enhancement during interventions. The task of estimating the apparent motion is particularly challenging due to the low signal to noise ratio (SNR) of fluoroscopic images and due to combined motion components originating from patient breathing and tool interactions performed by the physician.The presented approach is based on modeling interventional tools with B-splines whose optimal configuration of control points is determined through efficient discrete optimization. Each control point corresponds to a discrete random variable in a Markov random field (MRF) formulation where a set of labels represents the deformation space. In this context, the optimal curve corresponds to the maximum a posteriori (MAP) estimate of the MRF energy. The main motivation for employing a discrete approach is the possibility to incorporate a multi-directional search space which is robust to local minima. This is of particular interest for curve tracking under large deformation.This work analyzes feasibility of employing efficient first-order MRFs for tracking. In particular it shows how to achieve a good compromise between energy approximations and computational efficiency. Experimental results suggest to define both the external and internal energy in terms of pairwise potential functions. The method was successfully applied to the tracking of guide-wires in fluoroscopic X-ray sequences of several hundred frames which requires extremely robust techniques. Comparisons with state-ofthe-art guide-wire tracking algorithms confirm the effectiveness of the proposed method.

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3D road-mapping with syngo iPilot was used as an additional tool for assessing cerebral aneurysms and arteriovenous malformations (AVMs) for endovascular therapy. This method provides accurate superimposition of a live fluoroscopic image (native or vascular road-map) and its matching 2D projection of the 3D data set, delivering more anatomic information on one additional display. In the endovascular management of cases with complex anatomy, 3D road-mapping provides excellent image quality at the intervention site. This method can potentially reduce intervention time, the number of DSA runs, fluoroscopy time and the amount of contrast media used in a procedure, with reservation for these factors being mainly operator-dependent. 3D road-mapping probably does not provide any advantage in the treatment of cerebral aneurysms or AVMs with very simple configuration, and it should not be used when acquisition of an optimum 3D data set is not feasible.