Guidewire tracking using a novel sequential segment optimization method in interventional X-ray videos

Abstract

Robust guidewire tracking is important in many clinical applications yet it is still a very challenging problem. A guidewire is a thin, deformable medical device and usually appears in low quality X-ray imagery. Moreover, distracters with stronger gradient response may also present in the scenario. In this paper, we model the wire-like structure as a sequence of small segments and formulate guidewire tracking as a graph-based optimization problem which aims to find the optimal link set. To overcome distracters, we extract them from the dominant motion pattern and propose a confidence re-weighting process in the appearance measurement. Medical validations have shown over 50 percent reduction in mean tracking error in 54 clinical X-Ray sequences compared with a state-of-the-art guidewire tracking method.