Accurate 3D multi-marker tracking in X-ray cardiac sequences using a two-stage graph modeling approach

The in-depth analysis of heart movements under varying conditions is an important problem of cardiac surgery. To reveal the movement of relevant muscular parts, biplanar X-ray recordings of implanted radio-opaque markers are acquired. As manually locating these markers in the images is a very time-consuming task, our goal is to automate this process. Taking into account the difficulties in the recorded data such as missing detections or 2D occlusions, we propose a two-stage graph-based approach for both 3D tracklet and 3D track generation. In the first stage of our approach, we construct a directed acyclic graph of 3D observations to obtain tracklets via shortest path optimization. Afterwards, full tracks are extracted from a tracklet graph in a similar manner. This results in a globally optimal linking of detections and tracklets, while providing a flexible framework which can easily be adapted to various tracking scenarios based on the edge cost functions. We validate our approach on an X-ray sequence of a beating sheep heart based on manually labeled ground-truth marker positions. The results show that the performance of our method is comparable to human experts, while standard 3D tracking approaches such as particle filters are outperformed.