Dynamic Cone-Beam Reconstruction Using a Variational Level Set Formulation

Tomographic reconstruction from rotational cone-beam X-ray data is only solved for static objects of interest (like the abdominal region). In cardiac imaging, a rotational angiography sequence takes about 3 to 5s and therefore spans several heart beats. Since such an acquisition scheme forces a trade-off between consistency of the scene and reasonable baselines between camera positions, standard reconstruction techniques fail at recovering the 3D+t scene. We propose a new reconstruction framework based on variational level sets including a new data term for symbolic reconstruction as well as a novel incorporation of motion into the level set formalism. The resulting simultaneous estimation of shape and motion proves feasible in the presented experiments. Since the proposed formulation offers a great flexibility in incorporating other data terms as well as hard or soft constraints, it allows an adaption to a wider range of problems and could be of interest for other reconstruction settings as well.     «

Tomographic reconstruction from rotational cone-beam X-ray data is only solved for static objects of interest (like the abdominal region). In cardiac imaging, a rotational angiography sequence takes about 3 to 5s and therefore spans several heart beats. Since such an acquisition scheme forces a trade-off between consistency of the scene and reasonable baselines between camera positions, standard reconstruction techniques fail at recovering the 3D+t scene. We propose a new reconstruction fram...     »