This paper addresses an approach toward tomographic reconstruction from rotational angiography data as it is generated by C-arms in cardiac imaging. Since the rotational acquisition scheme forces a trade-off between consistency of the scene and reasonable baselines, most existing reconstruction techniques fail at recovering the 3D 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 to other reconstruction settings as well.     «

This paper addresses an approach toward tomographic reconstruction from rotational angiography data as it is generated by C-arms in cardiac imaging. Since the rotational acquisition scheme forces a trade-off between consistency of the scene and reasonable baselines, most existing reconstruction techniques fail at recovering the 3D 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...     »