Keil Andreas, Vogel Jakob, Lauritsch Günter, Navab Nassir
Computer Aided Medical Procedures, TU München, Germany.
Med Image Comput Comput Assist Interv. 2009;12(Pt 2):389-97. doi: 10.1007/978-3-642-04271-3_48.
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 + 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 to other reconstruction settings as well.
本文探讨了一种从心脏成像中C型臂生成的旋转血管造影数据进行断层重建的方法。由于旋转采集方案迫使在场景一致性和合理基线之间进行权衡，大多数现有的重建技术在恢复3D + t场景时均告失败。我们提出了一种基于变分水平集的新重建框架，其中包括用于符号重建的新数据项以及将运动新颖地纳入水平集形式体系。在所示实验中，由此产生的形状和运动的同时估计证明是可行的。由于所提出的公式在纳入其他数据项以及硬约束或软约束方面具有很大的灵活性，它允许适应更广泛的问题，并且可能对其他重建设置也有意义。
