Fraunhofer MEVIS, Universitätsallee 29, 28359 Bremen, Germany.
Med Image Anal. 2010 Apr;14(2):160-71. doi: 10.1016/j.media.2009.12.003. Epub 2009 Dec 16.
A multiple hypothesis tracking approach to the segmentation of small 3D vessel structures is presented. By simultaneously tracking multiple hypothetical vessel trajectories, low contrast passages can be traversed, leading to an improved tracking performance in areas of low contrast. This work also contributes a novel mathematical vessel template model, with which an accurate vessel centerline extraction is obtained. The tracking is fast enough for interactive segmentation and can be combined with other segmentation techniques to form robust hybrid methods. This is demonstrated by segmenting both the liver arteries in CT angiography data, which is known to pose great challenges, and the coronary arteries in 32 CT cardiac angiography data sets in the Rotterdam Coronary Artery Algorithm Evaluation Framework, for which ground-truth centerlines are available.
提出了一种用于分割小 3D 血管结构的多假设跟踪方法。通过同时跟踪多个假设的血管轨迹，可以穿越低对比度的通道，从而在低对比度区域提高跟踪性能。这项工作还提出了一种新的数学血管模板模型，通过该模型可以获得准确的血管中心线提取。跟踪速度足够快，可以进行交互式分割，并可以与其他分割技术结合形成稳健的混合方法。这通过在 CT 血管造影数据中分割肝脏动脉（已知具有很大挑战性）以及在 Rotterdam Coronary Artery Algorithm Evaluation Framework 中的 32 个 CT 心脏血管造影数据集的冠状动脉来证明，这些数据集都有可用的中心线。
