计算机科学
成像体模
分割
计算机视觉
冠状动脉
三维重建
运动(物理)
投影(关系代数)
基本事实
人工智能
一致性(知识库)
迭代重建
医学
算法
放射科
动脉
外科
作者
Christopher Rohkohl,Günter Lauritsch,Andreas Keil,Joachim Hornegger
标识
DOI:10.1088/0031-9155/55/10/008
摘要
The 3D reconstruction of cardiac vasculature, e.g. the coronary arteries, using C-arm CT (rotational angiography) is an active and challenging field of research. There are numerous publications on different reconstruction techniques. However, there is still a lack of comparability of achieved results for several reasons: foremost, datasets used in publications are not open to public and thus experiments are not reproducible by other researchers. Further, the results highly depend on the vasculature motion, i.e. cardiac and breathing motion patterns which are also not comparable across publications. We aim to close this gap by providing an open platform, called CAVAREV (CArdiac VAsculature Reconstruction EValuation). It features two simulated dynamic projection datasets based on the 4D XCAT phantom with contrasted coronary arteries which was derived from patient data. In the first dataset, the vasculature undergoes a continuous periodic motion. The second dataset contains aperiodic heart motion by including additional breathing motion. The geometry calibration and acquisition protocol were obtained from a real-world C-arm system. For qualitative evaluation of the reconstruction results, the correlation of the morphology is used. Two segmentation-based quality measures are introduced which allow us to assess the 3D and 4D reconstruction quality. They are based on the spatial overlap of the vasculature reconstruction with the ground truth. The measures enable a comprehensive analysis and comparison of reconstruction results independent from the utilized reconstruction algorithm. An online platform (www.cavarev.com) is provided where the datasets can be downloaded, researchers can manage and publish algorithm results and download a reference C++ and Matlab implementation.
科研通智能强力驱动
Strongly Powered by AbleSci AI