Knowledge-Based Vision Systems, Software Competence Center Hagenberg GmbH, Softwarepark 21, Hagenberg 4232, Austria.
Institut für Allgemeine Pathologie und Pathologische Anatomie, Technische Universität München, Germany.
Med Image Anal. 2016 Jan;27:72-83. doi: 10.1016/j.media.2015.03.007. Epub 2015 Apr 29.
In this paper we address the problem of recovering spatio-temporal trajectories of cancer cells in phase contrast video-microscopy where the user provides the paths on which the cells are moving. The paths are purely spatial, without temporal information. To recover the temporal information associated to a given path we propose an approach based on automatic cell detection and on a graph-based shortest path search. The nodes in the graph consist of the projections of the cell detections onto the geometrical cell path. The edges relate nodes which correspond to different frames of the sequence and potentially to the same cell and trajectory. In this directed graph we search for the shortest path and use it to define a temporal parametrization of the corresponding geometrical cell path. An evaluation based on 286 paths of 7 phase contrast microscopy videos shows that our algorithm allows to recover 92% of trajectory points with respect to the associated ground truth. We compare our method with a state-of-the-art algorithm for semi-automated cell tracking in phase contrast microscopy which requires interactively placed starting points for the cells to track. The comparison shows that supporting geometrical paths in combination with our algorithm allow us to obtain more reliable cell trajectories.
在本文中，我们解决了在相差显微镜视频中恢复癌细胞时空轨迹的问题，其中用户提供细胞移动的路径。这些路径是纯粹的空间路径，没有时间信息。为了恢复与给定路径相关的时间信息，我们提出了一种基于自动细胞检测和基于图的最短路径搜索的方法。图中的节点由细胞检测到的细胞路径的投影组成。边缘将对应于序列中不同帧的节点与同一细胞和轨迹相关联。在这个有向图中，我们搜索最短路径，并使用它来定义相应的几何细胞路径的时间参数化。基于 7 个相差显微镜视频的 286 条路径的评估表明，我们的算法可以恢复 92%的轨迹点，而与相关的真实轨迹相比。我们将我们的方法与一种用于相差显微镜半自动细胞跟踪的最先进算法进行了比较，该算法需要交互式放置要跟踪的细胞的起始点。比较表明，支持几何路径结合我们的算法可以使我们获得更可靠的细胞轨迹。
