论文标题
MPM：单元跟踪的运动和位置图的联合表示
MPM: Joint Representation of Motion and Position Map for Cell Tracking
论文作者
论文摘要
常规细胞跟踪方法在每个帧中检测多个单元格（检测），然后将检测关联导致连续的时间框架（关联）。大多数单元跟踪方法可以独立于检测任务执行关联任务。但是，不能保证在这些任务之间保持连贯性，并且缺乏连贯性可能会对跟踪性能产生不利影响。在本文中，我们提出的运动和位置图（MPM）共同代表了不仅迁移，而且代表细胞分裂的检测和关联。它保证了连贯性，以便如果检测到单元格，可以始终获得相应的运动流。这是一种简单但功能强大的方法，用于在密集环境中进行多目标跟踪。我们将提出的方法与当前在实际生物学图像中的各种条件下的当前跟踪方法进行了比较，发现它的表现优于最先进的方法（与第二好的相比，+5.2 \％改进）。
Conventional cell tracking methods detect multiple cells in each frame (detection) and then associate the detection results in successive time-frames (association). Most cell tracking methods perform the association task independently from the detection task. However, there is no guarantee of preserving coherence between these tasks, and lack of coherence may adversely affect tracking performance. In this paper, we propose the Motion and Position Map (MPM) that jointly represents both detection and association for not only migration but also cell division. It guarantees coherence such that if a cell is detected, the corresponding motion flow can always be obtained. It is a simple but powerful method for multi-object tracking in dense environments. We compared the proposed method with current tracking methods under various conditions in real biological images and found that it outperformed the state-of-the-art (+5.2\% improvement compared to the second-best).
