  Multi-object tracking (MOT) in computer vision and cell tracking in
biomedical image analysis are two similar research fields, whose common aim is
to achieve instance level object detection/segmentation and associate such
objects across different video frames. However, one major difference between
these two tasks is that cell tracking also aim to detect mitosis (cell
division), which is typically not considered in MOT tasks. Therefore, the
acyclic oriented graphs matching (AOGM) has been used as de facto standard
evaluation metrics for cell tracking, rather than directly using the evaluation
metrics in computer vision, such as multiple object tracking accuracy (MOTA),
ID Switches (IDS), ID F1 Score (IDF1) etc. However, based on our experiments,
we realized that AOGM did not always function as expected for mitosis events.
In this paper, we exhibit the limitations of evaluating mitosis with AOGM using
both simulated and real cell tracking data.
