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Multi-object tracking (MOT) in computer vision and cell tracking inbiomedical image analysis are two similar research fields, whose common aim isto achieve instance level object detection/segmentation and associate suchobjects across different video frames. However, one major difference betweenthese two tasks is that cell tracking also aim to detect mitosis (celldivision), which is typically not considered in MOT tasks. Therefore, theacyclic oriented graphs matching (AOGM) has been used as de facto standardevaluation metrics for cell tracking, rather than directly using the evaluationmetrics 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 usingboth simulated and real cell tracking data.

Limitation of Acyclic Oriented Graphs Matching as Cell Tracking Accuracy Measure when Evaluating Mitosis