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

机译:在评估有丝分裂时匹配作为细胞跟踪精度测量的非环状定向图的限制

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Multi-object tracking (MOT) in computer vision and cell tracking in biomedical image analysis arc 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.
机译:在生物医学图像分析中计算机视觉和单元追踪中的多对象跟踪(MOT)弧两个类似的研究领域,其共同目标是实现实例级别对象检测/分段,并将这些对象与不同的视频帧相关联。 然而,这两项任务之间的一个主要区别在于,细胞跟踪也旨在检测通常在MOT任务中不考虑的细胞源(细胞分裂)。 因此,匹配(AOGM)的无环定向图已被用作小区跟踪的事实标准评估度量,而不是直接使用计算机视觉中的评估度量,例如多个物体跟踪精度(MOTA)。 ID交换机(IDS),ID F1得分(IDF1)等,但是,根据我们的实验,我们意识到AOGM并不总是对有丝分裂事件的预期起作用。 在本文中,我们使用模拟和真实的小区跟踪数据表现出与AOGM评估有丝分裂的局限性。

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