Optic Flow Providing External Force for Active Contours in Visually Tracking Dense Cell Population

Shan Yu, D. Molloy
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引用次数: 0

Abstract

Intense current research requires quantitative analysis of cell behaviours in dense cell populations. The low contrast cellular image quality, diversity of cell shapes, frequent cell interactions, and complex cell motions all pose significant problems to the efficient and robust cell tracking in phase contrast cellular images. We have proposed an automated cell tracking system based on active contours for tracking cell deformation and movement. The pyramidal optic flow scheme is exploited for providing external motion force to guide active contour evolution, and thus helps to address the particular difficulty in tracking relatively fast moving cells in dense cell population. We have evaluated the proposed framework on one real cellular dataset and proved an 80.2% tracking accuracy.
密集细胞群视觉跟踪中为活动轮廓提供外力的光流
当前激烈的研究需要对密集细胞群中的细胞行为进行定量分析。细胞图像对比度低、细胞形状多样、细胞相互作用频繁、细胞运动复杂,这些都给细胞相衬图像的高效鲁棒跟踪带来了很大的问题。我们提出了一种基于活动轮廓的自动细胞跟踪系统,用于跟踪细胞的变形和运动。利用锥体光流方案提供外部运动力来引导主动轮廓演化,从而有助于解决在密集细胞群中跟踪相对快速运动细胞的特殊困难。我们已经在一个真实的细胞数据集上评估了所提出的框架,并证明了80.2%的跟踪精度。
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