Cell Lineage Tracking Based on Labeled Random Finite Set Filtering

B. Wei, Lin Zhou
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引用次数: 1

Abstract

One fundamental interest of developmental biology is to resolve lineage relationships between cells. This paper proposes a cell lineage tracking algorithm based on labeled Random Finite Set (RFS) filtering. δ-Generalized Labeled Multi-Bernoulli (δ-GLMB) filter is used for cell state estimation. New cells are captured by a measurement-based birth model. In order to capture spawned cells and lineage, a new δ-GLMB filter which incorporates spawning in addition to new births is proposed. Information regarding spawned cell's lineage is provided by an algorithm which can weigh the distance between new cells and old cells. The new filter can achieve joint estimation of new cell's state and information of its lineage. The efficacy of the proposed method is demonstrated by simulations.
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基于标记随机有限集滤波的细胞谱系跟踪
发育生物学的一个基本兴趣是解决细胞之间的谱系关系。提出了一种基于标记随机有限集(RFS)滤波的细胞谱系跟踪算法。δ-广义标记多伯努利(δ-GLMB)滤波器用于细胞状态估计。新的细胞被一个基于测量的出生模型捕获。为了捕获产卵细胞和谱系,提出了一种新的δ-GLMB滤波器,该滤波器除了包含新生细胞外还包含产卵细胞。生成细胞的谱系信息由一种算法提供,该算法可以衡量新细胞和旧细胞之间的距离。该滤波器可以实现对新细胞状态及其谱系信息的联合估计。仿真结果验证了该方法的有效性。
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