Cell Lineage Tracking Based on Labeled Random Finite Set Filtering
Baishen Wei, Lin Zhou · 2018
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.