Trajectory energy minimization for cell growth tracking and genealogy analysis.

ABSTRACT: Cell growth experiments with a microfluidic device produce large-scale time-lapse image data, which contain important information on cell growth and patterns in their genealogy. To extract such information, we propose a scheme to segment and track bacterial cells automatically. In contrast with most published approaches, which often split segmentation and tracking into two independent procedures, we focus on designing an algorithm that describes cell properties evolving between consecutive frames by feeding segmentation and tracking results from one frame to the next one. The cell boundaries are extracted by minimizing the distance regularized level set evolution (DRLSE) model. Each individual cell was identified and tracked by identifying cell septum and membrane as well as developing a t

SUBMITTER: Hu Y 

PROVIDER: S-EPMC5451832 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature