Lineage Mapper: Robust Cell Tracking System for Live Cell Image Analysis

Summary

We developed an open source, highly accurate, overlap-based cell tracking system that tracks live cells across a set of time-lapse images. The processing pipeline of the Lineage mapper is shown in Figure 1. The Lineage Mapper successfully detects dynamic single cell behavior: cell migration, changes in cell state (mitosis, apoptosis); cells within colonies or the entire colonies, cells within cell sheets or cells moving around with high cell-cell contact.

Description

The lineage mapper receives segmentation masks as input, and outputs a cell lineage tree and a set of labeled tracked masks where each cell is assigned with a unique global number. It has the capability to: 1) detect mitotic events by monitoring image descriptors, such as cell roundness and size of the mother cell and degree of similarity of daughter cell sizes and aspect ratios; 2) separate cells mistakenly segmented as a single cell when cell-to-cell contact occurs; 3) track cells using a method that is robust to input parameter selection, so it can be used with little training; 4) track cells independently of any segmentation method and with any masks generating by segmentation; and (5) track cells and colonies in real-time on terabyte-sized (TB) images.

Major Accomplishments

An open-source tool is made available for free download. This tool was developed in Matlab, for which the source code is available for download along with a compiled executable. This tool was converted into a Fiji plugin available either as a jar download or from a Fiji update site.

The paper: Joe Chalfoun et al., "Lineage mapper: A versatile cell and particle tracker" Scientific Reports, 2016 (pdf) (view article)

The paper: J. Chalfoun, A. Cardone, and A. Dima, “Overlap-based cell tracker,” J. Research Natl. Inst. Stand. Technol., vol. 115, no. 6, p. 477, Nov. 2010 (pdf) (view article)