National Institute of Standards and Technology

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.

Cell Tracking Pipeline
Lineage Mapper processing pipeline and tracking outputs. The algorithmic steps consists of: (1) compute cost between cells from consecutive frames, (2) detect cell collision and account for it, (3) detect mitosis events, (4) assign tracks between cells, and (5) create tracking outputs. The outputs includes saved tracked images, the cell lineage plotting and 4 tracking output measurements: confidence index, the birth and death matrix, the mitosis matrix, and the fusion matrix.

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)

Lead Organizational Unit:

ITL

Staff:

ITL-Software and Systems Division
Information Systems Group
MML-Biosystems and Biomaterials Division
Cell Systems Science Group
University of Maryland, College Park
Fischell Department of Bioengineering

Publications:

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

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)

Software Downloads:

Source Code (Github)

Matlab MCR - This link will take you to the Matlab website and is required to run the Matlab executable if you do not have a Matlab license. It can be downloaded free of charge.

Matlab Executable
Fiji Plugin Jar
Fiji Plugin Update Site

Data Downloads:

Test Images

Help Documents:

Wiki
Matlab Help (download pdf)

Contact:

Peter Bajcsy
peter.bajcsy@nist.gov
Phone: 301.975.2958

Date created: April 10, 2014 | Last updated: