Lineage Mapper User Guide

Table of Contents

Getting Started

This section describes how to install the Lineage Mapper plugin. Section Installing Fiji describes how to get Fiji. Section Lineage Mapper Plugin Installation describes how to add the plugin into Fiji. General help relating to Fiji and ImageJ can be found online.

  1. ImageJ http://rsbweb.nih.main.java.gov/ij/index.html
  2. Fiji http://fiji.sc/Fiji

Installing Fiji

To download Fiji go to http://fiji.sc/Downloads and follow their installation instructions for your platform.

Lineage Mapper Plugin Installation

See the wiki Install-Guide for instructions.

Launching LineageMapper

This section assumes you have already installed the plugin using the steps described in section Lineage Mapper Plugin Installation.

To launch the Lineage Mapper plugin:

  1. Open Fiji

  2. Menu item: Plugins >> Tracking >> LineageMapper

    Launching Tracking Plugin

  3. Lineage Mapper main window opens

    Lineage Mapper Main Window

Loading an Image Sequence into Fiji

The Cell Tracker expects a segmented labeled image sequence (an Image Stack within ImageJ http://rsbweb.nih.main.java.gov/ij/docs/guide/146-8.html). A labeled image is a segmented image where the regions of interest (ROI) are labeled from 1 to maximum number of objects per image. The ROI numbering does not need to reflect any organization. The labeled ROIs in the segmented images all consist of pixels that have the value of the ROI label. For example, every pixel in the ROI labeled 5 has a pixel value of 5. Background pixels have the value 0. If the input images after segmentation are binary and not labeled, the user can label the binary images using the following ImageJ/Fiji plugin: Connected_Components_Labeling available at: https://isg.nist.gov/deepzoomweb/resources/csmet/pages/cell_tracking/cell_tracking.html

Lineage Mapper does not automatically label the input images because that would undo any previous segmentation of touching ROIs.

The input to the cell tracker is a set of labeled segmented images where each Region of Interest (ROI) is assigned a unique number starting from 1 to the maximum number of ROIs in that image.

image

The image sequence can be loaded into Fiji in any number of ways. For a full listing see the documentation at:

-ImageJ http://rsbweb.nih.main.java.gov/ij/docs/guide/146-26.html and

-Fiji http://fiji.sc/Importing_Image_Files

Methods of loading an image sequence into Fiji:

  1. Drag and Drop a folder containing images onto the Fiji Window.

  2. Menu item: File >> Import >> Image Sequence

image

Installation Validation Test

In this section, we will walk through setting up running LineageMapper on the small test dataset in order to validate that the plugin is installed correctly.

  1. Download test images: LineageMapper_Test_Data.zip ~ 55 KB
  2. Extract LineageMapper_Test_Data.zip into a directory
  3. Launch LineageMapper plugin from Fiji
  4. Load the test sequence of segmented images into Fiji Loading Image Sequence
  5. Select Load Params and open '[extractionPath]/LineageMapper_Test_Data/tracking_parameters.txt'
  6. To avoid using Load Params
    1. Under Image Sequence to Track select the name of your sequence
    2. Select the Advanced tab
      1. Scroll to the bottom and press Load Default Parameters
  7. Select Output tab and de-select Save Outputs to Disk
  8. Click Track to launch

Lineage Mapper GUI

Main Window

Input Parameters

Input Tab

image

Output Parameters

Once the tracker has successfully completed a tracking session the tracking data collected during the session will be available here.

Output Tab

prefix - the prefix prepended to output files.

image

Example Metadata Windows

Advanced Parameters

Advanced Tab

Some possible scenarios for cell tracking: Problem 1 is our typical problem encountered in most cases, when cells change shape often and go into mitosis and image acquisition rate is high enough that there are good cellular overlaps between consecutive acquisitions. In general, the overlap weight should be proportional to the acquisition rate. Problems 2 and Problem 3 are considered to have low acquisition rates. In Problem 2 cells change shape but don’t move long distances and in Problem 3 like for particle tracking problems where objects don’t change shape and we have low image acquisition rate. A proposed weight combination to solve each of these problems is given in the table below. It is important to note that the cell tracker is very robust with regards to the weights. The three weights don’t need to be changed for solving similar problems like the ones displayed in the table below.

Cost Function Example