#3D Dot Detector Plugin for ImageJ
Kota Miura (miura@embl.de)
Please download and install Fiji.
Install jar file target/Dot_Detect3D-2.0.0.jar as a plugin for ImageJ / Fiji. This plugin analyzes a 3D image stack and lists dots in results table.
The command is located at
[Plugins > EMBLTools > Mayumi > Dot Detect 3D...]
Please download the MosaicSuit ImageJ plugin from the URL below and install it to your local ImageJ or Fiji:
http://mosaic.mpi-cbg.de/?q=downloads/imageJ
If you want to be always updated with changes, use the update site functionality and install "MOSAIC ToolSuite" using ImageJ updater.
http://fiji.sc/List_of_update_sites
Please read their conditions and terms, and if you use this tool in your paper, please also site the following paper.
I. F. Sbalzarini and P. Koumoutsakos.
Feature Point Tracking and Trajectory Analysis for Video Imaging in Cell Biology
Journal of Structural Biology 151(2):182-195, 2005.
Install the jar file to your local Maven repository by following command:
mvn install:install-file -Dfile=/PATH/TO/Mosaic_ToolSuite.jar -DgroupId=de.mpi-cbg.mosaic -DartifactId=mosaicSuit -Dversion=1.0.0 -Dpackaging=jar
Then compile Java files as usual.
mvn compile
##Usage
The plugin is executable from GUI, but major usage has been to use it from a Jython script.
For Mayumi's project following script was used.
src/main/scripts/Dot3Danalysis_2_MI.py
This script is runnable from the script editor in Fiji.
Description
The script uses three channels: hoechst (chromosome), kinetochore (CENPA, reference) and targeting proteins (target).
First, chromosome signal was segmented using a slight Gaussian blurring followed by Otsu threshold holding. This binary image was then used as a mask for reference channel to limit the detection of CENPA signal only from those located within chromosome boundary.
Spotty CENPA signals were detected using 3D-DotDetector plugin (this plugin) and their 3D coordinates were listed. As the measurement of intensity will be done in a small circle centered at each CENPA spots with a defined radius (we set this to 15 pixels, approximately 1 micrometer), we rejected CENPA spots that are too close to each other (spot-spot distance < 15 pixels). After this filtering of spots, we measured intensities for CENPA channel and targeting protein channel.
This plugin uses FeaturePoint detection library from MosaicSuit plugin developed by Mosaic group (Ivo Sbalzarini, CBG-MPI, Dresden). We thank their great implementation and offering them as an open source library!