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Image Processing with ImageJ - Second Edition

You're reading from   Image Processing with ImageJ - Second Edition Extract and analyze data from complex images with ImageJ, the world's leading image processing tool

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781785889837
Length 256 pages
Edition 1st Edition
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with ImageJ FREE CHAPTER 2. Basic Image Processing with ImageJ 3. Advanced Image Processing with ImageJ 4. Image Segmentation and Feature Extraction with ImageJ 5. Basic Measurements with ImageJ 6. Developing Macros in ImageJ 7. Explanation of ImageJ Constructs 8. Anatomy of ImageJ Plugins 9. Creating ImageJ Plugins for Analysis 10. Where to Go from Here? Index

ImageJ distributions

Currently, there are different distributions that are based on or are extensions of the original ImageJ. The basic ImageJ package is available on the ImageJ website at the National Institute of Health (http://imagej.nih.gov/ij/download.html). The current version of the package is version 1.50b, and the website is updated monthly. This is the core distribution of ImageJ, which contains the main interface and all the basic tools to load, view, process, and export images and data. Other distributions contain this core package and most of its features, but you need to add additional features and plugins to create an optimized interface for specific fields. Some of these other distributions are still easily recognizable as ImageJ, while others offer a completely different interface.

For different scientific fields, different distributions were developed based on the core of ImageJ. One of the major distributions for the life sciences is called Fiji (Fiji Is Just ImageJ), which can be found on the Fiji website (http://fiji.sc/Fiji). The basis of Fiji is ImageJ, but it comes with a large complement of preinstalled features (macros and plugins) that are commonly used for image processing in the life sciences. It is focused on fluorescence microscopy, with built-in tools for segmentation, visualization, and co-localization. It also contains plugins for image registration, particle tracking, and super-resolution processing and reconstruction. It also has an extensive library of image formats that can be opened. This library includes proprietary image formats from all the major acquisition software packages via the Bio-Formats plugin, as described in the upcoming section. The advantages of this distribution are the large number of supplied plugins that come with it as well as a very user-friendly script editor. It also has an extensive update mechanism for both ImageJ as well as some plugins.

For the field of astronomy, a different distribution of ImageJ was developed, named AstroImageJ (http://www.astro.louisville.edu/software/astroimagej/). This distribution takes the core implementation of ImageJ and supplements it with specific plugins and macros developed for analysis in the field of astronomy. It is not directly compatible with ImageJ. The core of ImageJ was slightly modified for this distribution.

An example of a distribution derived from ImageJ but with a different user interface is Icy (http://icy.bioimageanalysis.org/). The Icy distribution has integrated ImageJ, and many plugins are compatible. However, not every plugin developed for ImageJ will work within Icy and vice versa. In the Icy distribution, there is a strong emphasis on cellular and spot detection and tracking. There is also a strong emphasis on plugin development. Plugins that are developed for the Icy platform will have documentation and automated updating implemented by design. There are also possibilities for users to directly provide feedback to the developers from within the interface, which is a feature not present within other distributions based on ImageJ. A disadvantage may be that it requires several external libraries to be installed, most importantly VTK, which can cause issues on Linux systems.

Another distribution that uses ImageJ not only for the processing of data but also aids in the acquisition of data is called μManager, which can be found at https://www.micro-manager.org/. It is loaded from within ImageJ as a plugin, but provides a unique interface geared towards image acquisition and hardware control. Camera and microscope drivers allow the control of supported hardware used in image acquisition, which can then be fed directly to ImageJ for processing and analysis. An example of the use of μManager is in the Open SPIM project, where it is used to control a DIY light sheet microscope, acquire images, and process them.

You have been reading a chapter from
Image Processing with ImageJ - Second Edition
Published in: Nov 2015
Publisher:
ISBN-13: 9781785889837
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