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Image Processing with ImageJ - Second Edition
Image Processing with ImageJ - Second Edition

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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Profile Icon Jurjen Broeke Profile Icon Pascau
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.4 (5 Ratings)
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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.4 (5 Ratings)
eBook Nov 2015 256 pages 1st Edition
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Image Processing with ImageJ - Second Edition

Chapter 1. Getting Started with ImageJ

Welcome to the second edition of Image Processing with ImageJ. ImageJ is a versatile and open source software package designed for scientific image processing and analysis. It is written in the Java programming language, allowing for a uniform cross-platform experience. It is based on the NIH Image software package on the Macintosh platform, developed in 1987 by Wayne Rasband. Rasband, who is still an active contributor of ImageJ, published the first ImageJ distribution in 1997. It was developed as a project to provide a solution to a problem. In 2012, ImageJ celebrated its twenty-fifth birthday with a publication in the journal Nature Methods.

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.

The uses of ImageJ

ImageJ is a great tool to process images and perform analysis. It is used in many scientific peer-reviewed publications, with over 1000 articles in diverse fields such as life sciences, astronomy, and physics. In life sciences, it is used to quantify medical images to aid in the detection of pathological markers. It is also used to process and quantify data from single-cell or single-molecule experiments using super-resolution techniques such as STORM and PALM. In physics and engineering, it is used to quantify and visualize data obtained from atomic force microscopy. For astronomy, ImageJ is used to analyze images obtained from telescopes and satellites and visualize data obtained from observatories. NASA's Jet Propulsion Laboratory hosts a central node with a good collection of data that is available for download at http://pds.jpl.nasa.gov/. It contains information on the planetary missions as well as other research fields such as atmospheres or asteroids.

As it supports a large number of different image formats, it is a great image viewer and allows a great number of pixel-based operations. It also supports images with bit depths greater than 8 or 16 bits per channel. However, it is not meant for anything other than pixel-based operations. If you wish to use vector-based operations, then ImageJ is not the tool for you (unless you wish to develop this functionality).

Besides the common tools for image processing, such as cropping, rotating, and scaling, it supports images with multiple dimensions. Images with up to five dimensions can be processed and saved. These dimensions can include channels (multiple colors), frames (time points), and slices (Z planes), and any combination of these dimensions. Currently, multipoint acquisitions are not supported (different locations in a larger XY space). It is also possible to change the intensity of pixels displayed by adjusting the brightness and contrast, or the color-coding of the pixels (Lookup Tables). More advanced techniques to correct image acquisition artifacts, such as background and bleaching, are also available.

The default image format of ImageJ is the Tagged Image File Format (TIFF). This format allows for the storage of multidimensional data and supports many meta-information fields for calibration, data acquisition information, and descriptions. It can also store information about elements such as overlays. Graphical annotations are placed on the image in a separate layer. Measurements will benefit from the calibration included in the image, allowing for a fast feedback of sizes in the appropriate unit. It is, however, less suited for different kinds of mixed data such as video files. Using the FFMPEG plugin allows you to open and save the image data of a video but not the audio track(s). Also, editing is limited to a small set of transitions and layering techniques. For editing videos with image and sound, non-linear editors are available. They allow for greater control.

It can also be used as an image-conversion tool. Many image formats can be read natively by ImageJ, and with the help of a plugin, many proprietary formats can be opened. Once the image is opened, it can be saved to any of the supported export formats supported by ImageJ, including, but not limited to TIF, JPG, and PNG for images and AVI and MOV for time series and Z-stacks. It can also be used to change the order and/or color of images exported by other software. It is, however, not meant as a general photo editor or nonlinear video editor, as it lacks some of the specialized tools required for these workflows.

The current state of ImageJ

Currently, ImageJ has been cited in more than 200 publications since the beginning of 2015, in fields ranging from physics and engineering to medicine and biology. Many publications are about newly developed plugins that were specifically developed to solve a problem within a certain subfield of science. On the ImageJ website, the page that lists plugins has more than 1000 plugins available. A few research institutes even have collections of multiple plugins available that were developed there as research projects. Most, if not all, are open source plugins with the full source code available. You can adjust and customize the code to suit your needs.

ImageJ2

ImageJ is still under active development, and new features and bug fixes are added to the core distribution on a regular basis. Currently, the development of a revised system for ImageJ is being developed. It is called ImageJ2. The goals of ImageJ2 are to better support multidimensional data as well as create a more extensible platform that can be used as a library instead of a standalone application. It will also create a more consistent environment for development and extension. One of the features being developed is the updating mechanism for ImageJ. Currently, it is possible to update ImageJ automatically using a central repository, and one of the goals of ImageJ2 is to expand this option to plugins and other features and allow tracking of bugs and features. However, one of the core requirements in the new ImageJ2 system is backward compatibility. This goal means that plugins developed now will stay functional in future releases of ImageJ. The current status is indicated as beta, which means the plugin is functional but may still contain bugs and is not optimized for performance yet.

SciFIO and OME-XML

Other developments related to image are those related to image formats and standards. Currently, all major commercial acquisition platforms store image data in unique proprietary file formats. The SCIFIO project is aimed at creating an extensible and integrated interface to handle images of different formats. It will support more image formats and allow for additional options to be set when importing the data, such as autoscaling, loading metadata, and loading the data in different ImageJ image types. However, it is still under active development, and some of the features do not quite work in a production environment (yet).

The OME-XML (Open Microscopy Environment-XML) project is aimed at creating a file format that contains all the image and metadata in a standardized format. This would facilitate the exchange of microscope image data, regardless of the equipment used for acquisition. It is mainly focused on the exchange of microscopy data in the field of life sciences. It contains all the experimental and setup data as well as the pixel data in a single file specification.

Bio-formats

Besides the OME-XML format, which is focused on integrating acquisition and processing across multiple acquisition platforms, there is also active development of the plugin used to import many image formats currently in existence. This plugin, called Bio-Formats, is mostly focused on image formats from the life sciences. However, it also supports FITS data, which is used in the field of astronomy and space exploration. It currently supports (to different degrees) 140 different image formats and converts them to the OME-XML format for use in ImageJ.

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Key benefits

  • Design automated image-processing solutions and speed up image-processing tasks with ImageJ
  • Create quality and intuitive interfaces for image processing by developing a basic framework for ImageJ plugins.
  • Tackle even the most sophisticated datasets and complex images

Description

Advances in image processing have been vital for the scientific and technological communities, making it possible to analyze images in greater detail than ever before. But as images become larger and more complex, advanced processing techniques are required. ImageJ is built for the modern challenges of image processing – it’s one of the key tools in its development, letting you automate basic tasks so you can focus on sophisticated, in depth analysis. This book demonstrates how to put ImageJ into practice. It outlines its key features and demonstrates how to create your own image processing applications using macros and ImageJ plugins. Once you’ve got to grips with the basics of ImageJ, you’ll then discover how to build a number of different image processing solutions. From simple tasks to advanced and automated image processing, you’ll gain confidence with this innovative and powerful tool – however and whatever you are using it for.

Who is this book for?

The book has been created for engineers, scientists, and developers eager to tackle image processing with one of the leading tools available. No prior knowledge of ImageJ is needed. Familiarity with Java programming will be required for readers to code their own routines using ImageJ.

What you will learn

  • Install and set up ImageJ for image processing.
  • Process images using ImageJ's built-in tools
  • Create macros to perform repetitive processing tasks
  • Set up and use an integrated development environment for ImageJ plugins
  • Create plugins with a user-friendly interface for processing
  • Use established ImageJ plugins for processing and quantification
  • Generate a simple interface based on a real world example and create other interfaces for other projects
  • Speed up interface development by setting multiple parameters interactively

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Publication date : Nov 30, 2015
Length: 256 pages
Edition : 1st
Language : English
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Publication date : Nov 30, 2015
Length: 256 pages
Edition : 1st
Language : English
ISBN-13 : 9781785881589
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Tools :

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Table of Contents

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

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.4
(5 Ratings)
5 star 40%
4 star 20%
3 star 0%
2 star 20%
1 star 20%
Bruce Comber Jul 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
it answered specific questions that I ahd
Feefo Verified review Feefo
Marcos de A. Souza Sep 27, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is excelent to beginners with me. I lik'd!!!
Amazon Verified review Amazon
D. J. Stupple Feb 17, 2016
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Four stars, because the book is very informative on ImageJ and basic principles of image processing (I am up to page 55, so far). It is let down by the images being all in greyscale, while the captions repeatedly refer to colour features in the images. One image so far appears to be not printed at all.Some of the images for the processes described do not seem to be available from the Packt website(I will edit if this changes), but the samples provided by ImageJ are so far all available. Useful book, poor publishing and support.
Amazon Verified review Amazon
JB1650 Jun 07, 2019
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
Somebody needs to write a tutorial book on ImageJ. These authors tried, but this is not a good book. Seriously - black and white photos are used to explain color gamut. Where was the editor? The book has the feeling of being thin, especially for $40. I don't know what else to recommend - there are some PDF tutorials up on the web, perhaps those would be better.
Amazon Verified review Amazon
Marcia F. Stornetta Sep 30, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Either the publisher has a cruel sense of humor, or I was shipped a defective copy. All of the images are grayscale in this book, which seems like a significant oversight given 1) the nature of the subject matter and 2) that the authors make explicit mention to the colors in sample images multiple times.Perhaps the most egregious example of this mismatch is an image on page 81, with the following description on page 82: "The shapes with a circularity of 1.00 are colored orange (ellipse) and light green (oval). The red ellipse has a very low circularity (0.28), while the cyan oval has an intermediate circularity (0.48)." To reiterate, the image in question is in grayscale.Adding insult to injury, the images are of a uniformly poor quality. This is highlighted on page 23, where the authors compare a photo of Lenna that they attempt to deliberately reduce in quality by repeated JPEG compressions. However, the photos are indistinguishable! This is something that the authors or editor should have noticed.Concerning the didactic content of the book, it tries to strike a nice balance between material for the absolute beginner (chapters 1-5), intermediate users (chapter 6), and advanced users/developers (chapter 7-9). But, depth is definitely not its strong suit.Were the book not plagued by image quality issues, it would be easier to view this as just a mediocre book (2 stars), but given these reasons, it is impossible to rate anything but 1 star.Attached are the two images referenced from the book.
Amazon Verified review Amazon
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