3D-Imaging analysis and modelling
Image processing platform
ImageJ has been selected because it is a public domain, user friendly and extensible platform for 2D as well as for 3D image processing and analysis. It is designed by using an open architecture and provides extensibility via Java plugins. The source is freely available from http://imagej.nih.gov/ij/. It is designed and maintained by Wayne S. Rasband from the U.S. National Institutes of Health, Bethesda, Maryland, USA.
Its programming language is Java. Java is a free high level language using the concept of a virtual processor. Hence, it enables high portability on all operating systems supporting the java runtime engine, at least on all UNIX, MacIntosh and Microsoft operating systems.
Since ImageJ is being widely used, a respectable bunch of plugins is already available on the net. The smartly designed open architecture of ImageJ is inviting for further extensions.
Inhouse software development for ImageJ
A set of prospective ImageJ plugins is maintained by the group for 3D-Microscopy, Analysis and Modelling of the Laboratory for Concrete and Construction Chemistry at Empa. The plugins include automated imaging tools for filtering, data reconstruction, quantitative data evaluation and data import, as well tools for interactive segmentation, visualization and management of image data.
Since the research focus of our group is on 3D imaging, all of our plugins are able to deal with either 2D or 3D image data. 3D image data in ImageJ is represented by image stacks. 3D processing may include slice-wise 2D processing of all images in the stack or, more important, true 3D processing.
Each one of the new plugins includes a help button where general remarks about the functionality and a description of the parameters are provided. This feature does not correspond with the ImageJ philosophy assuming the help documentation to be available on the internet. However, we consider the help button as a handy feature.
The user might be surprised to realize that some of the tools apparently are already existing in other plugins of ImageJ or Fiji. Those tools are for instance “FFT”, “Image Calculator”, “Distance Transform” and others. The reason for this apparent re-duplication is that the original tools incorporate major restrictions which are eliminated in the newplugins. Each one of the available tools and its advantage is shortly being presented below.
Conditions for free usage and download
The ImageJ plugins are included into the library file "xlib_.jar". They can be freely visualized and downloaded from the official Wiki of ImageJ at http://wiki.imagej.net/Xlib which is also containing a comprehensive description of all plugins included to the library, or from the Empa ftp server at
(use an Explorer (not the Internet Explorer), enter the address and log in by giving "anonymous" as the user name and type your email address for the password.) For adding the library to ImageJ, please follow the instructions in the "ReadMe.txt" file. The new plugins can then be found under Plugins Beat.
The plugins are provided „as is“ with no further support guaranteed; any liability for loss of data or any other damage arising from its use is disclaimed. The use of the offered plugins is free, provided that they are neither integrated into commercial products nor used for any other kind of profit. If the software is being used for research, Empa as owner of the Software is mandatory to be mentioned in the acknowledgements, and for citing the respective papers indicated in the help text.
Plugins of this section offer importing, handling or analysis of special data formats that are unknown to ImageJ, but interesting for usage.
The filtering functions accept one or more images or stacks of images where some filtering technique are applied to. Generally, the filtering functions work on 2D images, slice-wise 2D, as well as in true 3D mode if it is applied to image stacks.
Plugins of this section support preprocessing and reconstruction of images from projection data for CT imaging.
Another category of methods in this section is the estimation of 3D data from 2D images with the idea of estimating parameters requesting 3D connectivity from 2D slices only.
The plugins of this section achieve quantitative evaluation on image values and structures. This is an important topic in image processing in different scientific fields. A result from quantitative evaluation is not an image as it is from filtering, but rather a number representing some structural characteristics.
Editors and Viewers
This section contains plugins that are designed for user-interactive visualization and data processing on 2D slices and 3D volumes. They therefore don't just support a unique interaction on some image data, but they provide engines supporting an interactive dialog between the computer and the user.
- Inhouse Software Development (pdf)
Beat Münch, Lukas H.J. Martin, Andreas Leemann
Segmentation of elemental EDS maps by means of multiple clustering combined with phase identification. Journal of Microscopy, Volume 260, Issue 3, pages 411–426, December 2015