In the Heit lab we utilise a large range of quantitative image analysis techniques, using a variety of image processing programs. These techniques are used to extract information on protein interactions, cell morphology, cell signalling pathway activity, cell behaviours, and many other aspects of cell activity. Not only do we utilise these tools, but we also develop new tools which we share with the research community – tools such as microscopy-based quantitative efferocytosis assays, and software for analysing super-resolution images.
There are many excellent tools out there for image analysis – the two most heavily used in the Heit lab are the free program ImageJ, as well as the ImageJ variant FIJI. ImageJ is a free and open-source image processing software program that will run in nearly any operating system, and whose capacity is easily expandable through a large library of plugins (programmers can also develop their own plugins). FIJI is a variant of ImageJ which has a number of very useful plugins pre-installed, and which has been extensively documented at the FIJI wiki. Help for both software packages can be found on the ImageJ forums.
But as useful as these packages are, the major factor limiting their broader acceptance by the research community is the difficulty in using the software. ImageJ/FIJI is intuitive for users already experienced in image analysis, but has a very steep learning curve for individuals new to the image processing scene. The huge number of plugins and tools available in these software packages, combined with documentation that often assumes a high degree of imaging expertise, makes these software packages hard for new users to approach.
Over this weekend I cam across two resources which close this gap. Both are free e-textbooks intended to introduce the new (or experienced) image analysis user to various software resources and techniques. The first of these books – Analyzing fluorescence microscopy images with ImageJ is a detailed guide to using ImageJ for image analysis. The book starts with the basics – what are pixels, image file formats, etc, and guides the user through the most common forms of image analysis, all in the ImageJ environment. The second book is Bioimage Data Analysis, also a free book, but registration is required. This book covers ImageJ as well as a range of other free and commercial image analysis packages, and includes some sample protocols for more advanced image analysis routines. Of particular note, this second text includes an extensive chapter on writing ImageJ macros, a “super-user” method can can largely automate many image analysis tasks.
These books have become a new part of my labs standard training materials, and I encourage anyone interested in – or even experts in – image analysis to download and read these excellent resources.
Bankhead, Peter. Analyzing fluorescence microscopy images with ImageJ. https://www.gitbook.com/book/petebankhead/imagej-intro/details
Miura, Kota (editor). Bioimage Data Analysis. http://www.imaging-git.com/applications/bioimage-data-analysis-0