Free and open source

[no download link, this description itself explains the steps to quantify staining in tissue sections] The Color Deconvolution plugin for ImageJ can be used to digitally separate up to three stains from brightfield images, after which standard ImageJ commands can be used. The algorithm is described in Ruifork and Johnston (2001). **However**, it is **very** important to take into consideration the caveats on the linked URL. In particular, note that: - Stain colors depend on numerous factors, such as the precise stains and scanner; therefore, the 'default' stain vectors (used to define the colors) are unlikely to be optimal and may be very inaccurate. See the URL instructions for how to create new stain vectors. - Pixel values should be interpreted with extreme caution; in particular, note the warning regarding 'brown' staining that *attempting to quantify DAB intensity using this plugin is not a good idea*. Note, the pixel values provided by this plugin are 8-bit and **not** equivalent to 'optical densities' frequently presented in the literature. Color deconvolution is particularly helpful in separating stains so that stained regions can be detected (e.g. by setting a threshold), and then the number or areas of stained structures may be quantified. Two potential approaches would be: 1. If one measurement should be made for the entire image: - *Image > Adjust > Threshold...* - *Edit > Selection > Create Selection* - *Analyze > Measure* 2. If distinct structures should be measured: - *Image > Adjust > Threshold...* - *Analyze > Analyze Particles...*

This macro segments blood vessels in a 3D stack. It is suited for well-contrasted images (low background) and works better if the width of the vessels of interest is reasonably uniform.

Sample image: 1

sample image: 2

Autofocus hyperstack macro:

Select the in focus frame from each slice of a hyperstack and create a new stack of just the in focus frames. Based on algorithm F-11 "Normalized Variance".

Original macro by Andy Weller.

Generation of Kymographs using 2D+t images. In the generated kymographs, objects can be tracked and the results are visualized.

This macro performs measurements of average and standard deviation intensity inside wells of a protein microarray (the number of wells is limited to 250, the image should be cropped for larger arrays). The macro requires the "ImageJ plugins toolkit". To ensure compatibility with Fiji you should download the version 1.6.1. The installation instructions can be found here, it only consists in un-compressing the .jar file from the previous archive to Fiji plugins folder.

sample image: link