Including Fiji/ImageJ2

ImageJ2 is an imgage manipulation program with focus on multidimensional image data for scientific purposes.

Fiji is a distribution of ImageJ, that bundles many plugins that can be used for scientific image analysis. It offers a range of functions that are useful in the application area of Segmensation, e.g. the calculation of directionality in Images.

To create a simple workflow, ImageJ2 (originally written in Java) has been included through PyImageJ, a package that allows the usage of ImageJ2 and Fiji in python. This package and its dependencies have already been added to the docker container of the backend and are ready to use.

Initializing ImageJ2/Fiji

To use ImageJ2 or Fiji-Plugins, the following steps are necessary:

  1. Initialize ImageJ:

ij = imagej.init('2.5.0 ') # only ImageJ

# OR:

ij = imagej.init('sc.fiji:fiji:2.5.0 ') # ImageJ and Fiji

  1. Import ImageJ and needed classes/plugins:

IJ = sj.jimport('ij.IJ')

ImagePlus = sj.jimport('ij.ImagePlus')
Directionality = sj.jimport('fiji.analyze.directionality.Directionality_')

  1. Initialize and use class/plugin (example):

directionality = Directionality()
directionality.setImagePlus(patch)
directionality.setMethod(AnalysisMethod.valueOf('LOCAL_GRADIENT_ORIENTATION'))
directionality.setBinNumber(91)
directionality.setBinStart(-90)
directionality.computeHistograms()

Note

All available classes can be looked up in Fiji’s official API Documentation.

Converting numpy arrays to ImagePlus

Images must be an instance of ImagePlus to be manipulated or analyzed by ImageJ. Numpy Arrays can be converted to ImagePlus with the following function:

imageplus = ij.py.to_imageplus(image_array)