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Bigdataviewer Scijava

As announced in the forum here and here, this repository aims at a better integration of BigDataViewer into FIJI by using the Scijava Framework.

Installation

Enable the update site (https://biop.epfl.ch/Fiji-Update-Bdv/) to activate bigdataviewer_scijava commands. All commands from this update site are present in the github repository bigdataviewer_scijava. A list of all commands can be found in the repository.

Goals

  • Modularity for bigdataviewer! Being able to combine scripts or code for display and processing. This update site creates a way to access an existing BDV instance when scripting or writing java code.
  • Provide a set of macro recordable commands for bigdataviewer. Makes it possible to script basic actions on BigDataViewer with the IJ1 recorder.

What you can do with this update site

By using Scijava framework to store BigDataViewer windows through its BdvHandle interface, it is possible to communicate bdv instances between scripts and commands (see script parameter page). This also facilitates the use of FIJI GUI because the commands of this repository can be chained easily. Any script or Command which declares a BdvHandle parameter can retrieve or provide reference to existing BigDataViewer instances.

In practice, Bdv windows created via the commands from this update site are put by default in the ObjectService. To get a reference to these windows:

  • In groovy, add this at the beginning of your script
#@bdv.util.BdvHandle bdvh
  • In Java:
@Parameter
BdvHandle bdvh;

How to make your bigdataviewer workflow compatible with Scijava

Two options:

  • Use the command BdvWindowCreate from this repository and retrieve its reference through SciJava parameter annotation. This will make your Bdv Window accessible to other plugins / commands.
  • Create your own Bdv window, but declare the associated BdvHandle as an output of your Command:
    • in Java: @Parameter(type = ItemIO.OUTPUT); BdvHandle bdvh_out;

The type of the parameter annotation can also be ItemIO.BOTH if your command is modifying an existing BdvHandle

Secondary Goals

This repo provide an implementation of all the command from the repository bigdataviewer_fiji to make it scijava compatible, so it should have the same commands.

  • Because complex bdv dataset (metadata, multiple views, channels...) are usually organized into SpimData objects, this update site / repository also provide tools to manipulate these objects, in a scijava compatible manner. Hence declaring in groovy #@mpicbg.spim.data.generic.AbstractSpimData sd or in java @Parameter AbstractSpimData asd; allows to manipulate and communicate such objects.
  • Easy visualization of the bdv sources present in a Bdv Window (-> access to display options). Right clicking on selected source also enables to access basic display operations.
  • Easy edition with "standard actions" on bdv sources held within a Bdv Handle:
    • transform
    • registration
    • export
    • import

Examples

Video

1 - Simple

https://www.youtube.com/watch?v=-q5qIdH9Idw (1 minute)

  • Open a sample image.
  • Change display settings.
  • Double clicking on the source in the bdv window translate the window to the origin of the source

2 - IJ Script example

https://youtu.be/IjIW5bOn4P8 (3 minutes)

  • Create Bdv Window
  • Start IJ1 recorder
  • Open a voronoi image
  • Create an affine transform
  • Transform source with affine transform
  • Make a loop and execute it
  • Modify display settings

3 - Procedural + Warping + Export (xml hdf5 and ImagePlus)

https://youtu.be/uOYWn7tUsf0 (7 minutes)

  • Open a procedural image ( mandelbrot )
  • Create new Bdv Window
  • Open voronoi in this new window
  • Warp one into another using BigWarp
  • Create a new bdv window
  • Transfer initial Voronoi Image into this window
  • Transfer transformed fractal into this window
  • Resample transformed Mandelbrot like Voronoi
  • Save initial voronoi and transformed resampled mandelbrot into a new dataset
  • Close everything
  • Reopen saved dataset
  • Apply correct display settings

Resampling is necessary because XML/Hdf5 do not allow to save procedural images.

Scripts

Groovy

Run both scripts consecutively:

  • Display a recursive FIJI image:
import bdv.util.Procedural3DImageShort
import net.imglib2.RealRandomAccessible
import bdv.util.BdvFunctions
import bdv.util.BdvOptions
import bdv.util.BdvHandle
import net.imglib2.type.numeric.integer.UnsignedShortType
import net.imglib2.FinalInterval
import net.imglib2.Interval
import net.imglib2.type.numeric.ARGBType
// Input : provided by Single Input Preprocessor in case no widow is present
#@bdv.util.BdvHandle bdv_h 
// Output : allow to updates list of sources
#@output bdv.util.BdvHandle bdv_h 

// Simple FIJI Image stored as an array
fijiData =
            [[0,0,0,0,0,0,0,0,0],
             [0,1,1,1,1,1,1,1,0],
             [0,1,0,0,0,0,0,0,0],
             [0,1,0,1,0,1,0,1,0],
             [0,1,0,1,0,1,0,1,0],
             [0,1,0,1,0,1,0,1,0],
             [0,1,0,0,0,1,0,0,0],
             [0,1,0,1,1,1,0,0,0],
             [0,0,0,0,0,0,0,0,0]] as short[][];

// Declare a procedural image
def s = new Procedural3DImageShort({p -> getRecursiveFiji(p[1], p[0], p[2])}).getRRA();  

// Interval (mainly useless here, but required by BdvFunctions
Interval interval = new FinalInterval([ 0, 0, 0] as long[], [ 9, 9, 0 ] as long[]);

// Display the source in the bdv_h window
bss = BdvFunctions.show( s , interval, "FIJI", BdvOptions.options().addTo(bdv_h) );

// Display options
bss.setDisplayRange(0,1);
bss.setColor(new ARGBType(ARGBType.rgba(101,164,227,255)));


//------------- FUNCTION for recursive FIJI Image generation

int getRecursiveFiji(double x, double y, double level) {
	def valueLevel = (int) (fijiData[((int)x%9)][((int)y%9)])
	if (level<=0) {
		return valueLevel
	} else {
		if (valueLevel==1) {
			if (level>2) {
				level=2;
			}
			return getRecursiveFiji(x*9,y*9,level-1)
		} else {
			return 0
		}
	}
}
  • Duplicate and rotate specified sources:
import ch.epfl.biop.bdv.scijava.command.BdvWindowCreate
import ch.epfl.biop.bdv.scijava.command.edit.transform.BdvSourcesAffineTransform
import bdv.util.BdvHandle

// bdv handle containing the source to transform
#@bdv.util.BdvHandle bdv_h_in
// index of the source in bdv handle input 
#@int index_src
// output bdv window
#@output bdv.util.BdvHandle bdv_h_out

// Command Service
#@CommandService cs

bdv_h_out = (BdvHandle) cs.run(BdvWindowCreate.class, true,
				"is2D",false,
				"windowTitle","Bdv_out",
				"px",0.0,
				"py",0.0,
				"pz",-1.0,
				"s",12.0).get().getOutput("bdvh");

affine_matrix = "[3d-affine: (0.45, -0.05, 0.0, 0.4, 0.05, 0.5, 0.0, -0.2, 0.0, 0.0, 1.0, -0.6)]";

cs.run(BdvSourcesAffineTransform.class, true, 
				"at", affine_matrix,
				"transformInPlace", false,
				"bdvh", bdv_h_in,
				"bdvh_out", bdv_h_out,
				"sourceIndexString", index_src,
				"output_mode", "Add To Bdv").get()

for (int i=0;i<2;i++) {
	cs.run(BdvSourcesAffineTransform.class, true,
				"at", affine_matrix,
				"transformInPlace", false,
				"bdvh", bdv_h_out,
				"bdvh_out", bdv_h_out,
				"sourceIndexString", i,
				"output_mode", "Add To Bdv").get()
}

IJ1 Macro Language

Opens blobs and deforms it and append it in BigDataViewer: 


run("Create Empty BDV Frame", "is2d=false windowtitle=Bdv px=0.0 py=0.0 pz=-1.0 s=850.0");
run("Blobs (25K)");
run("Current IJ1 Image [ImgLib2]");
run("Set Sources Color", "c=255,51,51 sourceindexstring=0"); 
run("Transform Sources (Affine, string)", "sourceindexstring=0 bdvh_out=Bdv output_mode=[Add To Bdv] stringmatrix=[1,-0.1,0,250,\n 0,0.5,0.1,0,\n 0,0,1,0, \n 0,0,0,1] transforminplace=false");

List of all commands

The list of commands of this repository is available in the git repository : https://github.com/BIOP/bigdataviewer_scijava

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