LaRoMe

What a strange name !

LaRoME = Label + Region Of Interest + Measure

Label image (aka Count Masks): An image in which pixels of an object have all the same value. Each object has a unique value.

Measurement image: An image in which pixels of an object have all the same value, corresponding to a measurement (Area, Angle, Mean...)

Scripting

You can find a Macro language and a Groovy examples in the scripts folder.

Installation

You can install LaRoMe via the PTBIOP update site.

Help>Update..., Manage Update Sites, select PTBIOP in the list (cf image below), Apply changes, Restart Fiji.

ImageJ plugin

Plugins > BIOP > Image Analysis > ROIs >

run("Label image to ROIs")

From a Label Image(§), generate ROIs and add them to the ImageJ ROI Manager.

Macro Language, you can use run("Label image to ROIs"); as in the example code below :

if (nImages>0) run("Label image to ROIs");

Known Limitations and Advantages

Note In the case of RGB label images (instead of 8, 16 or 32 bit images), this plugin can yield accurate labels so long as touching labels do not share the same RGB color. This is in contrast to run("Label image to composite ROIs") that will systematically put separate labels together as the same ROI if they have the same RGB color, no matter wether they are touching or not. Your best best is to avoid RGB images as label images :)

Warning Following a post made on the ImageSC forum, "Label image to ROIs" cannot handle composite ROIs* (ROIs with holes or disconnected ROIs). In case you expect complex ROIs of this type, you should use run("Label image to composite ROIs")

run("Label image to composite ROIs")

Uses the same method as Analyse Particles with the "Composite ROIs" option checked. This method was added in November 2022 as a response to a post made on the ImageSC forum

Warning In the case of RGB label images (instead of 8, 16 or 32 bit images), this plugin will potentially merge separate labels (that are physically apart, but share the same RGB color) into a single ROI. Your best best is to avoid RGB images as label images if you can :)

run("ROIs to Label image", "")

From an Image and some ROIs, generates a Label Image.

Macro Language, you can use run("ROIs to Label image"); as in the example code below :

if ((nImages>0)&&( roiManager("count") > 0)) run("ROIs to Label image");
else if (roiManager("count") == 0) print("No existing ROIs to make Label Image");
else if (nImages==0) print("No open image to use as template for dimensions");

run("ROIs to Measurement Image", "column_name=Area");

From an Image, some ROIs and a selected Measurement generates a Measurement Image.

Measurement list encompass (change column_name ) : "Area", "Angle", "AngleVert","AR", "Circ.", "Major","Minor","Mean","Median","Mode","Min","Max", "Perim."

Angle measure is based on horizontal, the AngleVert measure is based on vertical (substracting 90 )

AR, Aspect Ratio = Major / Minor

Circ., Aspect Ratio = 4 * PI * Area / Perim.^2

Macro Language, you can use run("ROIs to Measurement Image"; as in the example code below:

run("ROIs to Measurement Image" , "column_name=Area pattern=[]");

With the lastest version (0.2) you can now use the ROI name with the option Pattern to define label (application for tracking or 3D-objects). For example , using ijs-script you can use Track-(\d*):.* to generate a label image per track.