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Intro

  • This is a tutorial on ImageJ analysis that is of interest to biologists.                                             

  • The optimistic aim of this tutorial is to help explain the scientific use of ImageJ through its application in cell biology. Specifically, the study will obtain and derive morphometric and densitometric parameters of human red blood cells.                                                                  

  • Several key steps are illustrated in detail throughout the text to help address some of the complexities and difficulties in using ImageJ as a scientific tool.                                                                                                               

  • On this page, you will find information on key concepts in this tutorial:                                         1) ImageJ; 2) morphometry; 3)densitometry.                                                                     

  • Some relevant ImageJ tutorials are also listed to provide as background to this study. 

 

ImageJ

Morphemetric Parameters

Measurements related to the external shape and dimensions of landforms, living organisms or other objects (Gelsvartas, undated; Rohlf, 2015). It is essentially the quantitative analysis of the form of an object.This includes factors such as roundness, circularity, area, permimter and diameter.
 
 

Densitometric Parameters

In this tutorial, is it a quantitative measurement relating to the minimum, maximum, and mean gray value of an image or a selection in an image (Empix Imaging, 2015).
 
Gray value: The intensity of each pixel, which is 0-255 in 8-bit images (RSB, 2015c).
 
This study will use gray value to derive the approximated percentage coverage of red blood cells, red blood cell coverage area, and the number density of red blood cells.
 

Concepts

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ImageJ

ImageJ is a Java-based program that helps solve many image processing and analysis problems (Collins, 2007; RSB, 2015a). 

 

In relation to this turotial, there are many existing materials on the scientific use of ImageJ, such as: 1) the quantification of colour in stained liver tissue (RSB, 2015b); 2) the measurement of cell fluorescence (Bankhead, 2014); 3) and the measurement of areas in histological samples (Jensen, 2013). 

 

This tutorial will address a new area - Morphometry and Densitometry, that will help advance our understanding of ImageJ in the fields of biological science. 

The morphemetric parameters measured in this study are:

 

Feret's Diameter:  Similar to the maximum diamater of a spacial object, it is the distance between two parallel tangents of the two-dimensional outline of a particle shape (Quantachrome, 2015)

 

Aspect Ratio (AR): The aspect ratio of the particle’s fitted ellipse.                          

(RSB, 2015c)

 

Roundness:  A measure of how close the particle is to a circle

as the inverse of Aspect Ratio. (RSB, 2015c)

 

 

Solidity: The quality of being firm and strong in structure. (RSB, 2015c)

 

Circularity: Another approach of measuring how close the particle

is to a circle through the ratio between area and perimeter. (RSB, 2015c)

 

 

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Examples of Other ImageJ Tutorials

If you're new to ImageJ, it will help to take a look at the tutorials below on some basic ImageJ analysis before proceeding further in this tutorial. 

Quantifying stained liver tissue area with Image J (Ian, 2012)

 

Counting Cells with ImageJ (Foley, 2014)

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