Quantitative Image Analysis

Cell biology is often perceived as the science of beautiful images. However, images contain much more information than usually exploited. Functional analysis is often based on comparisons (such as different concentrations of a compound, mutant versus wild type, different time points). How to do this with images? It is possible - when the visual information hidden in images is quantified. This is the idea of quantitative image analysis. Each application requires a specific approach, but there are some common principles that are helpful to avoid misinterpretations.

Quantitative image analysis is generally conducted by support of software, which is often very expensive (typically in the range of several 10 k€). However, there are versatile open-source alternatives such as the programme ImageJ, which allows to do most investigations free of charge, if one knows what one wants to do.

Your task will be to exercise this approach using surface waxes of grapevine. Your data set consists in five SEM images from the forth leaf of different grapevine genotypes. The project is targeted on defining resources for breeding (surface waxes help to cope with drought stress to adapt for global climate change). We have identified wild grape genotypes that form more surface wax. This has to be quantified. The method depends a bit on the parameters, such as the circularity or the particle size. Here, you should measure the data set, first setting a parameter set that gives you a reasonable representation of the structures you want to measure. Then you quantify the five images. After that you run a series, where you vary particle size (spanning a factor of 5-fold), and another series, where you modify circularity (going up or down by a 0.1 unit from your original set). Plot the results to see, how robust or variable the output is and discuss this.

  • To download the programme and also get access to informational ressources, including plugins for specific applications: IMAGE J Webpage
  • To find some background on the principles of quantitative image analysis refer to Ilias: Fakultät für Chemie und Biowissenschaften - current semester - BIO_MA_FOR_1201_Plant_Cell_Biology
  • To find the data set and specific instructions on the use of ImageJ for this application refer to Illias: Fakultät für Chemie und Biowissenschaften - current semester - BIO_MA_FOR_1201_Plant_Cell_Biology