Applications: Difference between revisions

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# export R_HOME="/usr/lib/R" # path to your R installation
# export R_HOME="/usr/lib/R" # path to your R installation
# export R_SCRIPTS="/path/to/ImageJ/share/scripts/R" # path to the R scripts, shipped with MiToBo zip file
# export R_SCRIPTS="/path/to/ImageJ/share/scripts/R" # path to the R scripts, shipped with MiToBo zip file
# libjri.so must be in the LD_LIBRARY_PATH


To save these variables permanently, copy the commands above to your local .bashrc file.
To save these variables permanently, copy the commands above to your local .bashrc file.

Revision as of 14:19, 5 December 2013

Several image processing pipelines have already been developed in MiToBo.
Below you can find selected example applications, some of them have been published already.

Neuron Analyzer 2D

The Neuron Analyzer 2D is available since release version 1.1 of MiToBo.

NeuronAnalyzer2D.png

Name of Plugin/Operator:
NeuronAnalyzer2D (since MiToBo version 1.1)

Main features:

  • Neuron boundary detection based on active contours
  • Identification of structural neuron parts, like soma, neurites and growth cones
  • Morphology analysis, e.g., neurite length, average neurite width, number of branch and end points, growth cone size and shape roundness, etc.
  • Extraction of molecular profiles from fluorescently labeld molecules
  • Detection of molecular particles, for example FISH data

Installation:

The R software environment (http://www.r-project.org/) must be installed to use the Neuron Analyzer 2D.
If R is installed on the system, two environment variables must be set. Perform the following steps on the commandline to set the variables:

  1. export R_HOME="/usr/lib/R" # path to your R installation
  2. export R_SCRIPTS="/path/to/ImageJ/share/scripts/R" # path to the R scripts, shipped with MiToBo zip file
  3. libjri.so must be in the LD_LIBRARY_PATH

To save these variables permanently, copy the commands above to your local .bashrc file.

Note: The application is currently only available on Linux OS.

Example images
...will be available soon

Scratch assay analysis

published in
M. Glaß, B. Möller, A. Zirkel, K. Wächter, S. Hüttelmaier and S. Posch,
"Scratch Assay Analysis with Topology-preserving Level Sets and Texture Measures".
Proc. of Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA '11), LNCS 6669, pp. 100-108, Springer, Las Palmas de Gran Canaria, Spain, June 2011.

M. Glaß, B. Möller, A. Zirkel, K. Wächter, S. Hüttelmaier and S. Posch,
"Cell migration analysis: Segmenting scratch assay images with level sets and support vector machines".
Pattern Recognition, Volume 45, Issue 9, pp. 3154-3165, September 2012.

Name of Plugin/Operator:
ScratchAssayAnalyzer (since MiToBo version 0.9.5)

Description:

  • Quantifies the scratch area in monolayer cell culture images with levelset techniques
  • Combines the results from images of different time points in a results table


Example images
Scratch assay images

MiCA - MiToBo Cell Image Analyzer

presented at
B. Möller and S. Posch,
"MiCA - Easy Cell Image Analysis with Normalized Snakes".
Workshop on Microscopic Image Analysis with Applications in Biology (MIAAB '11), Heidelberg, Germany, September 2011.

Name of Plugin:
CellImageAnalyzer_2D (since MiToBo version 0.9.6)

Main features:

  • Integrated analysis of multi-channel microscope images of cells
  • Allows for segmentation of cells, nuclei and sub-cellular structures
  • Techniques subsume active contours, wavelets, morphological operators, and others
  • Visualization and quantitative summary of segmentation results