Applications: Difference between revisions

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


== Neuron Analyzer 2D ==
* [[Applications/CellBoundaryExtractor2D | CellBoundaryExtractor2D]] (since MiToBo 1.8.13.1) <br/> extracts cell boundaries from microscopy images using vesselness enhancement filters.


The ''Neuron Analyzer 2D'' is available since release version 1.1 of MiToBo. [[File:NeuronAnalyzer2D.png|right|link=]]
* [[Applications/CytoskeletonAnalyzer2D | Cytoskeleton Analyzer 2D]] (since MiToBo 1.8.13) <br/> is an advanced version of the [[Applications/ActinAnalyzer2D | Actin Analyzer 2D]] operator for quantifying and comparing structural patterns of the cytoskeleton in cells, e.g., of actin microfilament structures or microtubuli patterns.


'''Name of Plugin/Operator:'''<br/>
* [[Applications/PaCeQuantToolset | PaCeQuant]] (released with MiToBo 1.8.6, updated in 2.0), <br/> for quantifying pavement cell shape in a high-throughput manner; the main plugin is supplemented by corresponding tools, i.e. the '''''[[Operators/Tools/Interactive/LabelImageEditor|LabelImageEditor]]''''' and the '''''[[Applications/FeatureColorMapper|FeatureColorMapper]]'''''
NeuronAnalyzer2D (since MiToBo version 1.1)


'''Main features:'''<br/>
* [[Applications/MTBCellCounter | MTB Cell Counter]] (since MiToBo 1.5), <br/> a tool for semi-automatic labeling and counting of spot-like structures like, e.g., plastides, stress granules or p-bodies
* 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:'''<br/>
* [[Applications/MiCa | MiCA - MiToBo Cell Image Analyzer]]<br/> for segmenting cell boundaries and sub-cellular particles in fluorescent microscopy images


The R software environment (http://www.r-project.org/) must be installed to use the ''Neuron Analyzer 2D''.<br/>
* [[Applications/NeuronAnalyzer2D | Neuron Analyzer 2D]]<br/> for segmenting the area of neurites and quantify protein concentrations within these neurites
If R is installed on the system, two environment variables must be set. Perform the following steps on the commandline to set the variables:
* [[Applications/ScratchAssayAnalyzer | Scratch Assay Analyzer]]<br/> for analysis of collective cell migration based on scratch/ wound closure assay images


# export R_HOME="/usr/lib/R" # path to your R installation
* [[Applications/CellMigrationAnalyzer | Cell Migration Analyzer]]<br/> for migration analysis based on single cell tracking
# export R_SCRIPTS="/path/to/ImageJ/share/scripts/R" # path to the R scripts, shipped with MiToBo zip file
 
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'''<br/>
...will be available soon
 
== Scratch assay analysis ==
 
published in<br/>
''M. Glaß, B. Möller, A. Zirkel, K. Wächter, S. Hüttelmaier and S. Posch,<br/>
'''"Scratch Assay Analysis with Topology-preserving Level Sets and Texture Measures"'''.<br/>
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,<br/>
'''"Cell migration analysis: Segmenting scratch assay images with level sets and support vector machines"'''.<br/>
Pattern Recognition, Volume 45, Issue 9, pp. 3154-3165, September 2012.''
 
'''Name of Plugin/Operator:'''<br/>
ScratchAssayAnalyzer (since MiToBo version 0.9.5)
 
'''Description:'''<br/>
* 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'''<br/>
[http://www.informatik.uni-halle.de/mitobo/downloads/scratch_examples.zip Scratch assay images]
 
== MiCA - MiToBo Cell Image Analyzer ==
 
presented at<br/>
''B. Möller and S. Posch,<br/>
'''"MiCA - Easy Cell Image Analysis with Normalized Snakes"'''.<br/>
Workshop on Microscopic Image Analysis with Applications in Biology (MIAAB '11), Heidelberg, Germany, September 2011.''
 
'''Name of Plugin:'''<br/>
CellImageAnalyzer_2D (since MiToBo version 0.9.6)
 
'''Main features:'''<br/>
* 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

Latest revision as of 17:59, 16 May 2020

Several image processing pipelines have already been developed in MiToBo.
Below you can find selected example applications.

  • CellBoundaryExtractor2D (since MiToBo 1.8.13.1)
    extracts cell boundaries from microscopy images using vesselness enhancement filters.
  • Cytoskeleton Analyzer 2D (since MiToBo 1.8.13)
    is an advanced version of the Actin Analyzer 2D operator for quantifying and comparing structural patterns of the cytoskeleton in cells, e.g., of actin microfilament structures or microtubuli patterns.
  • PaCeQuant (released with MiToBo 1.8.6, updated in 2.0),
    for quantifying pavement cell shape in a high-throughput manner; the main plugin is supplemented by corresponding tools, i.e. the LabelImageEditor and the FeatureColorMapper
  • MTB Cell Counter (since MiToBo 1.5),
    a tool for semi-automatic labeling and counting of spot-like structures like, e.g., plastides, stress granules or p-bodies
  • Neuron Analyzer 2D
    for segmenting the area of neurites and quantify protein concentrations within these neurites
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