Applications: Difference between revisions
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* Detection of molecular particles, for example FISH data | * Detection of molecular particles, for example FISH data | ||
'''Note:''' The application is currently available | '''Note:''' The application is currently only available on Linux OS. | ||
'''Example images'''<br/> | '''Example images'''<br/> | ||
...will be available soon | ...will be available soon |
Revision as of 09:42, 19 February 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.
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
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.
Name of Plugin:
ScratchAssay_Analysis (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
Neuron Analyzer 2D
The Neuron Analyzer 2D is available since release version 1.1 of MiToBo.
Name of Plugin:
NeuronAnalyzer_2D (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
Note: The application is currently only available on Linux OS.
Example images
...will be available soon