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The Microscope Image Analysis Toolbox MiToBo
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MiToBo defines a set of its own data types. For example, a new image data type was developed to improve the [http://rsbweb.nih.gov/ij/ ImageJ] image classes.<br/><br/>
Latest revision as of 10:40, 31 January 2017
The Microscope Image Analysis Toolbox MiToBo is a collection of basic and advanced image processing and analysis tools and algorithms.
They for example subsume...
- morphological operators
- basic linear and non-linear filters
- ridge and vesselness detectors
- thresholding and component labeling
- extraction of region and contour features
- watershed segmentation
- active contour segmentation with snakes and level sets
- texture measures
In addition, it ships with some more elaborate and specialized applications, for example targetting at
- scratch assay analysis
- neurite tracing
- quantification of filament structure organization
- semi-automatic counting of sub-cellular entities
For more information on these applications take a look at the applications page.
To ease the development of more complex analysis pipelines MiToBo includes a graphical editor for user-friendly workflow development:
- Grappa - a graphical programming editor
The operator concept of Alida, which forms the fundament of MiToBo, allows for generic handling of operators.
It supports fully automatic generation of GUIs and graphical programming of complex analysis pipelines.
To this end Alida includes Grappa, a graphical programming editor for designing workflows, which is also shipped with MiToBo
and provides users with an intuitive tool for developing sophisticated image analysis workflows.
All Alida and consequently also all MiToBo operators are right away available as operator nodes in Grappa and form the building blocks for workflows.
Finally, besides providing ready-to-use image analysis functionality MiToBo also contains a lot of valueable features for scientists, who want to develop
new algorithms in the field of image analysis and processing, and for those who want to use custom plugins from ImageJ in their daily research.
These main features are:
- an advanced operator concept:
MiToBo relies on the operator concept of Alida. Alida is a library to ease the development of data analysis algorithms including mechanisms for automatic generation of user interfaces,
fully automatic documentation of analysis procedures, and inherent support for developing workflows.
MiToBo adopts all these features:
- results of image analysis procedures are automatically linked to a directed graph structure documenting the
entire image analysis process,
i.e. every result of a certain operator or sequence of operations is associated with a history graph in XML format
- for all operators graphical and command line interfaces are automatically generated
- all operators can directly be used in ImageJ without need for additional programming effort
- results of image analysis procedures are automatically linked to a directed graph structure documenting the entire image analysis process,
- additional data types:
MiToBo defines a set of its own data types. For example, a new image data type was developed to improve the ImageJ image classes.