Features

From MiToBo
Revision as of 10:19, 21 February 2013 by Moeller (talk | contribs)
Jump to navigationJump to search

The Microscope Image Analysis Toolbox MiToBo contains a lot of new features for scientists, who want to develop
new algorithms in the field of custom image analysis and processing, and for those who want to use
custom plugins from ImageJ in their daily research.

MiToBo's 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 commandline interfaces are automatically generated
    • all operators can directly be used in ImageJ without need for additional programming effort

  • 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.

  • Grappa - a graphical programming editor:
    The operator concept of Alida allows for generic handling of operators. Thereby not only GUIs can automatically be generated, but also graphical programming is significantly simplified. Alida includes Grappa, a graphical programming editor for designing workflows, which is also shipped with MiToBo and provides user with an intuitive tool for developing sophisticated image analysis workflows.

  • a large collection of Applications:
    MiToBo not only provides a framework for developing new image analysis algorithms,
    but also ships with a collection of ready-to-use image analysis algorithms, e.g.
    • morphological operators
    • basic linear and non-linear filters
    • thresholding and component labeling
    • active contour segmentation
    • ...

    In addition, also more complex tools are included, take a look at the applications page for some examples.