Features: Difference between revisions

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__NOTOC__
__NOTOC__
The Microscope Image Analysis Toolbox MiToBo contains a lot of new features for scientist, who want to develop<br/>
The Microscope Image Analysis Toolbox MiToBo is a collection of basic and advanced image processing and analysis tools and algorithms.<br>
new plugins and algorithms in the field of custom image analysis and processing, and those who want to use<br/>
They for example subsume...
custom plugins from [http://rsbweb.nih.gov/ij/ ImageJ] in their daily research.<br/><br/>
<ul>
<li> morphological operators
<li> basic linear and non-linear filters
<li> ridge and vesselness detectors
<li> thresholding and component labeling
<li> extraction of region and contour features
<li> watershed segmentation
<li> active contour segmentation with snakes and level sets
<li> texture measures
<li> ...
</ul>
In addition, it ships with some more elaborate and specialized applications, for example targetting at
<ul>
<li> scratch assay analysis
<li> neurite tracing
<li> quantification of filament structure organization
<li> semi-automatic counting of sub-cellular entities
<li> ...
</ul>
For more information on these applications take a look at the [[applications | applications page]].


A list of all contained features and their description in detail can be found below.<br/><br/>
To ease the development of more complex analysis pipelines MiToBo includes a graphical editor for user-friendly workflow development:<br>
[[file:Grappa_logo.png|135px|left|link=]]
<ul>
<li> '''Grappa''' - a graphical programming editor<br><br>
The operator concept of [http://www.informatik.uni-halle.de/alida/ Alida], which forms the fundament of MiToBo, allows for generic handling of operators.<br>
It supports fully automatic generation of GUIs and graphical programming of complex analysis pipelines.<br>
To this end Alida includes Grappa, a graphical programming editor for designing workflows, which is also shipped with MiToBo<br>
and provides users with an intuitive tool for developing sophisticated image analysis workflows.<br>
All Alida and consequently also all MiToBo operators are right away available as operator nodes in Grappa and form the building blocks for workflows.<br>
</ul><br>


'''[[#Operators|Operators]]'''<br/>
Finally, besides providing ready-to-use image analysis functionality MiToBo also contains a lot of valueable features for scientists, who want to develop<br/>
The operator concept is one of the major features in MiToBo. By developing such operators, the processing steps<br/>
new algorithms in the field of image analysis and processing, and for those who want to use custom plugins from [http://rsbweb.nih.gov/ij/ ImageJ] in their daily research.<br/>
can be linked to a directed graph structure, which allows '''self-documentation''' of the entire image analysis process.<br/>
Each resulting data object being the result of a certain operator or sequence of operations
is associated with an '''history graph''' in XML format.<br/>
Included operators can be found [[#Operators|here]].<br/><br/>


'''[[#Plugins|Plugins]]'''<br/>
These main features are:
The well known and very powerful plugin concept of [http://rsbweb.nih.gov/ij/ ImageJ] is also available in MiToBo.<br/>
<ul>
Every user and developer, using MiTobo, can easily create new plugins and customize existing [http://rsbweb.nih.gov/ij/plugins/index.html ImageJ plugins],<br/>
<li> an advanced '''operator concept''':<br/>
to use the automatic documentation of the plugin via the operator concept of MiToBo for instance.<br/>
MiToBo relies on the operator concept of [http://informatik.uni-halle.de/alida/ Alida]. Alida is a library to ease the development of data analysis algorithms including mechanisms for automatic generation of user interfaces,<br>
Included plugins can be found [[#Plugins|here]].<br/><br/>
fully automatic documentation of analysis procedures, and inherent support for developing workflows.<br/>
 
MiToBo adopts all these features:
'''[[#Data_types|Data types]]'''<br/>
<ul>
MiToBo defines a set of its own data types. For example, a new image data type was developed to improve the<br/>
<li> results of image analysis procedures are automatically linked to a directed graph structure documenting the  
[http://rsbweb.nih.gov/ij/ ImageJ] image classes.<br/>
entire image analysis process,<br> i.e. every result of a certain operator or sequence of operations is associated with a '''history graph''' in XML format
A short overview of some basic MiToBo data types can be found [[#Data types|here]].<br/><br/>
<li> for all operators '''graphical and command line interfaces''' are automatically generated
 
<li> all operators can '''directly be used in ImageJ''' without need for additional programming effort
'''[[#Applications|Applications]]'''<br/>
</ul>
Using the plugin and operator concept combined with the large amount of already implemented datatypes and operators,<br/>
<li> additional '''data types''':<br/>
a huge coupple of applications on biological and biomedical images can be developed.<br/>
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/>
An overview of current implemented applications, developed by the MiToBo developer team, can be found [[#Applications|here]].<br/><br/>
<br/>
 
</ul><br>
----<br/>
 
== Operators ==
Todo: Short listing and discription of included operators/or of an special selection.<br/>
...
 
== Plugins ==
Todo: Short listing and discription of included plugins.<br/>
...
 
== Data types ==
Todo: Short listing and discription of included data types/or of an special selection of basic types like in the manual.<br/>
 
== Applications ==
Todo: Short listing and discription of included applications.<br/>
...
 
----
== Future development ==
...

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 logo.png
  • 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
  • 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.



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