ImageJ Documentation Wiki

The Microscope Image Analysis Toolbox MiToBo is a collection of various image analysis algorithms ranging from basic image processing operations to sophisticated segmentation techniques.
MiToBo for example includes:

- morphological operators
- linear/non-linear filtering
- image enhancement techniques
- binarization methods
- 2D snakes including different energies
- PDE and nonPDE levelsets including different energies
- undecimated wavelet transformation
- texture measures
- …

In addition, MiToBo offers various specialized tools for the analysis of biomedical image data:

- Scratch Assay Analyzer for analyzing microscope image data from cell migration experiments [1,2]

- Neuron Analyzer for the segmentation of neurons in 2D microscope images

- Actin Analyzer 2D for quantifying structural differences in actin or microtubuli organization

- MTB Cell Counter for semi-automatic counting of sub-cellular structures in plants like plastides, stromuli and stomata

- Particle Detector for detecting sub-cellular particles in 2D microscopy images based on wavelet transformations [3]

- 2D Nucleus Detector for segmenting nuclei in DAPI stained microscope images

- …

For more details about these applications visit MiToBo's Applications and Projects page.

On the programming level MiToBo offers a programmer friendly framework for easy implementation of new algorithms and ImageJ plugins, respectively, including automatically generated graphical and command line user interfaces for these algorithms. In addition, MiToBo provides an automatic documentation of processing pipelines based on operators and plugins implemented within the MiToBo framework, and also all operators are available in the graphical programming editor Grappa shipped with MiToBo. Most of this functionality is provided by the Alida library which forms the fundament of MiToBo.

The MiToBo toolbox is developed by Birgit Möller and Stefan Posch at the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany, by the Pattern Recognition and Bioinformatics Group at the Institute of Computer Science, Faculty of Natural Sciences III, in cooperation with Markus Glaß and Danny Misiak working at the Division for Molecular Cell Biology, Institute of Molecular Medicine, of the Medical Faculty of the Martin Luther University.

Contact:
Dr. Birgit Möller or Prof. Dr. Stefan Posch

We are always happy to receive feedback, questions, comments, bug reports, feature wishes, …!

MiToBo is licensed under GPL, version 3.0.

The current release of the MiToBo toolbox as well as further information on the framework, installation guidelines, latest news, a user and programmer guide, and also the Javadoc documentation can be found on MiToBo's website:

http://www.informatik.uni-halle.de/mitobo

• B. Möller, M. Glaß, D. Misiak and S. Posch, MiToBo – A Toolbox for Image Processing and Analysis, Journal of Open Research Software 4: e17, DOI: http://dx.doi.org/10.5334/jors.103, 2016.
• L. Franke, B. Storbeck, J. L. Erickson, D. Rödel, D. Schröter, B. Möller, and M. H. Schattat, The 'MTB Cell Counter' a versatile tool for the semi-automated quantification of sub-cellular phenotypes in fluorescence microscopy images. A case study on plastids, nuclei and peroxisomes,
  Journal of Endocytobiosis and Cell Research, 26:31-42, 2015.
• B. Möller and S. Posch, A Framework Unifying the Development of Image Analysis Algorithms and Associated User Interfaces, Proc. of 13th IAPR International Conference on Machine Vision Applications (MVA '13), pp. 447-450, Kyoto, Japan, May 2013.
• B. Möller, E. Piltz and N. Bley, Quantification of Actin Structures using Unsupervised Pattern Analysis Techniques, Proc. of Int. Conf. on Pattern Recognition (ICPR '14), IEEE, pp. 3251-3256, Stockholm, Sweden, August 2014.
• D. Misiak, S. Posch, M. Lederer, C. Reinke, S. Hüttelmaier and B. Möller, Extraction of Protein Profiles from Primary Neurons using Active Contour Models and Wavelets, Journal of Neuroscience Methods , vol. 225, pages 1-12, March 2014.
• M. Glaß, B. Möller and S. Posch, Scratch Assay Analysis in ImageJ, Proc. of ImageJ User & Developer Conference, pp. 211-214, ISBN 2-919941-18-6, Mondorf-les-Bains, Luxembourg, October 2012.
• M. Glaß, B. Möller, A. Zirkel, K. Wächter, S. Hüttelmaier and S. Posch, Cell Migration Analysis: Segmenting Scratch Assay Images with Level Sets and Support Vector Machines, Pattern Recognition, vol. 45, no. 9, pp. 3154-3165, Elsevier, September 2012.