IQM

IQM | Scientific Image and Signal Analysis in Java

An extensible, flexible, and open source research tool, designed for repeating convenient examination of digital images and signals.
Because quantitative analysis matters.

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Features What can you do with IQM?

Image Analysis

Explore and analyze your digital images quantitatively with a set of standard image processing methods for

  • image denoising and edge detection
  • intensity-, region-, edge-based segmentation
  • image (texture) statistics
  • fractal image analysis
Moreover, create images on your own using dedicated generator functions. Extend the functionality via image operator plugins.

Signal Processing and Visualization

Explore and analyze your digital signals using methods for

  • data extraction
  • plotting
  • signal statistics
  • fractal signal analysis
Moreover, create signals on your own using dedicated signal generator functions. Extend the functionality via signal operator plugins.

Flexible Hybrid Operator Design

Mix signals and images as sources and produce heterogeneous results by processing multi-dimensional data in a single operator.

Advanced Stack Processing

Process your heterogeneous data in batches either in memory or in a "virtual" mode caching the files on the hard disk.

Graphical User Interface

Always stay informed about your current progress by tracking your processing steps visually in intermediate results in an intuitive Java Swing GUI.

Cross-Platform Application

Use the operating system of your choice. IQM runs on every platform, where a Java Virtual Machine exists, such as Windows, Mac OS X, and Linux.

Extensibility via Plugins

Need to have your ideas and algorithms implemented? - Easy: Write your own operator plugin and use it from other operators or in scripts.

Automatization via Scripting

Chaining of different operations is complex and can be summed in an automatic workflow, which we call a script. "Groovy", don't you think?

Machine Learning

Use the powerful methods of Machine Learning provided by the WEKA library. WEKA is shipped with IQM and its algorithms may either be accessed from Java code (operator plugins) directly, or from Groovy code (scripts).

Image Annotations

Annotate your image data, manage the annotations as generic XML documents, and load previously saved annotations to a new canvas.

Open Source

IQM is released under the permissive GNU General Public License version 3.0 (GPLv3). Feel free to check out a copy of the repository and extend or adapt the code to your requirements.

User Guide Application Documentation  

Screenshots

IQM Image Canvas

Examine image stacks with fixed zoom settings.

IQM Signal Visualization

Plot multiple signals in one window and examine data values directly.

Image Annotation Layers

Annotate your images using various shapes for drawing regions of interest on different layers.

IQM Signal Generator

Generate artificial signals using the generator.

IQM Image Generator

Generate artificial images from a set of parameters.

Image Operations

Execute image operators and track the progress in a progress bar.

Signal Import

Import signals from ASCII encoded plain text files.

Integration of ImageJ

Integrate ImageJ in your workflows and share images across applications.

Scripting

Automate common tasks in a convenient scripting environment using the Groovy programming language.

Publications Articles and Conferences

  • more coming soon...

2015

2014

2013

  • M. Mayrhofer-Reinhartshuber, P. Kainz, and H. Ahammer. Image pyramids as a new approach for the determination of fractal dimensions. In Proceedings of the 2013 2nd International Conference of Pattern Recognition Applications and Methods, INSTICC, Barcelona, Spain, February 15-18 2013.
  • M. Mayrhofer-Reinhartshuber, P. Kainz, and H. Ahammer. Fractal characterization of tissue with the new pyramid method. Joint Annual Meeting of the Austrian Physical Society and Swiss Physical Society, Sept. 3-6 2013.
  • P. Kainz, H. Burgsteiner, H. Ahammer, and M. Asslaber. Automated classification of haematopoietic compartments in the human bone marrow using reservoir computing. In International Joint Conference on Computational Intelligence IJCCI 2013, Vilamoura, Portugal, 20-22 Sept. 2013.

2008

  • H. Ahammer, C. Helige, G. Dohr, U. Weiss-Fuchs, and H. Juch. Fractal dimension of the choriocarcinoma cell invasion front. Physica D - Nonlinear Phenomena, 237(4):446–453, Apr. 2008.
  • H. Ahammer, J. M. Kroepfl, C. Hackl, and R. Sedivy. Image statistics and data mining of anal intraepithelial neoplasia. Pattern Recognition Letters, 29(16):2189–2196, 1 Dec. 2008.

2004

  • H. Ahammer and T. T. J. DeVaney. The influence of edge detection algorithms on the estimation of the fractal dimension of binary digital images. Chaos, 14(1):183–188, Mar. 2004.

2003

  • H. Ahammer, T. T. J. DeVaney, and H. A. Tritthart. How much resolution is enough? Influence of downscaling the pixel resolution of digital images on the generalised dimensions. Physica D - Nonlinear Phenomena, 181(3-4):147–156, 15 July 2003.

Contact

Contributing to the IQM project in terms of ideas and algorithms is also possible, hence we encourage researchers and developers to join our project. Please feel free to contact us.
Prof. Dr. Helmut Ahammer
Institute of Biophysics
Medical University of Graz
Harrachgasse 21/IV
8010 Graz, Austria
M: iqm.mug@gmail.com
Get in touch with Helmut Ahammer
Get in touch with Philipp Kainz
Philipp Kainz, MSc
Institute of Biophysics
Medical University of Graz
Harrachgasse 21/IV
8010 Graz, Austria
M: kainzp@users.sf.net
Dr. Michael Mayrhofer-Reinhartshuber
Institute of Biophysics
Medical University of Graz
Harrachgasse 21/IV
8010 Graz, Austria
M: mmayrhofer@users.sf.net
Get in touch with Michael Mayrhofer-Reinhartshuber