Methods Inf Med 2012; 51(05): 441-448
DOI: 10.3414/ME11-02-0031
Focus Theme – Original Articles
Schattauer GmbH

MITK Diffusion Imaging

K. H. Fritzsche
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
2   German Cancer Research Center, Section Quantitative Imaging-based Disease Characterization, Heidelberg, Germany
,
P. F. Neher
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
I. Reicht
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
T. van Bruggen
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
C. Goch
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
M. Reisert
3   University Hospital Freiburg, Department of Radiology, Medical Physics, Freiburg, Germany
,
M. Nolden
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
S. Zelzer
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
H.-P. Meinzer
1   German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany
,
B. Stieltjes
2   German Cancer Research Center, Section Quantitative Imaging-based Disease Characterization, Heidelberg, Germany
› Author Affiliations
Further Information

Publication History

received:13 October 2011

accepted:23 March 2012

Publication Date:
20 January 2018 (online)

Summary

Background: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets.

Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field.

Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITKDI, are demonstrated using in-vivo datasets.

Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use in stallable application.

Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

 
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